Structural Perturbations and Destabilizing Mutations in RAD51C and RAD51D Reveal Mechanisms of Cancer Risk

Structural Perturbations and Destabilizing Mutations in RAD51C and RAD51D Reveal Mechanisms of Cancer Risk | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Structural Perturbations and Destabilizing Mutations in RAD51C and RAD51D Reveal Mechanisms of Cancer Risk Vaishnavi Gund, Siddharth Sharma, Sidhartha Singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7450048/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Breast and ovarian cancers remain among the most prevalent malignancies affecting women worldwide, with only 20% of hereditary cases explained by BRCA1/2 mutations. This highlights the importance of alternative susceptibility genes such as RAD51C and RAD51D, which play essential roles in homologous recombination repair (HRR). In this study, a comprehensive in silico analysis was conducted to identify deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in RAD51C and RAD51D that may contribute to genomic instability and increased cancer risk. A total of 19,195 SNPs were retrieved and analyzed using multiple computational tools including SIFT, PolyPhen-2, PANTHER, PROVEAN, PhD-SNP, SNP&GO, I-Mutant, and MUpro. Eleven high-risk nsSNPs in RAD51C and several in RAD51D were identified, primarily affecting the ATP-binding and DNA repair domains. Structural modeling, docking, and molecular dynamics simulations revealed that mutations such as R212H, L219S, and L262V in RAD51C and S207L, S207P, and A210E in RAD51D significantly alter protein stability, flexibility, and binding affinity with interaction partners like XRCC2, RAD51B, and RAD51C. These alterations may compromise DNA repair mechanisms, contributing to carcinogenesis. Our findings underscore the utility of integrated computational approaches in identifying pathogenic variants and provide a molecular basis for understanding RAD51C/D-related cancer susceptibility. This work lays the groundwork for future experimental validation and supports the application of personalized medicine in HR-deficient tumors. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction Breast and ovarian cancers are among the most common and lethal malignancies affecting women globally. While mutations in BRCA1 and BRCA2 genes are well-established contributors to hereditary breast and ovarian cancer (HBOC), they account for only approximately 20% of familial cases, suggesting the involvement of additional genetic factors (Michael P. et al., 2006). Increasing evidence points to other DNA repair genes—such as RAD51C, RAD51D, CHEK2, and NBN—as significant contributors to cancer susceptibility, particularly due to their roles in DNA double-strand break (DSB) repair, cell cycle regulation, and apoptosis (Nielsen et al., 2016 ; Damiola et al., 2016 ). RAD51C and RAD51D, both located on chromosome 17 (q22 and q12, respectively), encode proteins essential for error-free repair of DSBs via the homologous recombination (HR) pathway. RAD51C forms part of two key complexes: the BCDX2 complex (RAD51B-RAD51C-RAD51D-XRCC2) and the CX3 complex (RAD51C-XRCC3), both of which are required for efficient strand invasion and stabilization of RAD51 nucleoprotein filaments during HR (Chun et al., 2016; Godthelp et al., 2002 ). RAD51D, on the other hand, facilitates homology recognition and repair by binding to single-stranded DNA post-damage (Kim et al., 2011 ). Amplification of RAD51C at chromosome 17q23 has been observed in breast tumors, suggesting its oncogenic potential in certain contexts despite its tumor suppressor function. Germline pathogenic variants (GPVs) in RAD51C and RAD51D have been associated with significantly elevated risks of breast and ovarian cancers ( Turnbull et al., 2012 ; Loveday et al., 2011 ). Recent advances in genome-wide association studies (GWAS) have highlighted the importance of single nucleotide polymorphisms (SNPs) in identifying genetic predispositions to various cancers (Omariba et al., 2020 ). However, the exponential growth in SNP data presents challenges in identifying those that are functionally relevant. Computational tools have become essential in filtering out deleterious variants. In a recent study, Anwaar et al. ( 2023 ) identified clinically significant mutations in breast cancer families and used multiple pathogenicity prediction tools to classify variants such as G125V and L138F in RAD51C as high-risk based on their conserved domain positions and structural impact. Similarly, RAD51D variants have been shown to compromise HR efficiency. Cells deficient in RAD51D are particularly sensitive to poly (ADP-ribose) polymerase (PARP) inhibitors, highlighting a therapeutic avenue for tumors harboring RAD51D mutations. Structural analyses have also shown that certain SNPs in RAD51D affect protein folding and stability, influencing sensitivity or resistance to treatments (Somyajit et al., 2022 ; McAlpine et al., 2018 ). The integration of bioinformatics and structural biology provides critical insights into tumor heterogeneity and genetic vulnerability. Tools such as SIFT and PolyPhen offer rapid, cost-effective approaches for identifying harmful SNPs, which can serve as biomarkers for patient stratification and targeted therapies (de Almeida et al., 2022 ). These findings also support personalized medicine initiatives, as individuals carrying high-risk RAD51C or RAD51D variants may benefit from tailored screening and preventive strategies (Zhang et al., 2020 ). Moreover, identifying population-specific variants contributes to the development of ethnically tailored interventions, a crucial aspect of global precision oncology (Sirugo et. Al., 2016). 2. Materials and method 2.1 Data Retrieval: We compiled a comprehensive catalog of Single Nucleotide Polymorphisms (SNPs) associated with the RAD51C and RAD51D genes by querying the NCBI dbSNP database using "RAD51C" and "RAD51D" as search terms. The retrieved SNPs were then filtered based on specific selection criteria ( https://www.ncbi.nlm.nih.gov ). Additionally, the complete FASTA sequences of the human RAD51C and RAD51D proteins were obtained from the NCBI database. Figure 1 illustrates a schematic representation of the methodology employed in this study. 2.2 Predicting deleterious nsSNPs: A variety of web servers and computational tools were used to assess all missense non-synonymous single nucleotide polymorphisms (nsSNPs) associated with the RAD51C and RAD51D genes. Because of their ability to forecast the functional effects of genetic variants—especially nsSNPs—which are essential for comprehending the genetic pathways underlying disease, tools like SIFT, PolyPhen-2, and PANTHER were especially selected. These prediction tools provide a comprehensive assessment of each variant's pathogenic potential by combining information on sequence conservation, structural traits, and biological context. Based on sequence homology, evolutionary conservation, and the physicochemical characteristics of amino acids, the SIFT (Sorting Intolerant From Tolerant) tool ( http://sift.bii.a-star.edu.sg ) assesses whether an amino acid substitution is likely to affect protein function. It works on the premise that amino acids that are essential for protein function are typically conserved across species, increasing the likelihood that replacements at these locations will have negative effects (Ng and Henikoff, 2001 ). According to Ng et al. (2003), SIFT scores range from 0 to 1, with a score below 0.05 signifying a detrimental (intolerant) effect and a score over 0.05 indicating that the substitution is probably tolerated. It is a commonly used tool in genome-wide variant research because to its ability to examine big datasets effectively. THMM, Colis2, and SignalP are among the algorithms used by the PolyPhen-2 (Polymorphism Phenotyping v2) program to assess the possible impacts of amino acid changes on the structure and functionality of human proteins (George et al., 2008 ). It classifies missense variations as benign, potentially harmful, or probably harmful after analyzing the position of the amino acid change, mapping SNPs onto known 3D protein structures, and including sequence annotations and structural characteristics. The tool is a reliable resource for evaluating the impact of nsSNPs implicated in complicated disorders because of its two-tiered prediction approach, which improves accuracy. The PANTHER (Protein Analysis through Evolutionary Relationships) tool ( http://pantherdb.org/tools/cSNPscoreForm.jsp ) predicts the possible structural and functional effects of amino acid substitutions by assessing the evolutionary conservation of particular amino acid residues across different species. Additionally, it evaluates both coding and non-coding variations' probable effects (Mi et al., 2021 ). PANTHER assists in identifying mutations that might affect the function of proteins by looking at evolutionary constraints on protein-coding areas. Researchers can also decipher the biological implications of genetic variations in the context of cellular systems and pathways thanks to its integrated pathway-level annotations. A prediction tool called PhD-SNP (Predictor of human Deleterious Single Nucleotide Polymorphisms) classifies genetic variants by combining evolutionary sequence data with support vector machine (SVM) algorithms ( http://SNPs.biofold.org/phd-snp/phd-snp.html ). By building its predictive model from a large dataset of mutations that are either neutral or known to be disease-associated, it is able to evaluate the possible influence of SNPs according to their particular sequence context. For large-scale variation analysis, PhD-SNP is a reliable option due to its great generalizability across a variety of datasets and strong prediction performance (Capriotti et al., 2017 ). To ascertain the probability that a particular mutation is linked to a disease, SNPs&GO is a predictive method that incorporates Gene Ontology (GO) annotations (Capriotti et al., 2013 ). SNPs&GO provides a more thorough assessment of the potential effects of mutations on protein function by combining sequence-based features with functional annotations. By placing the variant in a biological context using GO keywords associated with the target protein, it increases the accuracy of its predictions in differentiating between benign and harmful mutations (Calbrese et al., 2009). Because of their speed, ease of use, and compatibility with high-throughput analyses, SIFT and PolyPhen-2 are frequently chosen for the preliminary evaluation of non-synonymous SNPs (nsSNPs). These tools are perfect for large-scale applications like genome-wide association studies (GWAS) because of their proven performance, efficiency, and intuitive user interfaces. Even though programs like MutPred and SNAP2 provide more in-depth information—such molecular mechanism predictions and functional implications—they are typically more computationally intensive and generate intricate results that need expert interpretation. While SNAP2, which is powered by neural networks, performs well in a variety of poorly conserved regions, it produces granular predictions that may be difficult to interpret without specialized knowledge (Hecht et al., 2015 ). MutPred combines machine learning with functional annotations to predict effects such as changes in binding affinity (Li et al., 2009 ). On the other hand, researchers with limited infrastructure can more easily use SIFT and PolyPhen-2 since they are speedier and require fewer computer resources. They are therefore especially helpful for the preliminary screening and variant prioritization. Conversely, SNAP2 and MutPred are more appropriate for targeted, in-depth functional investigations where a thorough grasp of the mechanisms is crucial. Only nsSNPs that were consistently identified by all six methods as harmful or detrimental were chosen for downstream study. The disparities and inconsistencies that could result from output variances across several prediction platforms are reduced by this consensus-based method. 2.3 Modeling the native RAD51C and RAD51D protein using MODELLER v10.2: MODELLER v10.2, a widely used tool that employs comparative homology modeling to predict protein structures. Both versions of MODELLER were obtained from Andrej Sali’s official website ( https://salilab.org/ ). The software supports execution with or without a Python environment; if Python is not installed, modeling scripts can still be run via the command: mod10.2 SCRIPT_NAME.py. For Python-based modeling, MODELLER offers pre-configured scripts for sequence alignment and structure generation. The homology modeling process followed a structured approach: selecting suitable template structures via BLAST, validating the chosen templates by aligning them with the target sequence, constructing the 3D models, and finally assessing model quality using a Ramachandran plot. Since the full protein structures of RAD51C and RAD51D proteins were already present in PDB database so we have used them as our native proteins for the modelling of mutant proteins respectively. The resulting protein models were saved under the names RAD51C_WILD and RAD51D_WILD, respectively. 2.4 Generation of mutant protein structures: The most accurately validated model was selected and subsequently used as a template to introduce mutations into the protein structures, followed by evaluation using MODELLER version 10.2. This process combines comparative modeling techniques with optimization algorithms to incorporate specific alterations into the protein sequence, including amino acid substitutions, insertions, or deletions. During modeling, MODELLER aligns the target sequence with the chosen template structure, utilizing the spatial configuration of atoms from the template as a reference. It then refines the mutant model by adjusting dihedral angles, bond lengths, and other structural parameters to produce a reliable three-dimensional structure of the mutated protein. 2.5 Model Validation: All selected mutant models were validated using Ramachandran plots, a standard method in structural biology for evaluating the stereochemical quality of protein structures. Named after G. N. Ramachandran, the plot graphically displays the phi (ϕ) and psi (ψ) dihedral angles of amino acid residues, which correspond to rotations around the Cα–C and C–N bonds, respectively. Each point on the plot represents the torsion angle combination for a specific residue within the protein structure. The plot is segmented into allowed and disallowed regions, determined by steric constraints and atomic clashes. Allowed regions signify energetically favorable conformations that are structurally viable, while disallowed regions highlight unlikely or sterically hindered conformations. Following structural validation, all modeled proteins underwent energy minimization using the Chimera tool, which applies the steepest descent algorithm to reduce potential energy and optimize the stability of the 3D structures. 2.6 RMSD value calculation: The RMSD (Root Mean Square Deviation) values for both proteins were calculated by superimposing the native and mutant structures using the "align" function in PyMOL. RMSD serves as a measure of structural and functional deviation from the native protein; a higher RMSD value indicates a greater level of deviation, suggesting more substantial changes in the protein’s conformation. 2.7 Determining SNP’s impact on the RAD51C and RAD51D protein stability: To evaluate the impact of amino acid substitutions on the stability or potential denaturation of the RAD51D protein, we utilized two independent in silico prediction tools: I-Mutant and MuPro. Both algorithms rely on sequence-based analysis to assess changes in protein stability resulting from mutations. 2.8 Molecular Docking for Protein Interaction Identification: Mutant models of RAD51C and RAD51D proteins were docked with their known interacting partners—XRCC2, XRCC3, RAD51B, and RAD51C—to assess potential changes in binding affinity and interaction patterns. Protein–protein docking was carried out using the ClusPro server, with all parameters set to default values ( https://cluspro.org/help.php ). ClusPro was chosen for its high accuracy, reliability, and intuitive user interface, making it a widely adopted tool in structural bioinformatics. ClusPro performs docking through a systematic pipeline involving rigid body docking, energy-based scoring, and clustering of low-energy conformations to predict the most likely binding configurations (Kozakov et al., 2017 ). The server prioritizes the most frequently occurring conformations, which are presumed to represent native-like binding modes. Additionally, ClusPro provides the option to define specific restraints or bias the docking toward particular residues, enabling more precise modeling of biologically relevant interactions (Kozakov et al., 2013 ). For each docking run, ClusPro generates ten distinct docked models, each accompanied by a score reflecting the estimated binding energy of the complex. 2.7 Molecular Dynamics Simulations: The RAD51C and RAD51D protein complexes, along with their respective mutant forms, underwent comprehensive molecular dynamics (MD) simulations using GROMACS 2024 for a duration of 100 nanoseconds. Following the protocol outlined by Singh et al. ( 2023 ), the proteins were prepared using the all-atom OPLS force field, which included system minimization, solvation, and charge neutralization with Na⁺ and Cl⁻ ions. The simulation process began with energy minimization using the steepest descent algorithm, followed by equilibration in two phases: a canonical ensemble (NVT) and an isothermal–isobaric ensemble (NPT), each lasting 5 ns. The production run of 100 ns was then carried out, and the resulting trajectories were analyzed for key structural parameters including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA) to evaluate the stability and conformational dynamics of the protein systems. 3. Results Identifying deleterious SNPs is crucial for uncovering the genetic basis of Hereditary Breast and Ovarian Cancer (HBOC), as these variations often significantly increase an individual's susceptibility to these cancers. Through the use of advanced computational tools and genomic databases, researchers can explore the molecular pathways involved in HBOC, offering important insights into potential therapeutic targets and preventive strategies. Figure 1 presents a detailed overview of the workflow and database servers employed to detect harmful Single Nucleotide Polymorphisms (SNPs) in the human DNA repair genes RAD51C and RAD51D. These databases and tools are integral to the analytical framework, playing a key role in the accurate identification and functional characterization of pathogenic variants. Moreover, the depicted workflow ensures efficient data integration, systematic analysis, and meaningful interpretation, streamlining the discovery of SNPs with clinical and biological relevance. All genes analyzed in this study were sourced from the dbSNP database. For the RAD51C gene, a total of 19,195 SNPs were identified, comprising 10,027 intronic variants, 880 missense variants, and 359 coding synonymous variants. This investigation focused specifically on non-synonymous SNPs (nsSNPs) in RAD51C, as these variants are more likely to alter the structure or function of the resulting protein. Similarly, for the RAD51D gene, 19,195 SNPs were also retrieved, including 12,048 intronic variants, 860 missense variants, and 389 coding synonymous variants. The study was limited to the analysis of nsSNPs in RAD51D as well, due to their potential to disrupt protein function or structure, thereby impairing homologous recombination repair and increasing the risk of cancer development. 3.1 Finding harmful and detrimental nsSNPs using a sequence-based homology methodology: The SIFT, Polyp hen 2 and PANTHER algorithms forecast harmful nsSNP through a sequence-based homology methodology. At first, every single SNP that was obtained from the dbSNP database was examined in SIFT. Of all the SNPs that were examined in SIFT, only those that originated from the coding (CDS) region were selected for additional examination. The SIFT score is the normalized probability that the amino acid change is tolerated. SIFT predicts substitutions with scores less than 0.05 as deleterious and values up to 1 as tolerated amino acid substitution. SIFT has filtered out 19,195 SNPs for RAD51C, of which just 209 originate within the gene's CDS region and predicted 69 as deleterious and 124 as tolerated. On the basis of SIFT scores ranging between 0.001-1 SIFT has scored a total 25 SNPs of lowest score i.e. zero which will be further deleterious for the resultant protein function. The SIFT score represents the normalized probability of an amino acid substitution being tolerated, with scores below 0.05 classified as deleterious and values up to 1 considered tolerated. (Table 1) Similarly, for RAD51D gene SIFT filtered out 12,753 SNPs, identifying 559 in the CDS region. Among these, 150 were classified as deleterious and 389 as tolerated, with 38 SNPs scoring 0, indicating potential severe functional consequences. PANTHER predicted 59 harmful and 21 benign entries out of 210 RAD51C entries. For RAD51C, 22 entries were unanimously selected as deleterious. Out of these nsSNPs after removing multiple rsIDs entries for the same nsSNP the following results were obtained. Also for RAD51D PANTHER have predicted 164 harmful SNPs out of 210 RAD51D entries, with 8 unanimously identified as deleterious. After eliminating redundant rsID entries for the same nsSNPs, the final results were compiled. 3.2 Sequence- and structure-based homology-based Polyphen server predicted the following functionally harmful nsSNPs: PolyPhen-2 (Polymorphism Phenotyping v2) is a sophisticated computational tool developed by the Bork Group to evaluate the potential impact of genetic variations—particularly amino acid substitutions—on the structure and function of human proteins. By combining sequence-based and structure-based analyses, PolyPhen-2 assesses the pathogenic potential of variants using information such as phylogenetic conservation, structural features, and protein sequence data. In the case of RAD51C, predictions made using both the HumDiv and HumVar datasets classified 31 SNPs as either possibly or probably damaging. Notably, all 31 amino acid substitutions were scored as probably damaging, indicating a high likelihood that these mutations negatively affect protein function. For RAD51D, PolyPhen-2 identified 19 SNPs as possibly damaging, while 10 substitutions were categorized as probably damaging, reflecting a strong potential for these variants to impair the protein’s biological activity. All the unanimous SNPs that were predicted deleterious by all the software have been listed in table 2. 3.3 The disease prediction of nsSNP’s by the PhD-SNP and SNP & GO web tools: PhD-SNP is a computational tool designed to predict the phenotypic effects of non-synonymous substitutions, offering valuable insights into how genetic variations may influence protein function. In addition to this, it also assesses whether specific amino acid changes are likely to be associated with disease development. To evaluate the disease relevance of single amino acid substitutions, researchers utilize both PhD-SNP and SNP&GO. For the RAD51C gene, PhD-SNP initially identified 21 variants as potentially disease-associated. However, after excluding entries with invalid protein IDs, only 14 entries, representing 11 unique rsIDs, were retained, as shown in Table 3. In the case of RAD51D, PhD-SNP predicted 158 disease-linked variants, while SNP&GO identified 69. After removing duplicate entries, 8 distinct rsIDs remained, which are also detailed in Table 3. 3.4 Modelling of the complete RAD51C and RAD51D proteins using MODELLER (Comparative Homology Modelling): These nineteen nsSNPs were taken into consideration for further study. We created the RAD51 mutant structures using MODELLER v10.2 and a homology modelling approach to predict their effects on stability and functionality because the full structures of the RAD51C and RAD51D proteins were available in the PDB database. MODELLER was told to use the given templates to create five different protein architectures. Out of the five models that MODELLER generates, the best model is selected using a number of parameters. The DOPE score is one of the most commonly utilized parameters. We chose the structure with the lowest DOPE score because the better the simulated structure is thought to be, the lower the DOPE value. The models "RAD51C.pdb" and "RAD51D.pdb" (Fig. 2a and b) have been chosen as the best models for RAD51C and RAD51D proteins based on the lowest DOPE score. The Ramachandran Plot was used to further analyse the chosen models in order to verify the folding characteristics and protein structure (Supplementary Table 1). 3.5 RMSD value calculation of the modelled mutant protein : The Root Mean Square Deviation (RMSD) values presented for various RAD51C single nucleotide polymorphisms (SNPs) represent the degree of structural deviation in the protein caused by each specific amino acid (A.A) substitution. RMSD is a quantitative measure used to compare the altered protein structure to the native form, with higher values suggesting greater structural disturbance. In this dataset, RMSD values range from 0.079 to 0.134, indicating variable but relatively modest changes in protein conformation across different SNPs. Notably, the SNP rs137947462 (R212C) exhibits the highest RMSD of 0.134, suggesting a considerable conformational impact, potentially affecting RAD51C's DNA repair function due to structural instability. Other mutations such as rs149331537 (L262V) and rs267606998 (G125V) also show elevated RMSD values (0.128 and 0.130, respectively), indicating these variants might interfere with the protein’s ability to participate in homologous recombination, a critical pathway for genome stability. Conversely, SNPs like rs35151472 (G162E) and rs374196453 (R260W) have lower RMSD values (0.079 and 0.097, respectively), suggesting minor structural perturbations and possibly lesser functional consequences. Importantly, some residues like R212 and G125 appear in multiple mutations (e.g., R212C and R212H; G125S and G125V), highlighting their structural sensitivity. Even though some RMSD values seem modest in absolute terms, small structural shifts in critical domains may still disrupt RAD51C’s interaction with partner proteins or DNA substrates, thereby compromising DNA repair efficiency. Therefore, while the RMSD values provide an initial structural insight, functional assays and further in silico analysis would be essential to correlate these structural deviations with pathogenicity and cancer susceptibility, particularly in the context of breast and ovarian cancers linked to RAD51C dysfunction. Similarly in case of RAD51D proteins the RMSD (root mean square deviations) values provided for the SNPs in RDA51D gene indicate the extent of structural deviation caused by amino acid substitutions. Lower RMSD values suggest minimal structural deviations, higher values indicate significant conformational changes, which could potentially impact protein function. From the total examined SNPs, most SNPS exhibit relatively low RMSD values, ranging from 0.115 (S207L) to 0.145 (D90N), suggesting that these variants may not cause drastic alterations in the protein structure. However, the SNPs S88P (RMSD = 0.227) and A210E (RMSD = 1.159) show considerably high deviations, indicating potential structural disruptions. The proline substitution in S88P could induce rigidity, affecting protein flexibility, while the A210E mutation involves shift from non-polar alanine to negatively charged glutamate, potentially altering interactions and destabilization of protein structure. Given the role of RAD51D in the homologous recombination and DNA repair, these structural changes might influence its function in maintaining genomic stability. Particularly, the A210E variant with the highest RMSD warrants further investigation for its possible association with compromised DNA repair efficiency, which could contribute to cancer predisposition. Experimental validation and functional assays are necessary to confirm thses predictions. (Table 4) 3.6 Analysing the stability changes of mutants using the I-Mutant and MuPro web tools: The results from I-mutant and MUpro tools provide insights into the impact of RAD51C and RAD51D SNP variants on protein stability. Both tools predict whether a given mutation increases or decreases the stability of the protein, which is crucial for understanding its functional consequences in homologous recombination and DNA repair. Decreased stability suggest potential structural disruptions that may impair protein function, while increased stability could lead to altered protein dynamics and misfolding. Most mutations, including R249C, G162E, R212C, L297P, L262V, R212H, L219S, R258H, and G112A, are predicted by both tools to decrease the stability of RAD51C. This reduction in stability may impair RAD51C's ability to interact with other HR proteins such as RAD51, BRCA2, and XRCC3, potentially leading to compromised DNA repair and increased genomic instability—a hallmark of cancer development. Notably, mutations like L297P and L262V affect leucine residues, which are often involved in hydrophobic core formation and protein folding; such substitutions could lead to misfolding or degradation. Interestingly, the SNP rs267606998 (G125V) is predicted by I-Mutant to increase stability but by MUpro to decrease it, indicating conflicting outcomes. Although increased stability might seem beneficial, it can also hinder protein function if it leads to aberrant folding or impaired interaction with DNA or other repair factors. The consistent prediction of reduced stability across the majority of these SNPs suggests that these variants may compromise RAD51C function. In case of RAD51D, most SNPs, both I-mutant and MUpro predict a decrease in protein stability. Variants such as G265R, C9S, R145H, R275Q and D90N show decreased stability across both tools, indicating these mutations may destabilize the RAD51D structure and weaken its interaction within the RAD51 paralog complex. This instability could compromise RAD51D role in homologous recombination, leading to defective DNA repair and increased susceptibility to genomic instability and cancer. The R275Q mutation shows error suggesting uncertainty in its impact, but since I-mutant predicts a decrease, it is likely destabilizing. Interestingly, S207L and A210E show conflicting predictions. While I-Mutant predicts a decrease in stability for S207L, MuPro suggests an increase. This discrepancy indicates that the mutation may induce a conformational change rather than outright destabilization. A210E, on the other hand, is predicted to increase stability by I-Mutant but decrease stability by MuPro. The alanine-to-glutamate substitution introduces a charged residue in place of a small, nonpolar one, which could lead to altered binding properties rather than outright destabilization. The S207P mutation is notable as it decreases stability in MuPro but increases in I-Mutant, possibly due to the rigid structure of proline, which can disrupt local folding. This could affect RAD51D’s flexibility and interaction with binding partners like XRCC2, RAD51B, and RAD51C. Overall, the majority of these SNPs are predicted to decrease RAD51D stability, suggesting potential functional impairment in DNA repair pathways. The variations in S207L and A210E predictions warrant further experimental validation to determine their true biological consequences. 3.7 RAD51C and RAD51D protein domain mutation mapping: The domain mapping of the RAD51C protein reveals the distribution of several missense mutations across three major functional domains. The N-terminal domain (residues 1–90) harbors the L27V mutation. The central RecA-like ATP-binding domain (residues 96–186) contains mutations such as G112A, G125V, and G162E, suggesting potential impacts on ATP binding and homologous recombination activity. The C-terminal DNA recombination/repair domain (residues 207–348) shows a cluster of mutations including R212C, R212H, L219S, R249C, R258H, L262V, and L297P, indicating a high mutational burden in this critical region for DNA repair functionality. Overall, the mapping highlights key mutational hotspots within functionally significant regions of RAD51C, which may be relevant to its role in genome maintenance and cancer susceptibility. (Fig. 3) Similarly, the domain mapping of RAD51D shows multiple missense mutations distributed across its functional domains. The RAD51-like N-terminal domain (residues 1–110) contains mutations such as C9S, E74G, S88P, and D90N, suggesting alterations near the start of the protein. The ATPase domain (residues 112–200) has a single mutation, R145H, indicating potential effects on ATP hydrolysis. The DNA repair protein C-terminal domain (residues 201–298) carries several mutations including S207L, S207P, A210E, G265R, and R275Q, clustering within a region critical for DNA repair activity. (Fig. 4) 3.8 Protein -protein docking analysis: The docking results summarize the binding affinities between various RAD51C protein mutants and its key interacting partners—XRCC2, XRCC3, RAD51B, and RAD51D—which are essential components of the homologous recombination (HR) DNA repair complex. The binding scores (in kcal/mol) indicate interaction strength, where more negative values represent stronger binding affinities. The wild-type RAD51C (RAD51C-W) exhibits moderate affinity across all partners, serving as the baseline for comparison. Several mutations—including R212C, R249C, and L297P—demonstrate significantly more negative docking scores, especially with XRCC3 and RAD51B (e.g., R249C: -1376 with XRCC3 and − 1288.5 with RAD51B), suggesting stronger or aberrant binding. This could reflect a potential gain-of-binding, which might trap RAD51C in non-functional or misassembled complexes, disrupting dynamic interactions essential for DNA repair fidelity. (Fig. 5a – 5e) In contrast, mutations such as G125V and R212H show weaker or comparable interactions to the wild-type, implying a potential loss or alteration of binding, particularly with XRCC2 and XRCC3. For example, G125V displays a much less negative score with XRCC2 (-995.1) compared to the wild-type (-1023.6), which may reduce RAD51C’s ability to integrate into the BCDX2 complex, compromising its function in DNA damage response. Mutations like L219S, L262V, and R258H, which occur in the ATP-binding domain, generally show consistent interaction energies across partners, but modest deviations (e.g., R258H: -1145.6 with RAD51B) still suggest structural changes that could influence complex formation dynamics. Biologically, such altered binding affinities—whether increased or decreased—may impair RAD51C’s precise coordination with HR partners, leading to defective DNA repair, accumulation of DNA damage, and increased cancer susceptibility. (Table 5), (Supplementary Figs. 1–11) The docking results for RAD51D SNP variants with its interacting partners—XRCC2, RAD51B, and RAD51C—reveal important insights into how amino acid substitutions may alter protein-protein interactions within the homologous recombination (HR) repair pathway. RAD51D is a crucial component of the RAD51 paralog complex, which facilitates DNA repair and maintains genomic stability. Any disruption in these interactions can potentially impair DNA repair efficiency, increasing the risk of genomic instability and cancer susceptibility. Comparing the wild-type (RAD51D-WT) with mutant variants shows that most SNPs cause varying degrees of binding affinity changes, either weakening or strengthening interactions with XRCC2, RAD51B, and RAD51C. (Fig. 6a – 6e) Among the analysed SNPs, A210E exhibits one of the most notable shifts in binding affinity. This mutation, which replaces a small nonpolar alanine with a negatively charged glutamate, introduces potential charge repulsions and steric hindrance, leading to a weakened interaction with RAD51B (-1124 vs. -1174.1 in WT) and XRCC2 (-1059.5 vs. -1024.1 in WT). Interestingly, A210E enhances binding with RAD51C (-1294.8 vs. -1195.4 in WT), suggesting a structural rearrangement that may disrupt the normal function of the RAD51 paralog complex. Similarly, the S207L mutation, which replaces a polar serine with a hydrophobic leucine, leads to a significant change in binding affinity, particularly strengthening its interaction with RAD51C (-1274.4 vs. -1195.4 in WT). These changes could reflect an altered binding conformation, potentially leading to impaired recruitment of RAD51D in DNA repair processes. (Fig. 6f – 6h) Other variants, such as D90N, show moderate changes in docking scores. Meanwhile, D90N exhibits weaker binding to XRCC2 (-921.8 vs. -1024.1 in WT), suggesting a possible disruption in the RAD51D-XRCC2 interaction, which is critical for efficient DNA repair. Overall, mutations like A210E and S207L that significantly alter protein binding dynamics could compromise the stability of the RAD51 paralog complex, potentially leading to defective homologous recombination and increased susceptibility to genomic instability and cancer. (Table 6), (Supplementary Figs. 12–16). 3.9 Molecular dynamics simulation The molecular dynamics (MD) simulation results for the RAD51C protein and its interaction complexes with XRCC2 and RAD51B provide a comprehensive view of how specific polymorphisms can influence the structural dynamics, stability, and potential functional consequences of the protein. These simulations were analyzed using key structural parameters, including RMSD, RMSF, radius of gyration (Rg), and solvent-accessible surface area (SASA), as presented in Figures . Starting with the Root Mean Square Deviation (RMSD) analysis, Fig. 7a highlights the differences in structural stability between the wild-type RAD51C-XRCC2 complex and its R212H polymorphic variant. The average RMSD for the wild-type complex is 0.7279 nm, indicating moderate conformational stability throughout the simulation. In contrast, the R212H-XRCC2 complex shows a slightly lower RMSD value of 0.654 nm, suggesting improved structural stability in the mutant form. Similarly, Fig. 8a presents the RMSD profiles for the wild-type RAD51C-RAD51B complex and its polymorphic variants, L219S and L262V. The wild-type complex has an average RMSD of 0.858 nm, again indicating moderate stability. The L219S mutant exhibits a higher RMSD of 1.014 nm, reflecting greater structural deviations and hence reduced stability. Conversely, the L262V mutant demonstrates a lower RMSD of 0.7871 nm, suggesting that this mutation might confer improved stability over the wild type. These findings emphasize how specific mutations can either destabilize or stabilize the RAD51C complexes, with implications for their functional efficacy in homologous recombination. The Root Mean Square Fluctuation (RMSF) analysis, shown in Figs. 7b and 8b, further details the residue-wise flexibility of the protein complexes. In Fig. 7b, the wild-type RAD51C-XRCC2 complex shows notable fluctuations at residues 2–18, 244–268, 404–474, and 522–533, indicating flexible loop or terminal regions. In contrast, the R212H variant displays distinct fluctuation peaks at residues 200–226, 281, 570, and 626. These shifts in flexibility could reflect conformational alterations that may influence protein-protein interaction dynamics. In Fig. 8b, the wild-type RAD51C-RAD51B complex exhibits a significant fluctuation peak at residue 364. The L219S mutant, however, shows widespread fluctuations across multiple regions, including residues 6–49, 266, 276, 336, 411–500, 563, 592, and 667–725, indicating a markedly unstable behavior. The L262V mutant also shows prominent peaks at residues 274, 565, and 628. These increased fluctuations, especially in L219S, suggest that this variant may be less structurally stable and potentially impaired in maintaining essential interactions during DNA repair processes. The radius of gyration (Rg) results, shown in Figs. 7c and 8c, provide insights into the compactness of the protein complexes. In Fig. 7c, the wild-type RAD51C-XRCC2 complex exhibits an average Rg of 3.263 nm, while the R212H variant shows a slightly lower average Rg of 2.887 nm. The lower Rg of the R212H complex suggests a more compact and possibly more stable conformation. In Fig. 8c, the wild-type RAD51C-RAD51B complex has an average Rg of 3.13 nm, whereas the L219S and L262V mutants show higher Rg values of 3.302 nm and 3.211 nm, respectively. Notably, the L219S variant displays a significant increase in Rg after 33 ns, which continues until the end of the 100 ns simulation, indicating a deviation from its initial compactness and suggesting unfolding or conformational drift. This behavior is indicative of compromised structural stability in the L219S mutant compared to both the wild type and the L262V variant. Solvent Accessible Surface Area (SASA) values, presented in Figs. 7d and 8d, offer further evidence of mutation-induced structural alterations. In Fig. 7d, the wild-type RAD51C-XRCC2 complex has an average SASA of 345.7478 nm², while the R212H variant shows a slightly reduced SASA of 345.2597 nm². This marginal decrease suggests minimal change in solvent exposure and implies that the mutation does not significantly affect the complex’s surface characteristics. In Fig. 8d, the wild-type RAD51C-RAD51B complex has an average SASA of 397.433 nm². The L219S and L262V mutants exhibit increased average SASA values of 399.4568 nm² and 403.8887 nm², respectively. These increases imply that the mutant complexes have more exposed surface areas, which may alter their interaction profiles with other biomolecules or solvent, potentially reducing complex stability. Particularly, the higher SASA values associated with L219S and L262V suggest that these mutations might disrupt the normal packing of the protein complex, leading to functional impairment. In conclusion, the MD simulations reveal that polymorphisms in RAD51C, such as R212H, L219S, and L262V, distinctly alter the protein’s structural dynamics and stability in complex with XRCC2 and RAD51B. While R212H appears to confer greater stability and compactness, the L219S variant displays pronounced instability across multiple parameters, including higher RMSD, extensive residue fluctuations, increasing Rg over time, and elevated SASA. These characteristics suggest a significant structural compromise in L219S, potentially impairing RAD51C’s role in DNA repair. Conversely, L262V shows moderate stability with minor deviations, indicating a less detrimental impact compared to L219S. Collectively, these findings underscore the importance of evaluating structural dynamics in assessing the functional consequences of RAD51C mutations, with direct relevance to understanding cancer susceptibility and guiding targeted therapeutic interventions. The molecular dynamics (MD) simulation results of RAD51D and its variants, interacting with its known partners XRCC2, RAD51B, and RAD51C, reveal significant insights into specific mutations' structural and functional impact. The simulation focused on key metrics such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration, solvent accessible surface area (SASA), and the number of hydrogen bonds formed during the simulation. These parameters were systematically analyzed across multiple complexes and mutant variants. In the RAD51D–XRCC2 complex, the wild-type protein demonstrated stable dynamics with an average RMSD of approximately 1.16 Å, (Fig. 9a) while the D90N mutation exhibited a lower RMSD of around 0.68 Å, suggesting a structurally more rigid complex. This decreased deviation was supported by a corresponding reduction in RMSF (0.23 Å in D90N vs. 0.47 Å in wild-type), indicating less flexibility in the D90N mutant. (Fig. 9b) This rigidity could limit the protein’s conformational adaptability during DNA repair processes. Further, the D90N variant showed a slightly decreased radius of gyration and SASA compared to the wild-type, pointing to a more compact and less solvent-exposed structure. (Fig. 9c and d) Interestingly, D90N also exhibited a higher average number of hydrogen bonds (407) than the wild-type (400), suggesting enhanced internal stabilization that might hinder necessary conformational transitions or partner interactions during homologous recombination. For the RAD51D–RAD51B complex, the wild-type structure maintained low RMSD and RMSF values, denoting structural integrity. However, the S207L mutant displayed a substantial increase in RMSD (1.03 Å) and RMSF (0.39 Å), reflecting increased structural deviation and flexibility. (Fig. 10a and b) These changes suggest that the S207L mutation may weaken the protein-protein interaction interface with RAD51B, possibly affecting RAD51D's function in the RAD51 paralog complex. This is further evidenced by an increased radius of gyration and SASA, indicating a less compact and more exposed structure. The number of hydrogen bonds in S207L was also higher than in the wild-type, possibly as a compensatory mechanism to stabilize the perturbed structure. In contrast, the G265R mutation appeared to cause a milder impact, with moderate deviations in RMSD and slightly lower RMSF, hinting at a potential but less severe effect on structural integrity and function. (Fig. 10c and 10d) In the RAD51D–RAD51C complex, both the D90N and S207P variants were evaluated alongside the wild-type. The S207P mutant emerged as the most structurally disruptive, with elevated RMSD (0.80 Å) and RMSF (0.54 Å), indicating both global and local structural fluctuations. (Fig. 11a and 11b)It also showed a markedly increased radius of gyration and SASA, suggesting a looser, more flexible structure that may impair stable complex formation with RAD51C. (Fig. 11c and 11d) Additionally, the S207P mutant exhibited a lower average hydrogen bond count compared to the wild-type and D90N, implying reduced internal interactions and stability. D90N, on the other hand, maintained a structural profile similar to that seen in the XRCC2 complex, with slightly lower RMSD and RMSF than the wild-type, confirming its stabilizing but potentially rigidifying effect across different protein interfaces. Biologically, these findings highlight the differential impact of specific RAD51D mutations on protein structure and stability. The D90N mutation consistently appears to stabilize the protein and reduce flexibility, potentially at the cost of functional adaptability required during homologous recombination. Conversely, the S207L and S207P mutations introduce significant flexibility and reduce compactness, which may disrupt critical protein-protein interactions, thereby impairing the formation or stability of the RAD51 paralog complex. These disruptions could compromise RAD51D’s role in DNA repair, potentially leading to increased genomic instability and heightened cancer susceptibility. The G265R mutation shows a moderate structural effect, suggesting it may represent a hypomorphic or less penetrant pathogenic variant. Collectively, these results underscore the importance of residue-specific effects on RAD51D function and provide molecular-level explanations for the potential pathogenicity of these mutations in hereditary breast and ovarian cancers. 4. Discussion The current study presents an integrated computational and structural analysis of RAD51C and RAD51D genes, underscoring their critical roles in homologous recombination repair (HRR) and their implications in cancer susceptibility, particularly breast and ovarian cancers. Numerous studies have established that single nucleotide polymorphisms (SNPs), particularly missense mutations in DNA repair genes, contribute significantly to cancer progression. RAD51C mutations have been implicated in a variety of malignancies including breast, ovarian, and head and neck cancers (Smolarz et al., 2013 ; Grenser et al., 2014 ; Vuorela et al., 2011 ). Given their direct involvement in disease pathology and treatment responsiveness, this study focused on identifying deleterious non-synonymous SNPs (nsSNPs) in RAD51C and RAD51D through comprehensive in silico analysis. Utilizing tools such as SIFT, PROVEAN, PANTHER, PolyPhen for functional prediction, PhD-SNP and SNP&GO for disease association, and MUpro and I-Mutant for protein stability evaluation, a total of 19,195 SNPs retrieved from dbSNP were screened for the RAD51C gene. The multi-tool approach enabled robust cross-validation, leading to the identification of 11 pathogenic nsSNPs in RAD51C, predominantly localized in two functionally crucial domains: the ATP-binding domain (G112A, G125V, G125S, G162E) and the DNA repair/recombination C-terminal domain (R212C, R212H, L219S, R249C, R258H, L262V, L297P). Glycine mutations were particularly frequent and significant, given glycine’s inherent flexibility and its role in maintaining structural integrity due to the absence of a side chain. Similarly, arginine mutations occurred at five positions, indicating potential hotspots for functional disruption. Since protein flexibility is vital to molecular function, these substitutions—especially involving glycine and arginine—may cause deleterious conformational alterations. Molecular modeling and docking analyses revealed that certain mutations, especially R212H in the RAD51C-XRCC2 complex and L219S and L262V in the RAD51C-RAD51B complex, led to a decline in binding affinity. The docking results were further validated through molecular dynamics (MD) simulations, which showed that these mutations compromised the overall stability of the protein complexes. In particular, the L219S variant exhibited higher root mean square deviation (RMSD), increased root mean square fluctuation (RMSF) across multiple residues, a sustained increase in radius of gyration (Rg), and elevated solvent-accessible surface area (SASA), collectively indicating structural destabilization. By contrast, the R212H mutation, although altering specific residue flexibility, showed slightly improved compactness and reduced RMSD and SASA values, suggesting a nuanced effect on stability. Structurally, RAD51C functions as a core component of two key HRR complexes: the BCDX2 complex (comprising RAD51B, RAD51C, RAD51D, and XRCC2) and the CX3 complex (comprising RAD51C and XRCC3). These complexes play pivotal roles in stabilizing RAD51 nucleoprotein filaments and facilitating strand invasion—key steps in homologous DNA repair (Lio et. Al., 2004 ; Miller et al., 2004 ). Disruption of these interactions, as observed in the L219S and L262V mutants, can impair early recombination processes, potentially leading to inefficient double-strand break repair and increased genomic instability. This mechanistic impairment aligns with previous findings showing RAD51C amplification in breast tumors (Tarsounas & West, 2005 ) and its frequent mutation in familial breast and ovarian cancer cases (Meindl et al., 2010). In parallel, RAD51D, another essential paralog in the RAD51 family, contributes significantly to HRR by binding to single-stranded DNA and aiding in homology recognition Like RAD51C, pathogenic SNPs in RAD51D are known to destabilize its structure and disrupt DNA binding or protein interaction, thereby increasing cancer risk. The combined importance of RAD51C and RAD51D in HRR makes them critical genomic biomarkers. Structural and functional analyses have further confirmed that mutations in these genes, including G125V and L138F in RAD51C, cause significant conformational shifts, categorizing them as deleterious and pathogenic. With advances in computational biology and genome-wide association studies (GWAS), predicting the pathogenicity of SNPs has become increasingly precise. Tools such as SIFT, PolyPhen, and PROVEAN now enable high-throughput screening of candidate mutations (de Almeida et al., 2022 ), narrowing the gap between genomic data and clinical relevance. From a clinical standpoint, identifying high-risk nsSNPs in RAD51C and RAD51D opens up new avenues for personalized medicine. For example, tumors harboring HRR-deficient mutations are more responsive to poly (ADP-ribose) polymerase (PARP) inhibitors, offering targeted therapeutic strategies (Murai et al., 2012 ). Moreover, conformational alterations induced by certain SNPs may explain differential sensitivity or resistance to these therapies, informing precision oncology approaches (Luo et al., 2020 ). This study also emphasizes the significance of population-specific genomic profiling. Ethnic variations in RAD51C and RAD51D mutation frequencies can influence cancer risk and treatment outcomes, thereby necessitating regionally adapted interventions (Green et al., 2020 ). By integrating bioinformatics, structural modelling, docking, and dynamic simulations, this research presents a comprehensive framework for understanding the impact of deleterious SNPs in RAD51C and RAD51D. It highlights the need for experimental validation to further elucidate functional consequences and supports the future use of these insights in early detection, risk prediction, and the development of targeted therapies. In conclusion, our study affirms the central role of RAD51C and RAD51D in DNA repair and cancer susceptibility. By identifying and characterizing the most damaging nsSNPs through a robust computational pipeline, we contribute significantly to the understanding of how these genes influence tumorigenesis. These findings not only align with previous literature (Rodriguez-Lopez et al., 2004 ; Porto et al., 2015 ; Rajasekaran et al., 2008 ; Chun et al., 2013 ; Greenhough et al., 2023 ) but also lay the groundwork for future translational research aimed at harnessing RAD51 family mutations for diagnostic and therapeutic purposes. As genomic medicine continues to evolve, integrating such structural and functional insights will be key to advancing cancer prevention and precision treatment strategies (Hortobagyi, 2020 ). 5. Conclusion This study underscores the pivotal roles of RAD51C and RAD51D genes in maintaining genomic integrity through homologous recombination repair and highlights their contribution to breast and ovarian cancer susceptibility beyond BRCA1/2 mutations. Using a comprehensive computational pipeline, we screened over 19,000 SNPs and identified several deleterious non-synonymous variants with potential pathogenicity, particularly within critical functional domains such as the ATP-binding and DNA recombination/repair regions. Structural modeling and molecular dynamics simulations revealed that these variants can induce significant alterations in protein conformation, stability, and protein-protein interactions. Mutations such as L219S in RAD51C and S207L in RAD51D were found to be especially disruptive, compromising interactions within the RAD51 paralog complexes. These findings not only elucidate the molecular mechanisms by which RAD51C/D variants contribute to cancer development but also identify candidate biomarkers for early detection and therapeutic targeting. The integration of sequence-based screening with structural and dynamic analyses offers a powerful approach for prioritizing functionally relevant SNPs in cancer-associated genes. Future experimental studies are essential to validate these in silico predictions and further explore their clinical utility in cancer risk assessment and precision oncology. Declarations Declaration of Interest: Authors declare no conflict of interest. Author Contribution All authors have been contributed to the manuscript. References Michael PC, Parmigiani G, Beattie MS, Garber JE. 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RAD51C and RAD51D: Novel players in hereditary breast and ovarian cancer. Oncol Rep. 2015;33(2):965–71. https://doi.org/10.3892/or.2014.3630 . Rajasekaran B, Dutta S, et al. Genetic and biochemical analyses of RAD51C function. Cell Cycle. 2008;7(3):351–62. https://doi.org/10.4161/cc.7.3.5191 . Chun J, Buechelmaier ES, Powell SN. Rad51 paralog complexes BCDX2 and CX3 act at different stages in the BRCA1–BRCA2-dependent homologous recombination pathway. Mol Cell Biol. 2013;33(2):387–95. https://doi.org/10.1128/MCB.00847-12 . Greenhough A, Zeng X, et al. Targeting homologous recombination repair defects in cancer therapy. Trends Cancer. 2023;9(1):3–17. https://doi.org/10.1016/j.trecan.2022.09.008 . Hortobagyi GN. Developments in precision oncology: The future is now. J Clin Oncol. 2020;38(5):443–54. https://doi.org/10.1200/JCO.19.03124 . Tables Table I: Deleterious SNPs in RAD51C and RDA51D genes predicted by sequence and structure based tools. RAD51C Sr. No. rsID Amino Acid change Sr. No. rsID Amino Acid change rs28363307 I76T 36. rs201523760 T5M rs28363311 R249C 37. rs201523760 T5M rs28363311 R128C 38. rs201523760 T5M rs28363311 R249C 39. rs201529791 L219S rs28363311 R14C 40. rs201529791 L98S rs28363317 T52A 41. rs201529791 L219S rs28363317 T287A 42. rs201529791 L151S rs28910276 R12W 43. rs267606997 R258H rs28910276 R12W 44. rs267606997 R137H rs28910276 R12W 45 rs267606997 R258H rs35151472 G162E 46. rs267606997 R23H rs35151472 G94E 47. rs267606998 G125V rs35151472 G162E 48 rs267606998 G4V rs35151472 G41E 49 rs267606998 G125V rs137947462 R212C 50 rs267606998 G57V rs137947462 R91C 51 rs267606998 G125V rs137947462 R144C 52 rs267606999 L138F rs137947462 R212C 53 rs267606999 L70F rs142058115 G125S 54 rs267606999 L138F rs142058115 G4S 55 rs267606999 L17F rs142058115 G125S 56 rs370212314 G112A rs142058115 G57S 57 rs370212314 G112A rs142058115 G125S 58 rs370212314 G112A rs143026267 L297P 59 rs370212314 G44A rs143026267 L62P 60 rs374196453 R260W rs147241704 G29S 61 rs374196453 R139W rs149331537 L27V 62 rs374196453 R260W rs149331537 L141V 63 rs374196453 R25W rs149331537 L262V 64 rs375451955 E67G rs149331537 L262V 65 rs376494695 D141G rs184033132 V6M 66 rs376494695 D141G rs200857129 R212H 67 rs376494695 D73G rs200857129 R91H 68 rs376494695 D20G rs200857129 R144H 69 rs184126555 I174T rs200857129 R212H RAD51D Sr. No. rsID Amino Acid change Sr. No. rsID Amino Acid change 1 rs28363282 A106T 76 rs368838910 I105T 2 rs28363282 A180T 77 rs368838910 I105T 3 rs28363282 A106T 78 rs368838910 I105T 4 rs28363282 A48T 79 rs368838910 I125T 5 rs28363284 E74G 80 rs368914740 R98Q 6 rs28363284 E114G 81 rs368914740 R156Q 7 rs28363284 E114G 82 rs368914740 R230Q 8 rs28363284 E114G 83 rs368914740 R295Q 9 rs28363284 E56G 84 rs368914740 R275Q 10 rs55942401 E38D 85 rs368914740 R275Q 11 rs80116829 A78T 86 rs368914740 R163Q 12 rs80116829 A13T 87 rs369946779 E73K 13 rs137886232 R134G 88 rs369946779 E73K 14 rs137886232 R76G 89 rs370228071 S162L 45 rs137886232 R141G 90 rs370228071 S88L 16 rs137886232 R134G 91 rs370228071 S88L 17 rs137886232 R134G 92 rs370228071 S30L 18 rs137886232 R94G 93 rs370228071 S88L 19 rs138969595 T216I 94 rs370228071 S48L 20 rs138969595 T328I 95 rs370228071 S207L 21 rs138969595 T283I 96 rs370228071 S207L 22 rs138969595 T328I 97 rs370228071 S227L 23 rs138969595 T209I 98 rs371182137 F64I 24 rs138969595 T348I 99 rs371182137 F64I 25 rs139642328 T27K 100 rs371561526 D110N 26 rs139642328 T27K 101 rs371561526 D90N 27 rs139642328 T27K 102 rs371561526 D90N 28 rs139642328 T27K 103 rs371561526 D90N 29 rs139642328 T27K 104 rs371812219 L146F 30 rs139642328 T27K 105 rs371812219 L146F 31 rs140285068 G153R 106 rs371812219 L166F 32 rs140285068 G265R 107 rs371812219 L27F 33 rs140285068 G220R 108 rs372038369 R179C 34 rs140285068 G265R 109 rs372038369 R172C 35 rs140285068 G146R 110 rs372038369 R291C 36 rs140285068 G285R 111 rs372038369 R246C 37 rs140285068 G88R 112 rs372038369 R291C 38 rs140285068 G146R 113 rs372038369 R311C 39 rs140317560 A49V 114 rs372038369 R172C 40 rs140825795 C9S 115 rs372038369 R114C 41 rs140825795 C9S 116 rs372038369 R132C 42 rs140825795 C9S 117 rs372365287 S162P 43 rs140825795 C9S 118 rs372365287 S88P 44 rs140825795 C9S 119 rs372365287 S88P 45 rs141690729 N19H 120 rs372365287 S30P 46 rs141690729 N19H 121 rs372365287 S88P 47 rs141690729 N19H 122 rs372365287 S48P 48 rs142189122 D70N 123 rs372365287 S207P 49 rs142189122 D70N 124 rs372365287 S207P 50 rs142189122 D70N 125 rs372365287 S227P 51 rs142387263 R108C 126 rs374019782 A177S 52 rs145309168 I199N 127 rs374019782 A119S 53 rs145309168 I192N 128 rs374019782 A251S 54 rs145309168 I266N 129 rs374019782 A184S 55 rs147264215 R145H 130 rs374357106 S62L 56 rs147264215 R145H 131 rs374357106 S62L 57 rs147264215 R165H 132 rs374730714 G44D 58 rs147264215 R26H 133 rs376472075 L84H 59 rs147264215 R26H 134 rs376855484 A33E 60 rs147264215 R26H 135 rs376855484 A91E 61 rs151198586 R55Q 136 rs376855484 A51E 62 rs151198586 R55Q 137 rs376855484 A165E 63 rs151198586 R55Q 138 rs376855484 A98E 64 rs151198586 R55Q 139 rs376855484 A91E 65 rs200009601 E25K 140 rs376855484 A230E 66 rs200009601 E72K 141 rs376855484 A210E 67 rs200009601 E65K 142 rs376855484 A210E 68 rs200009601 E7K 143 rs376855484 A91E 69 rs200018296 T84A 144 rs28363282 A106T 70 rs200018296 T84A 145 rs28363282 A180T 71 rs200018296 T84A 146 rs28363282 A106T 72 rs201141245 V152I 147 rs28363282 A48T 73 rs201141245 V132I 148 rs199589923 F22C 74 rs201141245 V132I 149 rs199659185 R43Q 75 rs201141245 V13I 150 rs199659185 R43L Table II: Unanimous results of all tools for RAD51C and RAD51D RAD51C RAD51D Sr. No. rsID Amino Acid change Sr. No. rsID Amino Acid change 1 rs28363311 R249C 1 rs140285068 G265R 2 rs28363311 R249C 2 rs140825795 C9S 3 rs28363317 T287A 3 rs140825795 C9S 4 rs35151472 G162E 4 rs140825795 C9S 5 rs137947462 R212C 5 rs140825795 C9S 6 rs142058115 G125S 6 rs140825795 C9S 7 rs142058115 G125S 7 rs147264215 R145H 8 rs142058115 G125S 8 rs147264215 R145H 9 rs143026267 L297P 9 rs368914740 R275Q 10 rs149331537 L27V 10 rs368914740 R275Q 11 rs149331537 L262V 11 rs370228071 S207L 12 rs149331537 L262V 12 rs370228071 S207L 13 rs200857129 R212H 13 rs371561526 D90N 14 rs201529791 L219S 14 rs371561526 D90N 15 rs267606997 R258H 15 rs371561526 D90N 16 rs267606998 G125V 16 rs372365287 S88P 17 rs267606998 G125V 17 rs372365287 S88P 18 rs267606998 G125V 18 rs372365287 S88P 19 rs370212314 G112A 19 rs372365287 S207P 20 rs370212314 G112A 20 rs372365287 S207P 21 rs370212314 G112A 21 rs376855484 A210E 22 rs374196453 R260W 22 rs376855484 A210E Table III: Entries after removing multiple rsIDs entries and invalid protein ID RAD51C RAD51D S.No. rsID Amino Acid Change S.No. rsID Amino Acid Change 1 rs28363311 R249C 1 rs140285068 G265R 2 rs35151472 G162E 2 rs140825795 C9S 3 rs137947462 R212C 3 rs147264215 R145H 4 rs142058115 G125S 4 rs368914740 R275Q 5 rs143026267 L297P 5 rs370228071 S207L 6 rs149331537 L262V 6 rs371561526 D90N 7 rs200857129 R212H 7 rs372365287 S207P 8 rs201529791 L219S 8 rs376855484 A210E 9 rs267606997 R258H 10 rs267606998 G125V 11 rs370212314 G112A Table IV: Stability prediction and RMSD values of deleterious SNPs in RAD51C and RAD51D. RAD51C S. No rs IDs Amino acid change RMSD I-Mutant MuPro 1 rs28363311 R249C 0.107 Decrease Decrease 2 rs35151472 G162E 0.079 Decrease Decrease 3 rs137947462 R212C 0.134 Decrease Decrease 4 rs142058115 G125S 0.108 Decrease - 5 rs143026267 L297P 0.115 Decrease - 6 rs149331537 L262V 0.128 Decrease Decrease 7 rs200857129 R212H 0.098 Decrease Decrease 8 rs201529791 L219S 0.107 Decrease Decrease 9 rs267606997 R258H 0.107 Decrease Decrease 10 rs267606998 G125V 0.13 Decrease Decrease 11 rs370212314 G112A 0.091 Increase Decrease RAD51D S. No rs IDs Amino acid change RMSD I-Mutant MuPro 1 rs140285068 G265R 0.134 Decrease Decrease 2 rs140825795 C9S 0.123 Decrease - 3 rs147264215 R145H 0.132 Decrease Decrease 4 rs368914740 R275Q 0.124 Decrease Decrease 5 rs370228071 S207L 0.115 Decrease Decrease 6 rs371561526 D90N 0.145 Decrease Decrease 7 rs372365287 S207P 0.123 Decrease - 8 rs376855484 A210E 1.159 Decrease Decrease Table V: Molecular docking results of RAD51C protein with interacting proteins. S. No Amino Acid Change Binding energies Kcal/mol XRCC2 XRCC3 RAD51B RAD51D 1 RAD51C-W -1023.6 -1016 -1281.3 -112.8 2 G112A -1081.5 -1262 -1254 -1095.9 3 G125S -1061.3 -1000.1 -1119.6 -1003.5 4 G125V -995.1 -1242.4 -1284 -1103.4 5 G162E -1106.7 -996 -1127.8 -1046.3 6 L219S -1123.3 -1060.7 -1147.5 -1030.4 7 L262V -1047.3 -1226.5 -1211.6 -1112.6 8 L297P -1033.9 -1079.6 -1200.1 -960.7 9 R212C -1168.2 -1389.4 -1295.8 -1046.1 10 R212H -980.8 -1294.1 -1302.9 -1040.8 11 R249C -1175.3 -1376 -1288 -1030.4 12 R258H -1124.6 -1048.3 -1145.6 -1030.2 Table VI: Molecular docking results of RAD51D protein with interacting proteins. S. No Amino Acid Change Binding energies Kcal/mol XRCC2 RAD51B RAD51C RAD51D_WILD -1024.1 -1174.1 -1195.4 1 G265R -997.5 -1088.1 -1186.5 2 C9S -1020.7 -1233.2 -996 3 R145H -1042.2 -1099.9 -1178.2 4 R275Q -981.8 -1185.9 -1185.7 5 S207L -1089.9 -1146.5 -1274.4 6 D90N -921.8 -1111.2 -1050.5 7 S207P -1047.9 -1137 -1190.7 8 A210E -1059.5 -1124 -1294.8 Additional Declarations No competing interests reported. Supplementary Files Supplementaryfigures.zip Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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06:49:02","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1939365,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigures.zip","url":"https://assets-eu.researchsquare.com/files/rs-7450048/v1/7293a24e504e642849b02b5e.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Structural Perturbations and Destabilizing Mutations in RAD51C and RAD51D Reveal Mechanisms of Cancer Risk","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBreast and ovarian cancers are among the most common and lethal malignancies affecting women globally. While mutations in BRCA1 and BRCA2 genes are well-established contributors to hereditary breast and ovarian cancer (HBOC), they account for only approximately 20% of familial cases, suggesting the involvement of additional genetic factors (Michael P. et al., 2006). Increasing evidence points to other DNA repair genes\u0026mdash;such as RAD51C, RAD51D, CHEK2, and NBN\u0026mdash;as significant contributors to cancer susceptibility, particularly due to their roles in DNA double-strand break (DSB) repair, cell cycle regulation, and apoptosis (Nielsen et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Damiola et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRAD51C and RAD51D, both located on chromosome 17 (q22 and q12, respectively), encode proteins essential for error-free repair of DSBs via the homologous recombination (HR) pathway. RAD51C forms part of two key complexes: the BCDX2 complex (RAD51B-RAD51C-RAD51D-XRCC2) and the CX3 complex (RAD51C-XRCC3), both of which are required for efficient strand invasion and stabilization of RAD51 nucleoprotein filaments during HR (Chun et al., 2016; Godthelp et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). RAD51D, on the other hand, facilitates homology recognition and repair by binding to single-stranded DNA post-damage (Kim et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Amplification of RAD51C at chromosome 17q23 has been observed in breast tumors, suggesting its oncogenic potential in certain contexts despite its tumor suppressor function. Germline pathogenic variants (GPVs) in RAD51C and RAD51D have been associated with significantly elevated risks of breast and ovarian cancers ( Turnbull et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Loveday et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent advances in genome-wide association studies (GWAS) have highlighted the importance of single nucleotide polymorphisms (SNPs) in identifying genetic predispositions to various cancers (Omariba et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the exponential growth in SNP data presents challenges in identifying those that are functionally relevant. Computational tools have become essential in filtering out deleterious variants. In a recent study, Anwaar et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) identified clinically significant mutations in breast cancer families and used multiple pathogenicity prediction tools to classify variants such as G125V and L138F in RAD51C as high-risk based on their conserved domain positions and structural impact.\u003c/p\u003e\u003cp\u003eSimilarly, RAD51D variants have been shown to compromise HR efficiency. Cells deficient in RAD51D are particularly sensitive to poly (ADP-ribose) polymerase (PARP) inhibitors, highlighting a therapeutic avenue for tumors harboring RAD51D mutations. Structural analyses have also shown that certain SNPs in RAD51D affect protein folding and stability, influencing sensitivity or resistance to treatments (Somyajit et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; McAlpine et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe integration of bioinformatics and structural biology provides critical insights into tumor heterogeneity and genetic vulnerability. Tools such as SIFT and PolyPhen offer rapid, cost-effective approaches for identifying harmful SNPs, which can serve as biomarkers for patient stratification and targeted therapies (de Almeida et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These findings also support personalized medicine initiatives, as individuals carrying high-risk RAD51C or RAD51D variants may benefit from tailored screening and preventive strategies (Zhang et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, identifying population-specific variants contributes to the development of ethnically tailored interventions, a crucial aspect of global precision oncology (Sirugo et. Al., 2016).\u003c/p\u003e"},{"header":"2. Materials and method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data Retrieval:\u003c/h2\u003e\u003cp\u003eWe compiled a comprehensive catalog of Single Nucleotide Polymorphisms (SNPs) associated with the RAD51C and RAD51D genes by querying the NCBI dbSNP database using \"RAD51C\" and \"RAD51D\" as search terms. The retrieved SNPs were then filtered based on specific selection criteria (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Additionally, the complete FASTA sequences of the human RAD51C and RAD51D proteins were obtained from the NCBI database. Figure\u0026nbsp;1 illustrates a schematic representation of the methodology employed in this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Predicting deleterious nsSNPs:\u003c/h2\u003e\u003cp\u003eA variety of web servers and computational tools were used to assess all missense non-synonymous single nucleotide polymorphisms (nsSNPs) associated with the RAD51C and RAD51D genes. Because of their ability to forecast the functional effects of genetic variants\u0026mdash;especially nsSNPs\u0026mdash;which are essential for comprehending the genetic pathways underlying disease, tools like SIFT, PolyPhen-2, and PANTHER were especially selected. These prediction tools provide a comprehensive assessment of each variant's pathogenic potential by combining information on sequence conservation, structural traits, and biological context.\u003c/p\u003e\u003cp\u003eBased on sequence homology, evolutionary conservation, and the physicochemical characteristics of amino acids, the SIFT (Sorting Intolerant From Tolerant) tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://sift.bii.a-star.edu.sg\u003c/span\u003e\u003cspan address=\"http://sift.bii.a-star.edu.sg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) assesses whether an amino acid substitution is likely to affect protein function. It works on the premise that amino acids that are essential for protein function are typically conserved across species, increasing the likelihood that replacements at these locations will have negative effects (Ng and Henikoff, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). According to Ng et al. (2003), SIFT scores range from 0 to 1, with a score below 0.05 signifying a detrimental (intolerant) effect and a score over 0.05 indicating that the substitution is probably tolerated. It is a commonly used tool in genome-wide variant research because to its ability to examine big datasets effectively.\u003c/p\u003e\u003cp\u003eTHMM, Colis2, and SignalP are among the algorithms used by the PolyPhen-2 (Polymorphism Phenotyping v2) program to assess the possible impacts of amino acid changes on the structure and functionality of human proteins (George et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It classifies missense variations as benign, potentially harmful, or probably harmful after analyzing the position of the amino acid change, mapping SNPs onto known 3D protein structures, and including sequence annotations and structural characteristics. The tool is a reliable resource for evaluating the impact of nsSNPs implicated in complicated disorders because of its two-tiered prediction approach, which improves accuracy.\u003c/p\u003e\u003cp\u003eThe PANTHER (Protein Analysis through Evolutionary Relationships) tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://pantherdb.org/tools/cSNPscoreForm.jsp\u003c/span\u003e\u003cspan address=\"http://pantherdb.org/tools/cSNPscoreForm.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) predicts the possible structural and functional effects of amino acid substitutions by assessing the evolutionary conservation of particular amino acid residues across different species. Additionally, it evaluates both coding and non-coding variations' probable effects (Mi et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). PANTHER assists in identifying mutations that might affect the function of proteins by looking at evolutionary constraints on protein-coding areas. Researchers can also decipher the biological implications of genetic variations in the context of cellular systems and pathways thanks to its integrated pathway-level annotations.\u003c/p\u003e\u003cp\u003eA prediction tool called PhD-SNP (Predictor of human Deleterious Single Nucleotide Polymorphisms) classifies genetic variants by combining evolutionary sequence data with support vector machine (SVM) algorithms (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://SNPs.biofold.org/phd-snp/phd-snp.html\u003c/span\u003e\u003cspan address=\"http://SNPs.biofold.org/phd-snp/phd-snp.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). By building its predictive model from a large dataset of mutations that are either neutral or known to be disease-associated, it is able to evaluate the possible influence of SNPs according to their particular sequence context. For large-scale variation analysis, PhD-SNP is a reliable option due to its great generalizability across a variety of datasets and strong prediction performance (Capriotti et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo ascertain the probability that a particular mutation is linked to a disease, SNPs\u0026amp;GO is a predictive method that incorporates Gene Ontology (GO) annotations (Capriotti et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). SNPs\u0026amp;GO provides a more thorough assessment of the potential effects of mutations on protein function by combining sequence-based features with functional annotations. By placing the variant in a biological context using GO keywords associated with the target protein, it increases the accuracy of its predictions in differentiating between benign and harmful mutations (Calbrese et al., 2009).\u003c/p\u003e\u003cp\u003eBecause of their speed, ease of use, and compatibility with high-throughput analyses, SIFT and PolyPhen-2 are frequently chosen for the preliminary evaluation of non-synonymous SNPs (nsSNPs). These tools are perfect for large-scale applications like genome-wide association studies (GWAS) because of their proven performance, efficiency, and intuitive user interfaces. Even though programs like MutPred and SNAP2 provide more in-depth information\u0026mdash;such molecular mechanism predictions and functional implications\u0026mdash;they are typically more computationally intensive and generate intricate results that need expert interpretation. While SNAP2, which is powered by neural networks, performs well in a variety of poorly conserved regions, it produces granular predictions that may be difficult to interpret without specialized knowledge (Hecht et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). MutPred combines machine learning with functional annotations to predict effects such as changes in binding affinity (Li et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOn the other hand, researchers with limited infrastructure can more easily use SIFT and PolyPhen-2 since they are speedier and require fewer computer resources. They are therefore especially helpful for the preliminary screening and variant prioritization. Conversely, SNAP2 and MutPred are more appropriate for targeted, in-depth functional investigations where a thorough grasp of the mechanisms is crucial. Only nsSNPs that were consistently identified by all six methods as harmful or detrimental were chosen for downstream study. The disparities and inconsistencies that could result from output variances across several prediction platforms are reduced by this consensus-based method.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Modeling the native RAD51C and RAD51D protein using MODELLER v10.2:\u003c/h2\u003e\u003cp\u003eMODELLER v10.2, a widely used tool that employs comparative homology modeling to predict protein structures. Both versions of MODELLER were obtained from Andrej Sali\u0026rsquo;s official website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://salilab.org/\u003c/span\u003e\u003cspan address=\"https://salilab.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The software supports execution with or without a Python environment; if Python is not installed, modeling scripts can still be run via the command: mod10.2 SCRIPT_NAME.py.\u003c/p\u003e\u003cp\u003eFor Python-based modeling, MODELLER offers pre-configured scripts for sequence alignment and structure generation. The homology modeling process followed a structured approach: selecting suitable template structures via BLAST, validating the chosen templates by aligning them with the target sequence, constructing the 3D models, and finally assessing model quality using a Ramachandran plot. Since the full protein structures of RAD51C and RAD51D proteins were already present in PDB database so we have used them as our native proteins for the modelling of mutant proteins respectively. The resulting protein models were saved under the names RAD51C_WILD and RAD51D_WILD, respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Generation of mutant protein structures:\u003c/h2\u003e\u003cp\u003eThe most accurately validated model was selected and subsequently used as a template to introduce mutations into the protein structures, followed by evaluation using MODELLER version 10.2. This process combines comparative modeling techniques with optimization algorithms to incorporate specific alterations into the protein sequence, including amino acid substitutions, insertions, or deletions. During modeling, MODELLER aligns the target sequence with the chosen template structure, utilizing the spatial configuration of atoms from the template as a reference. It then refines the mutant model by adjusting dihedral angles, bond lengths, and other structural parameters to produce a reliable three-dimensional structure of the mutated protein.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Model Validation:\u003c/h2\u003e\u003cp\u003eAll selected mutant models were validated using Ramachandran plots, a standard method in structural biology for evaluating the stereochemical quality of protein structures. Named after G. N. Ramachandran, the plot graphically displays the phi (ϕ) and psi (ψ) dihedral angles of amino acid residues, which correspond to rotations around the Cα\u0026ndash;C and C\u0026ndash;N bonds, respectively. Each point on the plot represents the torsion angle combination for a specific residue within the protein structure. The plot is segmented into allowed and disallowed regions, determined by steric constraints and atomic clashes. Allowed regions signify energetically favorable conformations that are structurally viable, while disallowed regions highlight unlikely or sterically hindered conformations. Following structural validation, all modeled proteins underwent energy minimization using the Chimera tool, which applies the steepest descent algorithm to reduce potential energy and optimize the stability of the 3D structures.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 RMSD value calculation:\u003c/h2\u003e\u003cp\u003eThe RMSD (Root Mean Square Deviation) values for both proteins were calculated by superimposing the native and mutant structures using the \"align\" function in PyMOL. RMSD serves as a measure of structural and functional deviation from the native protein; a higher RMSD value indicates a greater level of deviation, suggesting more substantial changes in the protein\u0026rsquo;s conformation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Determining SNP\u0026rsquo;s impact on the RAD51C and RAD51D protein stability:\u003c/h2\u003e\u003cp\u003eTo evaluate the impact of amino acid substitutions on the stability or potential denaturation of the RAD51D protein, we utilized two independent in silico prediction tools: I-Mutant and MuPro. Both algorithms rely on sequence-based analysis to assess changes in protein stability resulting from mutations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Molecular Docking for Protein Interaction Identification:\u003c/h2\u003e\u003cp\u003eMutant models of RAD51C and RAD51D proteins were docked with their known interacting partners\u0026mdash;XRCC2, XRCC3, RAD51B, and RAD51C\u0026mdash;to assess potential changes in binding affinity and interaction patterns. Protein\u0026ndash;protein docking was carried out using the ClusPro server, with all parameters set to default values (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cluspro.org/help.php\u003c/span\u003e\u003cspan address=\"https://cluspro.org/help.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). ClusPro was chosen for its high accuracy, reliability, and intuitive user interface, making it a widely adopted tool in structural bioinformatics.\u003c/p\u003e\u003cp\u003eClusPro performs docking through a systematic pipeline involving rigid body docking, energy-based scoring, and clustering of low-energy conformations to predict the most likely binding configurations (Kozakov et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The server prioritizes the most frequently occurring conformations, which are presumed to represent native-like binding modes. Additionally, ClusPro provides the option to define specific restraints or bias the docking toward particular residues, enabling more precise modeling of biologically relevant interactions (Kozakov et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). For each docking run, ClusPro generates ten distinct docked models, each accompanied by a score reflecting the estimated binding energy of the complex.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Molecular Dynamics Simulations:\u003c/h2\u003e\u003cp\u003eThe RAD51C and RAD51D protein complexes, along with their respective mutant forms, underwent comprehensive molecular dynamics (MD) simulations using GROMACS 2024 for a duration of 100 nanoseconds. Following the protocol outlined by Singh et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the proteins were prepared using the all-atom OPLS force field, which included system minimization, solvation, and charge neutralization with Na⁺ and Cl⁻ ions.\u003c/p\u003e\u003cp\u003eThe simulation process began with energy minimization using the steepest descent algorithm, followed by equilibration in two phases: a canonical ensemble (NVT) and an isothermal\u0026ndash;isobaric ensemble (NPT), each lasting 5 ns. The production run of 100 ns was then carried out, and the resulting trajectories were analyzed for key structural parameters including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA) to evaluate the stability and conformational dynamics of the protein systems.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eIdentifying deleterious SNPs is crucial for uncovering the genetic basis of Hereditary Breast and Ovarian Cancer (HBOC), as these variations often significantly increase an individual's susceptibility to these cancers. Through the use of advanced computational tools and genomic databases, researchers can explore the molecular pathways involved in HBOC, offering important insights into potential therapeutic targets and preventive strategies.\u003c/p\u003e\u003cp\u003eFigure 1 presents a detailed overview of the workflow and database servers employed to detect harmful Single Nucleotide Polymorphisms (SNPs) in the human DNA repair genes RAD51C and RAD51D. These databases and tools are integral to the analytical framework, playing a key role in the accurate identification and functional characterization of pathogenic variants. Moreover, the depicted workflow ensures efficient data integration, systematic analysis, and meaningful interpretation, streamlining the discovery of SNPs with clinical and biological relevance.\u003c/p\u003e\u003cp\u003eAll genes analyzed in this study were sourced from the dbSNP database. For the RAD51C gene, a total of 19,195 SNPs were identified, comprising 10,027 intronic variants, 880 missense variants, and 359 coding synonymous variants. This investigation focused specifically on non-synonymous SNPs (nsSNPs) in RAD51C, as these variants are more likely to alter the structure or function of the resulting protein.\u003c/p\u003e\u003cp\u003eSimilarly, for the RAD51D gene, 19,195 SNPs were also retrieved, including 12,048 intronic variants, 860 missense variants, and 389 coding synonymous variants. The study was limited to the analysis of nsSNPs in RAD51D as well, due to their potential to disrupt protein function or structure, thereby impairing homologous recombination repair and increasing the risk of cancer development.\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Finding harmful and detrimental nsSNPs using a sequence-based homology methodology:\u003c/h2\u003e\u003cp\u003eThe SIFT, Polyp hen 2 and PANTHER algorithms forecast harmful nsSNP through a sequence-based homology methodology. At first, every single SNP that was obtained from the dbSNP database was examined in SIFT. Of all the SNPs that were examined in SIFT, only those that originated from the coding (CDS) region were selected for additional examination. The SIFT score is the normalized probability that the amino acid change is tolerated. SIFT predicts substitutions with scores less than 0.05 as deleterious and values up to 1 as tolerated amino acid substitution. SIFT has filtered out 19,195 SNPs for RAD51C, of which just 209 originate within the gene's CDS region and predicted 69 as deleterious and 124 as tolerated. On the basis of SIFT scores ranging between 0.001-1 SIFT has scored a total 25 SNPs of lowest score i.e. zero which will be further deleterious for the resultant protein function. The SIFT score represents the normalized probability of an amino acid substitution being tolerated, with scores below 0.05 classified as deleterious and values up to 1 considered tolerated. (Table\u0026nbsp;1)\u003c/p\u003e\u003cp\u003eSimilarly, for RAD51D gene SIFT filtered out 12,753 SNPs, identifying 559 in the CDS region. Among these, 150 were classified as deleterious and 389 as tolerated, with 38 SNPs scoring 0, indicating potential severe functional consequences.\u003c/p\u003e\u003cp\u003ePANTHER predicted 59 harmful and 21 benign entries out of 210 RAD51C entries. For RAD51C, 22 entries were unanimously selected as deleterious. Out of these nsSNPs after removing multiple rsIDs entries for the same nsSNP the following results were obtained. Also for RAD51D PANTHER have predicted 164 harmful SNPs out of 210 RAD51D entries, with 8 unanimously identified as deleterious. After eliminating redundant rsID entries for the same nsSNPs, the final results were compiled.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Sequence- and structure-based homology-based Polyphen server predicted the following functionally harmful nsSNPs:\u003c/h2\u003e\u003cp\u003ePolyPhen-2 (Polymorphism Phenotyping v2) is a sophisticated computational tool developed by the Bork Group to evaluate the potential impact of genetic variations\u0026mdash;particularly amino acid substitutions\u0026mdash;on the structure and function of human proteins. By combining sequence-based and structure-based analyses, PolyPhen-2 assesses the pathogenic potential of variants using information such as phylogenetic conservation, structural features, and protein sequence data.\u003c/p\u003e\u003cp\u003eIn the case of RAD51C, predictions made using both the HumDiv and HumVar datasets classified 31 SNPs as either possibly or probably damaging. Notably, all 31 amino acid substitutions were scored as probably damaging, indicating a high likelihood that these mutations negatively affect protein function.\u003c/p\u003e\u003cp\u003eFor RAD51D, PolyPhen-2 identified 19 SNPs as possibly damaging, while 10 substitutions were categorized as probably damaging, reflecting a strong potential for these variants to impair the protein\u0026rsquo;s biological activity. All the unanimous SNPs that were predicted deleterious by all the software have been listed in table 2.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.3 The disease prediction of nsSNP\u0026rsquo;s by the PhD-SNP and SNP \u0026amp; GO web tools:\u003c/h2\u003e\u003cp\u003ePhD-SNP is a computational tool designed to predict the phenotypic effects of non-synonymous substitutions, offering valuable insights into how genetic variations may influence protein function. In addition to this, it also assesses whether specific amino acid changes are likely to be associated with disease development. To evaluate the disease relevance of single amino acid substitutions, researchers utilize both PhD-SNP and SNP\u0026amp;GO.\u003c/p\u003e\u003cp\u003eFor the RAD51C gene, PhD-SNP initially identified 21 variants as potentially disease-associated. However, after excluding entries with invalid protein IDs, only 14 entries, representing 11 unique rsIDs, were retained, as shown in Table\u0026nbsp;3.\u003c/p\u003e\u003cp\u003eIn the case of RAD51D, PhD-SNP predicted 158 disease-linked variants, while SNP\u0026amp;GO identified 69. After removing duplicate entries, 8 distinct rsIDs remained, which are also detailed in Table\u0026nbsp;3.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Modelling of the complete RAD51C and RAD51D proteins using MODELLER (Comparative Homology Modelling):\u003c/h2\u003e\u003cp\u003eThese nineteen nsSNPs were taken into consideration for further study. We created the RAD51 mutant structures using MODELLER v10.2 and a homology modelling approach to predict their effects on stability and functionality because the full structures of the RAD51C and RAD51D proteins were available in the PDB database. MODELLER was told to use the given templates to create five different protein architectures. Out of the five models that MODELLER generates, the best model is selected using a number of parameters. The DOPE score is one of the most commonly utilized parameters. We chose the structure with the lowest DOPE score because the better the simulated structure is thought to be, the lower the DOPE value. The models \"RAD51C.pdb\" and \"RAD51D.pdb\" (Fig.\u0026nbsp;2a and b) have been chosen as the best models for RAD51C and RAD51D proteins based on the lowest DOPE score. The Ramachandran Plot was used to further analyse the chosen models in order to verify the folding characteristics and protein structure (Supplementary Table\u0026nbsp;1).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.5 RMSD value calculation of the modelled mutant protein\u003c/b\u003e:\u003c/h2\u003e\u003cp\u003eThe Root Mean Square Deviation (RMSD) values presented for various RAD51C single nucleotide polymorphisms (SNPs) represent the degree of structural deviation in the protein caused by each specific amino acid (A.A) substitution. RMSD is a quantitative measure used to compare the altered protein structure to the native form, with higher values suggesting greater structural disturbance. In this dataset, RMSD values range from 0.079 to 0.134, indicating variable but relatively modest changes in protein conformation across different SNPs.\u003c/p\u003e\u003cp\u003eNotably, the SNP rs137947462 (R212C) exhibits the highest RMSD of 0.134, suggesting a considerable conformational impact, potentially affecting RAD51C's DNA repair function due to structural instability. Other mutations such as rs149331537 (L262V) and rs267606998 (G125V) also show elevated RMSD values (0.128 and 0.130, respectively), indicating these variants might interfere with the protein\u0026rsquo;s ability to participate in homologous recombination, a critical pathway for genome stability. Conversely, SNPs like rs35151472 (G162E) and rs374196453 (R260W) have lower RMSD values (0.079 and 0.097, respectively), suggesting minor structural perturbations and possibly lesser functional consequences.\u003c/p\u003e\u003cp\u003eImportantly, some residues like R212 and G125 appear in multiple mutations (e.g., R212C and R212H; G125S and G125V), highlighting their structural sensitivity. Even though some RMSD values seem modest in absolute terms, small structural shifts in critical domains may still disrupt RAD51C\u0026rsquo;s interaction with partner proteins or DNA substrates, thereby compromising DNA repair efficiency. Therefore, while the RMSD values provide an initial structural insight, functional assays and further in silico analysis would be essential to correlate these structural deviations with pathogenicity and cancer susceptibility, particularly in the context of breast and ovarian cancers linked to RAD51C dysfunction.\u003c/p\u003e\u003cp\u003eSimilarly in case of RAD51D proteins the RMSD (root mean square deviations) values provided for the SNPs in RDA51D gene indicate the extent of structural deviation caused by amino acid substitutions. Lower RMSD values suggest minimal structural deviations, higher values indicate significant conformational changes, which could potentially impact protein function. From the total examined SNPs, most SNPS exhibit relatively low RMSD values, ranging from 0.115 (S207L) to 0.145 (D90N), suggesting that these variants may not cause drastic alterations in the protein structure. However, the SNPs S88P (RMSD\u0026thinsp;=\u0026thinsp;0.227) and A210E (RMSD\u0026thinsp;=\u0026thinsp;1.159) show considerably high deviations, indicating potential structural disruptions. The proline substitution in S88P could induce rigidity, affecting protein flexibility, while the A210E mutation involves shift from non-polar alanine to negatively charged glutamate, potentially altering interactions and destabilization of protein structure.\u003c/p\u003e\u003cp\u003eGiven the role of RAD51D in the homologous recombination and DNA repair, these structural changes might influence its function in maintaining genomic stability. Particularly, the A210E variant with the highest RMSD warrants further investigation for its possible association with compromised DNA repair efficiency, which could contribute to cancer predisposition. Experimental validation and functional assays are necessary to confirm thses predictions. (Table\u0026nbsp;4)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Analysing the stability changes of mutants using the I-Mutant and MuPro web tools:\u003c/h2\u003e\u003cp\u003eThe results from I-mutant and MUpro tools provide insights into the impact of RAD51C and RAD51D SNP variants on protein stability. Both tools predict whether a given mutation increases or decreases the stability of the protein, which is crucial for understanding its functional consequences in homologous recombination and DNA repair. Decreased stability suggest potential structural disruptions that may impair protein function, while increased stability could lead to altered protein dynamics and misfolding.\u003c/p\u003e\u003cp\u003eMost mutations, including R249C, G162E, R212C, L297P, L262V, R212H, L219S, R258H, and G112A, are predicted by both tools to decrease the stability of RAD51C. This reduction in stability may impair RAD51C's ability to interact with other HR proteins such as RAD51, BRCA2, and XRCC3, potentially leading to compromised DNA repair and increased genomic instability\u0026mdash;a hallmark of cancer development. Notably, mutations like L297P and L262V affect leucine residues, which are often involved in hydrophobic core formation and protein folding; such substitutions could lead to misfolding or degradation.\u003c/p\u003e\u003cp\u003eInterestingly, the SNP rs267606998 (G125V) is predicted by I-Mutant to increase stability but by MUpro to decrease it, indicating conflicting outcomes. Although increased stability might seem beneficial, it can also hinder protein function if it leads to aberrant folding or impaired interaction with DNA or other repair factors. The consistent prediction of reduced stability across the majority of these SNPs suggests that these variants may compromise RAD51C function.\u003c/p\u003e\u003cp\u003eIn case of RAD51D, most SNPs, both I-mutant and MUpro predict a decrease in protein stability. Variants such as G265R, C9S, R145H, R275Q and D90N show decreased stability across both tools, indicating these mutations may destabilize the RAD51D structure and weaken its interaction within the RAD51 paralog complex. This instability could compromise RAD51D role in homologous recombination, leading to defective DNA repair and increased susceptibility to genomic instability and cancer. The R275Q mutation shows error suggesting uncertainty in its impact, but since I-mutant predicts a decrease, it is likely destabilizing.\u003c/p\u003e\u003cp\u003eInterestingly, S207L and A210E show conflicting predictions. While I-Mutant predicts a decrease in stability for S207L, MuPro suggests an increase. This discrepancy indicates that the mutation may induce a conformational change rather than outright destabilization. A210E, on the other hand, is predicted to increase stability by I-Mutant but decrease stability by MuPro. The alanine-to-glutamate substitution introduces a charged residue in place of a small, nonpolar one, which could lead to altered binding properties rather than outright destabilization. The S207P mutation is notable as it decreases stability in MuPro but increases in I-Mutant, possibly due to the rigid structure of proline, which can disrupt local folding. This could affect RAD51D\u0026rsquo;s flexibility and interaction with binding partners like XRCC2, RAD51B, and RAD51C. Overall, the majority of these SNPs are predicted to decrease RAD51D stability, suggesting potential functional impairment in DNA repair pathways. The variations in S207L and A210E predictions warrant further experimental validation to determine their true biological consequences.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.7 RAD51C and RAD51D protein domain mutation mapping:\u003c/h2\u003e\u003cp\u003eThe domain mapping of the RAD51C protein reveals the distribution of several missense mutations across three major functional domains. The N-terminal domain (residues 1\u0026ndash;90) harbors the L27V mutation. The central RecA-like ATP-binding domain (residues 96\u0026ndash;186) contains mutations such as G112A, G125V, and G162E, suggesting potential impacts on ATP binding and homologous recombination activity. The C-terminal DNA recombination/repair domain (residues 207\u0026ndash;348) shows a cluster of mutations including R212C, R212H, L219S, R249C, R258H, L262V, and L297P, indicating a high mutational burden in this critical region for DNA repair functionality. Overall, the mapping highlights key mutational hotspots within functionally significant regions of RAD51C, which may be relevant to its role in genome maintenance and cancer susceptibility. (Fig.\u0026nbsp;3)\u003c/p\u003e\u003cp\u003eSimilarly, the domain mapping of RAD51D shows multiple missense mutations distributed across its functional domains. The RAD51-like N-terminal domain (residues 1\u0026ndash;110) contains mutations such as C9S, E74G, S88P, and D90N, suggesting alterations near the start of the protein. The ATPase domain (residues 112\u0026ndash;200) has a single mutation, R145H, indicating potential effects on ATP hydrolysis. The DNA repair protein C-terminal domain (residues 201\u0026ndash;298) carries several mutations including S207L, S207P, A210E, G265R, and R275Q, clustering within a region critical for DNA repair activity. (Fig.\u0026nbsp;4)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.8 Protein -protein docking analysis:\u003c/h2\u003e\u003cp\u003eThe docking results summarize the binding affinities between various RAD51C protein mutants and its key interacting partners\u0026mdash;XRCC2, XRCC3, RAD51B, and RAD51D\u0026mdash;which are essential components of the homologous recombination (HR) DNA repair complex. The binding scores (in kcal/mol) indicate interaction strength, where more negative values represent stronger binding affinities. The wild-type RAD51C (RAD51C-W) exhibits moderate affinity across all partners, serving as the baseline for comparison. Several mutations\u0026mdash;including R212C, R249C, and L297P\u0026mdash;demonstrate significantly more negative docking scores, especially with XRCC3 and RAD51B (e.g., R249C: -1376 with XRCC3 and \u0026minus;\u0026thinsp;1288.5 with RAD51B), suggesting stronger or aberrant binding. This could reflect a potential gain-of-binding, which might trap RAD51C in non-functional or misassembled complexes, disrupting dynamic interactions essential for DNA repair fidelity. (Fig.\u0026nbsp;5a \u0026ndash; 5e)\u003c/p\u003e\u003cp\u003eIn contrast, mutations such as G125V and R212H show weaker or comparable interactions to the wild-type, implying a potential loss or alteration of binding, particularly with XRCC2 and XRCC3. For example, G125V displays a much less negative score with XRCC2 (-995.1) compared to the wild-type (-1023.6), which may reduce RAD51C\u0026rsquo;s ability to integrate into the BCDX2 complex, compromising its function in DNA damage response. Mutations like L219S, L262V, and R258H, which occur in the ATP-binding domain, generally show consistent interaction energies across partners, but modest deviations (e.g., R258H: -1145.6 with RAD51B) still suggest structural changes that could influence complex formation dynamics. Biologically, such altered binding affinities\u0026mdash;whether increased or decreased\u0026mdash;may impair RAD51C\u0026rsquo;s precise coordination with HR partners, leading to defective DNA repair, accumulation of DNA damage, and increased cancer susceptibility. (Table\u0026nbsp;5), (Supplementary Figs.\u0026nbsp;1\u0026ndash;11)\u003c/p\u003e\u003cp\u003eThe docking results for RAD51D SNP variants with its interacting partners\u0026mdash;XRCC2, RAD51B, and RAD51C\u0026mdash;reveal important insights into how amino acid substitutions may alter protein-protein interactions within the homologous recombination (HR) repair pathway. RAD51D is a crucial component of the RAD51 paralog complex, which facilitates DNA repair and maintains genomic stability. Any disruption in these interactions can potentially impair DNA repair efficiency, increasing the risk of genomic instability and cancer susceptibility. Comparing the wild-type (RAD51D-WT) with mutant variants shows that most SNPs cause varying degrees of binding affinity changes, either weakening or strengthening interactions with XRCC2, RAD51B, and RAD51C. (Fig.\u0026nbsp;6a \u0026ndash; 6e)\u003c/p\u003e\u003cp\u003eAmong the analysed SNPs, A210E exhibits one of the most notable shifts in binding affinity. This mutation, which replaces a small nonpolar alanine with a negatively charged glutamate, introduces potential charge repulsions and steric hindrance, leading to a weakened interaction with RAD51B (-1124 vs. -1174.1 in WT) and XRCC2 (-1059.5 vs. -1024.1 in WT). Interestingly, A210E enhances binding with RAD51C (-1294.8 vs. -1195.4 in WT), suggesting a structural rearrangement that may disrupt the normal function of the RAD51 paralog complex. Similarly, the S207L mutation, which replaces a polar serine with a hydrophobic leucine, leads to a significant change in binding affinity, particularly strengthening its interaction with RAD51C (-1274.4 vs. -1195.4 in WT). These changes could reflect an altered binding conformation, potentially leading to impaired recruitment of RAD51D in DNA repair processes. (Fig.\u0026nbsp;6f \u0026ndash; 6h)\u003c/p\u003e\u003cp\u003eOther variants, such as D90N, show moderate changes in docking scores. Meanwhile, D90N exhibits weaker binding to XRCC2 (-921.8 vs. -1024.1 in WT), suggesting a possible disruption in the RAD51D-XRCC2 interaction, which is critical for efficient DNA repair. Overall, mutations like A210E and S207L that significantly alter protein binding dynamics could compromise the stability of the RAD51 paralog complex, potentially leading to defective homologous recombination and increased susceptibility to genomic instability and cancer. (Table\u0026nbsp;6), (Supplementary Figs.\u0026nbsp;12\u0026ndash;16).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.9 Molecular dynamics simulation\u003c/h2\u003e\u003cp\u003eThe molecular dynamics (MD) simulation results for the RAD51C protein and its interaction complexes with XRCC2 and RAD51B provide a comprehensive view of how specific polymorphisms can influence the structural dynamics, stability, and potential functional consequences of the protein. These simulations were analyzed using key structural parameters, including RMSD, RMSF, radius of gyration (Rg), and solvent-accessible surface area (SASA), as presented in Figures .\u003c/p\u003e\u003cp\u003eStarting with the Root Mean Square Deviation (RMSD) analysis, Fig.\u0026nbsp;7a highlights the differences in structural stability between the wild-type RAD51C-XRCC2 complex and its R212H polymorphic variant. The average RMSD for the wild-type complex is 0.7279 nm, indicating moderate conformational stability throughout the simulation. In contrast, the R212H-XRCC2 complex shows a slightly lower RMSD value of 0.654 nm, suggesting improved structural stability in the mutant form. Similarly, Fig.\u0026nbsp;8a presents the RMSD profiles for the wild-type RAD51C-RAD51B complex and its polymorphic variants, L219S and L262V. The wild-type complex has an average RMSD of 0.858 nm, again indicating moderate stability. The L219S mutant exhibits a higher RMSD of 1.014 nm, reflecting greater structural deviations and hence reduced stability. Conversely, the L262V mutant demonstrates a lower RMSD of 0.7871 nm, suggesting that this mutation might confer improved stability over the wild type. These findings emphasize how specific mutations can either destabilize or stabilize the RAD51C complexes, with implications for their functional efficacy in homologous recombination.\u003c/p\u003e\u003cp\u003eThe Root Mean Square Fluctuation (RMSF) analysis, shown in Figs.\u0026nbsp;7b and 8b, further details the residue-wise flexibility of the protein complexes. In Fig.\u0026nbsp;7b, the wild-type RAD51C-XRCC2 complex shows notable fluctuations at residues 2\u0026ndash;18, 244\u0026ndash;268, 404\u0026ndash;474, and 522\u0026ndash;533, indicating flexible loop or terminal regions. In contrast, the R212H variant displays distinct fluctuation peaks at residues 200\u0026ndash;226, 281, 570, and 626. These shifts in flexibility could reflect conformational alterations that may influence protein-protein interaction dynamics. In Fig.\u0026nbsp;8b, the wild-type RAD51C-RAD51B complex exhibits a significant fluctuation peak at residue 364. The L219S mutant, however, shows widespread fluctuations across multiple regions, including residues 6\u0026ndash;49, 266, 276, 336, 411\u0026ndash;500, 563, 592, and 667\u0026ndash;725, indicating a markedly unstable behavior. The L262V mutant also shows prominent peaks at residues 274, 565, and 628. These increased fluctuations, especially in L219S, suggest that this variant may be less structurally stable and potentially impaired in maintaining essential interactions during DNA repair processes.\u003c/p\u003e\u003cp\u003eThe radius of gyration (Rg) results, shown in Figs.\u0026nbsp;7c and 8c, provide insights into the compactness of the protein complexes. In Fig.\u0026nbsp;7c, the wild-type RAD51C-XRCC2 complex exhibits an average Rg of 3.263 nm, while the R212H variant shows a slightly lower average Rg of 2.887 nm. The lower Rg of the R212H complex suggests a more compact and possibly more stable conformation. In Fig.\u0026nbsp;8c, the wild-type RAD51C-RAD51B complex has an average Rg of 3.13 nm, whereas the L219S and L262V mutants show higher Rg values of 3.302 nm and 3.211 nm, respectively. Notably, the L219S variant displays a significant increase in Rg after 33 ns, which continues until the end of the 100 ns simulation, indicating a deviation from its initial compactness and suggesting unfolding or conformational drift. This behavior is indicative of compromised structural stability in the L219S mutant compared to both the wild type and the L262V variant.\u003c/p\u003e\u003cp\u003eSolvent Accessible Surface Area (SASA) values, presented in Figs.\u0026nbsp;7d and 8d, offer further evidence of mutation-induced structural alterations. In Fig.\u0026nbsp;7d, the wild-type RAD51C-XRCC2 complex has an average SASA of 345.7478 nm\u0026sup2;, while the R212H variant shows a slightly reduced SASA of 345.2597 nm\u0026sup2;. This marginal decrease suggests minimal change in solvent exposure and implies that the mutation does not significantly affect the complex\u0026rsquo;s surface characteristics. In Fig.\u0026nbsp;8d, the wild-type RAD51C-RAD51B complex has an average SASA of 397.433 nm\u0026sup2;. The L219S and L262V mutants exhibit increased average SASA values of 399.4568 nm\u0026sup2; and 403.8887 nm\u0026sup2;, respectively. These increases imply that the mutant complexes have more exposed surface areas, which may alter their interaction profiles with other biomolecules or solvent, potentially reducing complex stability. Particularly, the higher SASA values associated with L219S and L262V suggest that these mutations might disrupt the normal packing of the protein complex, leading to functional impairment.\u003c/p\u003e\u003cp\u003eIn conclusion, the MD simulations reveal that polymorphisms in RAD51C, such as R212H, L219S, and L262V, distinctly alter the protein\u0026rsquo;s structural dynamics and stability in complex with XRCC2 and RAD51B. While R212H appears to confer greater stability and compactness, the L219S variant displays pronounced instability across multiple parameters, including higher RMSD, extensive residue fluctuations, increasing Rg over time, and elevated SASA. These characteristics suggest a significant structural compromise in L219S, potentially impairing RAD51C\u0026rsquo;s role in DNA repair. Conversely, L262V shows moderate stability with minor deviations, indicating a less detrimental impact compared to L219S. Collectively, these findings underscore the importance of evaluating structural dynamics in assessing the functional consequences of RAD51C mutations, with direct relevance to understanding cancer susceptibility and guiding targeted therapeutic interventions.\u003c/p\u003e\u003cp\u003eThe molecular dynamics (MD) simulation results of RAD51D and its variants, interacting with its known partners XRCC2, RAD51B, and RAD51C, reveal significant insights into specific mutations' structural and functional impact. The simulation focused on key metrics such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration, solvent accessible surface area (SASA), and the number of hydrogen bonds formed during the simulation. These parameters were systematically analyzed across multiple complexes and mutant variants.\u003c/p\u003e\u003cp\u003eIn the RAD51D\u0026ndash;XRCC2 complex, the wild-type protein demonstrated stable dynamics with an average RMSD of approximately 1.16 \u0026Aring;, (Fig.\u0026nbsp;9a) while the D90N mutation exhibited a lower RMSD of around 0.68 \u0026Aring;, suggesting a structurally more rigid complex. This decreased deviation was supported by a corresponding reduction in RMSF (0.23 \u0026Aring; in D90N vs. 0.47 \u0026Aring; in wild-type), indicating less flexibility in the D90N mutant. (Fig.\u0026nbsp;9b) This rigidity could limit the protein\u0026rsquo;s conformational adaptability during DNA repair processes. Further, the D90N variant showed a slightly decreased radius of gyration and SASA compared to the wild-type, pointing to a more compact and less solvent-exposed structure. (Fig.\u0026nbsp;9c and d) Interestingly, D90N also exhibited a higher average number of hydrogen bonds (407) than the wild-type (400), suggesting enhanced internal stabilization that might hinder necessary conformational transitions or partner interactions during homologous recombination.\u003c/p\u003e\u003cp\u003eFor the RAD51D\u0026ndash;RAD51B complex, the wild-type structure maintained low RMSD and RMSF values, denoting structural integrity. However, the S207L mutant displayed a substantial increase in RMSD (1.03 \u0026Aring;) and RMSF (0.39 \u0026Aring;), reflecting increased structural deviation and flexibility. (Fig.\u0026nbsp;10a and b) These changes suggest that the S207L mutation may weaken the protein-protein interaction interface with RAD51B, possibly affecting RAD51D's function in the RAD51 paralog complex. This is further evidenced by an increased radius of gyration and SASA, indicating a less compact and more exposed structure. The number of hydrogen bonds in S207L was also higher than in the wild-type, possibly as a compensatory mechanism to stabilize the perturbed structure. In contrast, the G265R mutation appeared to cause a milder impact, with moderate deviations in RMSD and slightly lower RMSF, hinting at a potential but less severe effect on structural integrity and function. (Fig.\u0026nbsp;10c and 10d)\u003c/p\u003e\u003cp\u003eIn the RAD51D\u0026ndash;RAD51C complex, both the D90N and S207P variants were evaluated alongside the wild-type. The S207P mutant emerged as the most structurally disruptive, with elevated RMSD (0.80 \u0026Aring;) and RMSF (0.54 \u0026Aring;), indicating both global and local structural fluctuations. (Fig.\u0026nbsp;11a and 11b)It also showed a markedly increased radius of gyration and SASA, suggesting a looser, more flexible structure that may impair stable complex formation with RAD51C. (Fig.\u0026nbsp;11c and 11d) Additionally, the S207P mutant exhibited a lower average hydrogen bond count compared to the wild-type and D90N, implying reduced internal interactions and stability. D90N, on the other hand, maintained a structural profile similar to that seen in the XRCC2 complex, with slightly lower RMSD and RMSF than the wild-type, confirming its stabilizing but potentially rigidifying effect across different protein interfaces.\u003c/p\u003e\u003cp\u003eBiologically, these findings highlight the differential impact of specific RAD51D mutations on protein structure and stability. The D90N mutation consistently appears to stabilize the protein and reduce flexibility, potentially at the cost of functional adaptability required during homologous recombination. Conversely, the S207L and S207P mutations introduce significant flexibility and reduce compactness, which may disrupt critical protein-protein interactions, thereby impairing the formation or stability of the RAD51 paralog complex. These disruptions could compromise RAD51D\u0026rsquo;s role in DNA repair, potentially leading to increased genomic instability and heightened cancer susceptibility. The G265R mutation shows a moderate structural effect, suggesting it may represent a hypomorphic or less penetrant pathogenic variant. Collectively, these results underscore the importance of residue-specific effects on RAD51D function and provide molecular-level explanations for the potential pathogenicity of these mutations in hereditary breast and ovarian cancers.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe current study presents an integrated computational and structural analysis of RAD51C and RAD51D genes, underscoring their critical roles in homologous recombination repair (HRR) and their implications in cancer susceptibility, particularly breast and ovarian cancers. Numerous studies have established that single nucleotide polymorphisms (SNPs), particularly missense mutations in DNA repair genes, contribute significantly to cancer progression. RAD51C mutations have been implicated in a variety of malignancies including breast, ovarian, and head and neck cancers (Smolarz et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Grenser et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Vuorela et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Given their direct involvement in disease pathology and treatment responsiveness, this study focused on identifying deleterious non-synonymous SNPs (nsSNPs) in RAD51C and RAD51D through comprehensive in silico analysis. Utilizing tools such as SIFT, PROVEAN, PANTHER, PolyPhen for functional prediction, PhD-SNP and SNP\u0026amp;GO for disease association, and MUpro and I-Mutant for protein stability evaluation, a total of 19,195 SNPs retrieved from dbSNP were screened for the RAD51C gene.\u003c/p\u003e\u003cp\u003eThe multi-tool approach enabled robust cross-validation, leading to the identification of 11 pathogenic nsSNPs in RAD51C, predominantly localized in two functionally crucial domains: the ATP-binding domain (G112A, G125V, G125S, G162E) and the DNA repair/recombination C-terminal domain (R212C, R212H, L219S, R249C, R258H, L262V, L297P). Glycine mutations were particularly frequent and significant, given glycine\u0026rsquo;s inherent flexibility and its role in maintaining structural integrity due to the absence of a side chain. Similarly, arginine mutations occurred at five positions, indicating potential hotspots for functional disruption. Since protein flexibility is vital to molecular function, these substitutions\u0026mdash;especially involving glycine and arginine\u0026mdash;may cause deleterious conformational alterations.\u003c/p\u003e\u003cp\u003eMolecular modeling and docking analyses revealed that certain mutations, especially R212H in the RAD51C-XRCC2 complex and L219S and L262V in the RAD51C-RAD51B complex, led to a decline in binding affinity. The docking results were further validated through molecular dynamics (MD) simulations, which showed that these mutations compromised the overall stability of the protein complexes. In particular, the L219S variant exhibited higher root mean square deviation (RMSD), increased root mean square fluctuation (RMSF) across multiple residues, a sustained increase in radius of gyration (Rg), and elevated solvent-accessible surface area (SASA), collectively indicating structural destabilization. By contrast, the R212H mutation, although altering specific residue flexibility, showed slightly improved compactness and reduced RMSD and SASA values, suggesting a nuanced effect on stability.\u003c/p\u003e\u003cp\u003eStructurally, RAD51C functions as a core component of two key HRR complexes: the BCDX2 complex (comprising RAD51B, RAD51C, RAD51D, and XRCC2) and the CX3 complex (comprising RAD51C and XRCC3). These complexes play pivotal roles in stabilizing RAD51 nucleoprotein filaments and facilitating strand invasion\u0026mdash;key steps in homologous DNA repair (Lio et. Al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Miller et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Disruption of these interactions, as observed in the L219S and L262V mutants, can impair early recombination processes, potentially leading to inefficient double-strand break repair and increased genomic instability. This mechanistic impairment aligns with previous findings showing RAD51C amplification in breast tumors (Tarsounas \u0026amp; West, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and its frequent mutation in familial breast and ovarian cancer cases (Meindl et al., 2010).\u003c/p\u003e\u003cp\u003eIn parallel, RAD51D, another essential paralog in the RAD51 family, contributes significantly to HRR by binding to single-stranded DNA and aiding in homology recognition Like RAD51C, pathogenic SNPs in RAD51D are known to destabilize its structure and disrupt DNA binding or protein interaction, thereby increasing cancer risk. The combined importance of RAD51C and RAD51D in HRR makes them critical genomic biomarkers. Structural and functional analyses have further confirmed that mutations in these genes, including G125V and L138F in RAD51C, cause significant conformational shifts, categorizing them as deleterious and pathogenic.\u003c/p\u003e\u003cp\u003eWith advances in computational biology and genome-wide association studies (GWAS), predicting the pathogenicity of SNPs has become increasingly precise. Tools such as SIFT, PolyPhen, and PROVEAN now enable high-throughput screening of candidate mutations (de Almeida et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), narrowing the gap between genomic data and clinical relevance. From a clinical standpoint, identifying high-risk nsSNPs in RAD51C and RAD51D opens up new avenues for personalized medicine. For example, tumors harboring HRR-deficient mutations are more responsive to poly (ADP-ribose) polymerase (PARP) inhibitors, offering targeted therapeutic strategies (Murai et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Moreover, conformational alterations induced by certain SNPs may explain differential sensitivity or resistance to these therapies, informing precision oncology approaches (Luo et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study also emphasizes the significance of population-specific genomic profiling. Ethnic variations in RAD51C and RAD51D mutation frequencies can influence cancer risk and treatment outcomes, thereby necessitating regionally adapted interventions (Green et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). By integrating bioinformatics, structural modelling, docking, and dynamic simulations, this research presents a comprehensive framework for understanding the impact of deleterious SNPs in RAD51C and RAD51D. It highlights the need for experimental validation to further elucidate functional consequences and supports the future use of these insights in early detection, risk prediction, and the development of targeted therapies.\u003c/p\u003e\u003cp\u003eIn conclusion, our study affirms the central role of RAD51C and RAD51D in DNA repair and cancer susceptibility. By identifying and characterizing the most damaging nsSNPs through a robust computational pipeline, we contribute significantly to the understanding of how these genes influence tumorigenesis. These findings not only align with previous literature (Rodriguez-Lopez et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Porto et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rajasekaran et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Chun et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Greenhough et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) but also lay the groundwork for future translational research aimed at harnessing RAD51 family mutations for diagnostic and therapeutic purposes. As genomic medicine continues to evolve, integrating such structural and functional insights will be key to advancing cancer prevention and precision treatment strategies (Hortobagyi, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study underscores the pivotal roles of RAD51C and RAD51D genes in maintaining genomic integrity through homologous recombination repair and highlights their contribution to breast and ovarian cancer susceptibility beyond BRCA1/2 mutations. Using a comprehensive computational pipeline, we screened over 19,000 SNPs and identified several deleterious non-synonymous variants with potential pathogenicity, particularly within critical functional domains such as the ATP-binding and DNA recombination/repair regions. Structural modeling and molecular dynamics simulations revealed that these variants can induce significant alterations in protein conformation, stability, and protein-protein interactions. Mutations such as L219S in RAD51C and S207L in RAD51D were found to be especially disruptive, compromising interactions within the RAD51 paralog complexes. These findings not only elucidate the molecular mechanisms by which RAD51C/D variants contribute to cancer development but also identify candidate biomarkers for early detection and therapeutic targeting. The integration of sequence-based screening with structural and dynamic analyses offers a powerful approach for prioritizing functionally relevant SNPs in cancer-associated genes. Future experimental studies are essential to validate these in silico predictions and further explore their clinical utility in cancer risk assessment and precision oncology.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eDeclaration of Interest:\u003c/h2\u003e\n\u003cp\u003eAuthors declare no conflict of interest.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors have been contributed to the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMichael PC, Parmigiani G, Beattie MS, Garber JE. 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J Clin Oncol. 2020;38(5):443\u0026ndash;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1200/JCO.19.03124\u003c/span\u003e\u003cspan address=\"10.1200/JCO.19.03124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable I:\u003c/strong\u003e Deleterious SNPs in RAD51C and RDA51D genes predicted by sequence and structure based tools.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSr. No.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSr. No.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28363307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eI76T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e36.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers201523760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eT5M\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"2\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR249C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e37.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers201523760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eT5M\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"3\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR128C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e38.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers201523760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eT5M\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"4\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR249C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e39.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers201529791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL219S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"5\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR14C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e40.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers201529791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL98S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"6\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28363317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eT52A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e41.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers201529791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL219S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"7\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28363317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eT287A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e42.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers201529791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL151S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"8\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28910276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR12W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e43.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR258H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"9\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28910276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR12W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e44.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR137H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"10\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers28910276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR12W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR258H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"11\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers35151472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG162E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e46.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR23H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"12\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers35151472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG94E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e47.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"13\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers35151472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG162E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG4V\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"14\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers35151472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG41E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"15\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers137947462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR212C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG57V\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"16\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers137947462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR91C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"17\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers137947462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR144C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL138F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"18\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers137947462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR212C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL70F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"19\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL138F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"20\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG4S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers267606999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL17F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"21\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"22\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG57S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"23\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"24\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers143026267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL297P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG44A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"25\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers143026267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL62P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers374196453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR260W\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"26\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers147241704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eG29S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers374196453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR139W\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"27\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL27V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers374196453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR260W\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"28\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL141V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers374196453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR25W\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"29\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL262V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers375451955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eE67G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"30\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eL262V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers376494695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eD141G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"31\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers184033132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eV6M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers376494695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eD141G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"32\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers200857129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR212H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers376494695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eD73G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"33\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers200857129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR91H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers376494695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eD20G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"34\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers200857129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR144H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003ers184126555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eI174T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7616%;\"\u003e\n \u003col start=\"35\"\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.6689%;\"\u003e\n \u003cp\u003ers200857129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003eR212H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2649%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26.1589%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0728%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSr. No.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSr. No.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA106T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368838910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eI105T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA180T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368838910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eI105T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA106T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368838910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eI105T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA48T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368838910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eI125T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE74G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR98Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE114G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR156Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE114G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR230Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE114G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR295Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE56G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR275Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers55942401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE38D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR275Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers80116829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA78T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR163Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers80116829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA13T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers369946779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE73K\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers137886232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR134G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers369946779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE73K\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers137886232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR76G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS162L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers137886232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR141G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS88L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers137886232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR134G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS88L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers137886232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR134G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS30L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers137886232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR94G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS88L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers138969595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT216I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS48L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers138969595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT328I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS207L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers138969595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT283I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS207L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers138969595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT328I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS227L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers138969595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT209I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371182137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eF64I\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers138969595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT348I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371182137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eF64I\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers139642328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT27K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eD110N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers139642328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT27K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers139642328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT27K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers139642328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT27K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers139642328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT27K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371812219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eL146F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers139642328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT27K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371812219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eL146F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG153R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371812219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eL166F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG265R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers371812219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eL27F\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG220R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR179C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG265R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR172C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG146R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR291C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG285R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR246C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG88R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR291C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG146R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR311C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140317560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA49V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR172C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR114C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372038369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR132C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS162P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS88P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS88P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers141690729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eN19H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS30P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers141690729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eN19H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS88P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers141690729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eN19H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS48P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers142189122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eD70N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS207P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers142189122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eD70N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS207P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers142189122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eD70N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS227P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers142387263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR108C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers374019782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA177S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers145309168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eI199N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers374019782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA119S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers145309168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eI192N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers374019782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA251S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers145309168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eI266N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers374019782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA184S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR145H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers374357106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS62L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR145H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers374357106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eS62L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR165H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers374730714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eG44D\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR26H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376472075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eL84H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR26H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA33E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR26H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA91E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers151198586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR55Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA51E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers151198586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR55Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA165E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers151198586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR55Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA98E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers151198586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR55Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA91E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers200009601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE25K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA230E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers200009601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE72K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA210E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers200009601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE65K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA210E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers200009601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eE7K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA91E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers200018296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT84A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA106T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers200018296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT84A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA180T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers200018296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eT84A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA106T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers201141245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eV152I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers28363282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eA48T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers201141245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eV132I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers199589923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eF22C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers201141245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eV132I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers199659185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR43Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers201141245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eV13I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ers199659185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eR43L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable II:\u0026nbsp;\u003c/strong\u003eUnanimous results of all tools for RAD51C and RAD51D\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"667\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 354px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSr. No.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSr. No.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR249C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG265R\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR249C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers28363317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eT287A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers35151472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG162E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers137947462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR212C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR145H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR145H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers143026267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eL297P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR275Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eL27V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR275Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eL262V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eS207L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eL262V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eS207L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers200857129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR212H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers201529791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eL219S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers267606997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR258H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eS88P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eS88P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eS88P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eS207P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eS207P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eA210E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003ers374196453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eR260W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eA210E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable III:\u003c/strong\u003e Entries after removing multiple rsIDs entries and invalid protein ID\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"601\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 273px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ersID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eR249C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eG265R\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers35151472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eG162E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers137947462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eR212C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eR145H\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eR275Q\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers143026267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eL297P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eS207L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eL262V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers200857129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eR212H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eS207P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers201529791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eL219S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eA210E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers267606997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eR258H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable IV:\u003c/strong\u003e Stability prediction and RMSD values of deleterious SNPs in RAD51C and RAD51D.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS. No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ers IDs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eI-Mutant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMuPro\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers28363311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eR249C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers35151472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eG162E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers137947462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eR212C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers142058115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers143026267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eL297P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers149331537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eL262V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers200857129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eR212H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers201529791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eL219S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers267606997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eR258H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers267606998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers370212314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eIncrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS. No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ers IDs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino acid change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eI-Mutant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMuPro\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers140285068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eG265R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers140825795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers147264215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eR145H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers368914740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eR275Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers370228071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eS207L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers371561526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers372365287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eS207P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003ers376855484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28px;\"\u003e\n \u003cp\u003eA210E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 13px;\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable V:\u003c/strong\u003e Molecular docking results of RAD51C protein with interacting proteins.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"87%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS. No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBinding energies Kcal/mol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eXRCC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eXRCC3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eRAD51C-W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1023.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1281.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-112.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eG112A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1081.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1095.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eG125S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1061.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1000.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1119.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1003.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eG125V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-995.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1242.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1103.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eG162E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1106.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1127.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1046.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eL219S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1123.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1060.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1147.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1030.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eL262V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1047.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1226.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1211.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1112.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eL297P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1033.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1079.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1200.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-960.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eR212C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1168.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1389.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1295.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1046.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eR212H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-980.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1294.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1302.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1040.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eR249C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1175.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1030.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003eR258H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1124.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1048.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1145.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-1030.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable VI:\u003c/strong\u003e Molecular docking results of RAD51D protein with interacting proteins.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"85%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS. No\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBinding energies Kcal/mol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eXRCC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAD51C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eRAD51D_WILD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1024.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1174.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1195.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eG265R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-997.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1088.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1186.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eC9S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1020.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1233.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-996\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eR145H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1042.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1099.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1178.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eR275Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-981.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1185.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1185.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eS207L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1089.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1146.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1274.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eD90N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-921.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1111.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1050.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eS207P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1047.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1190.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eA210E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1059.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e-1294.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7450048/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7450048/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreast and ovarian cancers remain among the most prevalent malignancies affecting women worldwide, with only 20% of hereditary cases explained by BRCA1/2 mutations. This highlights the importance of alternative susceptibility genes such as RAD51C and RAD51D, which play essential roles in homologous recombination repair (HRR). In this study, a comprehensive in silico analysis was conducted to identify deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in RAD51C and RAD51D that may contribute to genomic instability and increased cancer risk. A total of 19,195 SNPs were retrieved and analyzed using multiple computational tools including SIFT, PolyPhen-2, PANTHER, PROVEAN, PhD-SNP, SNP\u0026amp;GO, I-Mutant, and MUpro. Eleven high-risk nsSNPs in RAD51C and several in RAD51D were identified, primarily affecting the ATP-binding and DNA repair domains. Structural modeling, docking, and molecular dynamics simulations revealed that mutations such as R212H, L219S, and L262V in RAD51C and S207L, S207P, and A210E in RAD51D significantly alter protein stability, flexibility, and binding affinity with interaction partners like XRCC2, RAD51B, and RAD51C. These alterations may compromise DNA repair mechanisms, contributing to carcinogenesis. Our findings underscore the utility of integrated computational approaches in identifying pathogenic variants and provide a molecular basis for understanding RAD51C/D-related cancer susceptibility. This work lays the groundwork for future experimental validation and supports the application of personalized medicine in HR-deficient tumors.\u003c/p\u003e","manuscriptTitle":"Structural Perturbations and Destabilizing Mutations in RAD51C and RAD51D Reveal Mechanisms of Cancer Risk","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 12:07:56","doi":"10.21203/rs.3.rs-7450048/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0c963025-1490-427d-85b3-cc0cd6997ede","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:09:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 12:07:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7450048","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7450048","identity":"rs-7450048","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}