Immunoinformatics-driven design and in silico evaluation of a multi-epitope vaccine targeting the hemagglutinin–neuraminidase protein of Sosuga virus

Immunoinformatics-driven design and in silico evaluation of a multi-epitope vaccine targeting the hemagglutinin–neuraminidase protein of Sosuga virus | 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 Immunoinformatics-driven design and in silico evaluation of a multi-epitope vaccine targeting the hemagglutinin–neuraminidase protein of Sosuga virus Vijayabharathi Saravanan, Dharshini Jaisankar, Monisha Punniyakotti This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9694926/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 Sosuga virus (SOSV) is a zoonotic paramyxovirus that is characterized by a high mortality rate, and the lack of approved vaccines or specific antiviral treatment contributes to its high importance in terms of public health. This paper adopted an immunoinformatics-based approach to develop a multi-epitope subunit vaccine against the protein hemagglutinin-neuraminidase (HN) of SOSV. B-cell and T-cell epitopes that had the potential to be antigens, allergens, toxically active and cover a large portion of the population were identified and screened to promote safety and general immunogenic relevance. The epitopes were then put together as a chimeric construct with the aid of the appropriate linkers, with an addition of 2-defensin to boost the activation of the immune. The designed vaccine construct was further evaluated for physicochemical and structural properties. The construct exhibited strong antigenicity (VaxiJen score: 0.7163) and high solubility (0.999990), with stable structural parameters. Population coverage analysis demonstrated 99.79% global coverage, indicating broad applicability. Molecular docking revealed stable interactions with immune receptors, with binding energies of − 1120.8 (MHC-I), − 1035.5 (MHC-II), and − 1061.6 (TLR4). Normal mode analysis supported structural stability and flexibility of the complexes. Immune simulation predicted robust humoral and cellular responses, including antibody production and memory cell formation. Codon optimization indicated efficient expression potential in Escherichia coli (CAI: 0.9584; GC content: 49.85%). On the whole, the multi-epitope vaccine construct suggested is a potential vaccine against SOSV; nevertheless, it needs to be proved by experimental methods that it is immunogenic, safe, and can offer protection. Sosuga virus hemagglutinin-neuraminidase β-defensin TLR4 MHC class I MHC class II Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Sosuga virus (SOSV), a member of the Paramyxoviridae family, is an emerging zoonotic pathogen of increasing public health concern. Sporadic outbreaks in sub-Saharan Africa highlight its potential for wider transmission, particularly with increasing human–wildlife interactions. Infection is associated with severe outcomes, with mortality rates reported between 60% and 90%. Transmission primarily occurs through contact with infected animals or bodily fluids, with limited human-to-human spread also suggested. Currently, no licensed vaccines or specific antiviral therapies are available, emphasizing the necessity of effective preventive strategies [ 1 ]. A major challenge in SOSV vaccine development is the limited understanding of its immunogenic components. The hemagglutinin–neuraminidase (HN) glycoprotein plays a key role in viral attachment, entry, and immune evasion and is essential for viral replication. Its surface accessibility and conserved nature among paramyxoviruses make it a promising target for vaccine design. In addition, HN can induce both humoral and cellular immune responses, supporting its suitability as an immunogen [ 2 ]. Conventional vaccine development approaches are time-consuming and resource-intensive, particularly for emerging pathogens. In contrast, immunoinformatics enables rapid identification and optimization of immunogenic epitopes, facilitating the rational design of multi-epitope vaccines with improved antigenicity and safety profiles [ 3 ]. In this study, an immunoinformatics-based methodology was utilized to create and assess a multi-epitope subunit vaccination targeting the HN protein of SOSV. The workflow integrates epitope prediction, structural modeling, molecular docking, and immune simulation to propose a candidate vaccine for further experimental validation [ 4 ]. Materials and Methods Retrieval and Physicochemical Characterization of HN Protein The amino acid sequence of the Sosuga virus hemagglutinin-neuraminidase (HN) protein (UniProt ID: W5SB61) was downloaded on UniProt and was chosen as the target antigen because it is involved in viral entry and immune recognition. TMHmm v2.0 was used to analyze transmembrane topology. To reduce possible cross-reactivity, sequence specificity was confirmed with BLASTp against the Homo sapiens proteome. ExPASy ProtParam tool was used to calculate physicochemical properties, such as molecular weight, isoelectric point (pI), instability index, aliphatic index, and GRAVY [ 5 ]. PDBsum was used in predicting the secondary structure. Prediction of antigenicity, allergenicity and toxicity were done using VaxiJen v2.0 (threshold: 0.4), AllerTOP v2.0, and ToxinPred respectively, and solubility using PepCalc. Prediction of B-Cell and T-Cell Epitopes Predicted epitopes in linear B-cells were done using the BepiPred-2.0 (IEDB) and epitopes with a score exceeding the default score were selected. The IEDB resource of MHC class I and II alleles was used to identify T-cell epitopes. In the case of MHC class I, NetMHCpan EL 4.1 was employed with 9-mer peptides, whereas epitopes of MHC class II were chosen depending on the binding affinity and percentile rank [ 6 , 7 ]. Population Coverage Analysis The IEDB population coverage tool was used to determine population coverage of the selected epitopes with global data set, taking into consideration both MHC class I and II alleles. The main outputs were population coverage (percent), average epitope hits and PC90 values [ 8 ]. Screening of Epitopes Selected epitopes were screened for antigenicity, allergenicity, and toxicity using VaxiJen v2.0 (> 0.4), AllerTOP v2.0, and ToxinPred, respectively. Only epitopes meeting all criteria were retained [ 9 – 11 ]. Multi-Epitope Vaccine Construction Appropriate linkers were used to assemble selected epitopes, and β-defensin 1 (UniProt ID: P60022) was included as an N-terminal adjuvant. The adjuvant, AAY with CTL epitopes and GPGPG with HTL epitopes were linked using EAAAK, whereas the B-cell epitopes were linked using appropriate linkers [ 12 ]. Structural Modeling, Refinement, and Validation Secondary and tertiary structures were predicted using PDBsum and I-TASSER, respectively. The best model (based on C-score) was refined using GalaxyRefine and validated through Ramachandran plot analysis [ 13 ]. Molecular Docking and Dynamics Simulation Molecular docking was performed using ClusPro to evaluate interactions with immune receptors, including TLR4. Structural stability and flexibility were assessed using iMODS [ 14 ]. Codon Optimization and In Silico Cloning The sequence of the vaccine was optimized to be expressed in Escherichia coli (K12) with JCat and inserted in silico into the pET-28a(+) expression vector with Eco53kI and BstZ17I sites. SnapGene was used to validate cloning [ 15 ]. Immune Simulation Immune responses were simulated using C-ImmSim to evaluate cytokine production, antigen clearance, and memory cell generation under default conditions. Results Physicochemical Characterization of Sosuga Virus Hemagglutinin-Neuraminidase Protein Transmembrane analysis of the HN protein using TMHMM v2.0 identified a single helix spanning residues 10–55, with the remaining regions exposed, supporting its suitability for epitope prediction (Fig. 1 ). This protein had an antigenicity score of 0.4678 (VaxiJen v2.0). It comprises 582 amino acids and a molecular weight of 64,738.41 Da and theoretical pI of 7.75. The instability index (38.14) is a sign of stability whereas the aliphatic index (90.69) is an indicator of thermostability. The GRAVY value (-0.110) indicates hydrophilic nature profile. It had an estimated half-life of about 30 hours and its composition is confirmed by the molecular formula (C₂₈₆₈H₄₅₅₆N₇₆₂O₈₆₉S₃₅) [ 16 ]. B-Cell Epitope Prediction Linear B-cell epitopes of the HN protein were identified using the BepiPred-2.0 tool with a threshold value of 0.5. A total of 18 potential epitopes were detected across the protein sequence (Fig. 2 ). The predicted epitopes showed score values ranging from 0.182 to 0.670, with an average of 0.475, indicating variability in antigenic potential across different regions. Further filtering based on antigenicity and allergenicity led to the selection of two epitopes with favorable immunological characteristics, both predicted to be non-allergenic. [ 17 , 18 ] Comprehensive details of these selected epitopes, including their positions, lengths, and antigenicity scores, are presented in Table 1 . Table 1 Predicted B-cell epitopes with antigenicity and allergenicity profiles No Start End Length Epitope sequence Antigenicity Allergenicity 1 60 86 27 VKSECSNRDHVTEIINLQQKELSLMNN 0.8853 Non-allergen 2 440 470 31 RVSKNSMKVRESVRLNITSTTRPGVEGCNIN 0.6957 Non-allergen T-cell epitope mapping MHC Class I Epitope Prediction MHC class I epitopes of the HN protein were predicted using the IEDB 2.22 method with Homo sapiens HLA alleles. A total of 137 candidate epitopes were identified, from which the top 1% with the highest binding affinity were selected. After screening for antigenicity, allergenicity, toxicity, and solubility, 14 epitopes were retained (Table 2 ). Most exhibited percentile ranks < 0.5 and antigenicity scores ranging from 0.4300 to 1.7288. Notably, epitopes such as NLQQKELSL, LQQKELSLM, and RLNITSTTR showed strong binding and immunogenic potential [ 19 , 20 ]. Table 2 MHC CLASS 1 epitopes Allele Start End Length Peptide Antigenicity Score Percentile Rank HLA-A*32:01 158 166 9 KMLGKNITF 0.6149 0.9401 0.01 HLA-A*30:01 213 222 10 KVRESVRLNI 0.6638 0.4315 0.21 HLA-B*15:01 40 48 9 LQQKELSLM 1.6228 0.6358 0.19 HLA-A*31:01 159 167 9 MLGKNITFR 0.5443 0.4570 0.43 HLA-B*40:01 129 137 9 NETQDYETI 0.4300 0.3586 0.42 HLA-B*08:01 39 47 9 NLQQKELSL 1.7288 0.9284 0.01 HLA-A*33:01 210 219 10 NSMKVRESVR 0.4904 0.2849 0.46 HLA-A*31:01 219 227 9 RLNITSTTR 1.6984 0.7975 0.06 HLA-A*31:01 206 215 10 RVSKNSMKVR 0.5155 0.5387 0.31 HLA-A*32:01 157 166 10 SKMLGKNITF 0.6212 0.2433 0.32 HLA-A*31:01 211 219 9 SMKVRESVR 1.0004 0.4439 0.45 HLA-B*08:01 211 220 10 SMKVRESVRL 1.0594 0.3083 0.33 HLA-A*31:01 207 215 9 VSKNSMKVR 0.6147 0.5387 0.31 HLA-B*07:02 203 212 10 WPYRVSKNSM 0.6274 0.7402 0.11 MHC Class II Epitope Prediction MHC class II prediction identified 152 candidate epitopes based on IEDB criteria (percentile rank ≤ 10.0 and IC₅₀ < 1000 nM). Screening for antigenicity and allergenicity resulted in 25 selected epitopes with favorable binding properties (Table 3 ) [ 21 , 22 ]. Table 3 Selected MHC Class II epitopes of SOSV HN protein based on antigenicity and binding affinity. Allele Start End Length Core Peptide Peptide Antigenicity Score Rank HLA-DRB1*12:01 32 46 15 IINLQQKEL DHVTEIINLQQKELS 1.0544 0.7558 0.31 HLA-DRB1*12:01 33 47 15 IINLQQKEL HVTEIINLQQKELSL 1.4036 0.7692 0.26 HLA-DRB1*04:05 235 249 15 IRKALSPKE INVIIRKALSPKESN 0.5071 0.6221 1.90 HLA-DRB1*15:01 209 223 15 MKVRESVRL KNSMKVRESVRLNIT 0.9102 0.3565 3.90 HLA-DRB3*02:02 213 227 15 VRLNITSTT KVRESVRLNITSTTR 1.1509 0.3571 1.50 HLA-DRB1*15:01 40 54 15 LSLMNNKSA LQQKELSLMNNKSAV 1.2790 0.3125 4.70 HLA-DRB1*04:01 30 44 15 VTEIINLQQ NRDHVTEIINLQQKE 0.9373 0.5027 3.00 HLA-DPA1*02:01/DPB1*14:01 212 226 15 RESVRLNIT MKVRESVRLNITSTT 1.1656 0.0762 5.40 HLA-DPA1*01:03/DPB1*04:01 145 159 15 ISDNRFSEA PVGISDNRFSEASKM 1.1143 0.1461 2.00 HLA-DRB3*02:02 42 56 15 LMNNKSAVC QKELSLMNNKSAVCR 0.5395 0.2640 2.20 HLA-DRB1*15:01 41 55 15 LSLMNNKSA QQKELSLMNNKSAVC 1.7260 0.2381 6.50 HLA-DRB1*08:02 240 254 15 LSPKESNSD RKALSPKESNSDSIA 0.5662 0.2402 8.50 HLA-DRB1*15:01 208 222 15 MKVRESVRL SKNSMKVRESVRLNI 0.7298 0.3073 4.80 HLA-DPA1*02:01/DPB1*14:01 211 225 15 RESVRLNIT SMKVRESVRLNITST 1.2603 0.0773 5.30 HLA-DRB5*01:01 201 215 15 YRVSKNSMK SWWPYRVSKNSMKVR 0.9142 0.5825 0.64 HLA-DRB1*12:01 35 49 15 IINLQQKEL TEIINLQQKELSLMN 1.3609 0.5548 1.30 HLA-DPA1*01:03/DPB1*02:01 146 160 15 ISDNRFSEA VGISDNRFSEASKML 0.9434 0.1115 7.10 HLA-DRB1*12:01 34 48 15 IINLQQKEL VTEIINLQQKELSLM 1.3023 0.7455 0.32 HLA-DRB5*01:01 203 217 15 YRVSKNSMK WPYRVSKNSMKVRES 0.7876 0.5534 0.77 HLA-DRB5*01:01 202 216 15 YRVSKNSMK WWPYRVSKNSMKVRE 0.8475 0.6657 0.39 Population Coverage Analysis Population coverage analysis using the IEDB tool demonstrated a global coverage of 99.79%, indicating broad applicability of the selected MHC class I and II epitopes (Table 4 ). The average epitope hit per individual was 7.21, suggesting multiple epitope–HLA interactions, while the PC90 value of 4.15 indicates that at least 90% of the population is predicted to recognize a minimum of four epitope–HLA combinations. These results support the potential effectiveness of the proposed vaccine construct across diverse populations [ 23 ]. Table 4 Global population coverage analysis of the selected MHC class I and II epitopes, indicating projected population coverage (%), average epitope hits per individual, and PC90 values, as predicted using the IEDB population coverage tool. Population MHC Class Coverage (%) Average Hit PC90 World Combined 99.79 7.21 4.15 Table 5 Hydrogen bond interactions between MHC-I (Chain D) and vaccine construct (Chain G) No. MHC-I residue Position Vaccine residue Position 1 ARG 108 ASN 682 2 ARG 108 LYS 681 3 ARG 108 ASN 682 4 ARG 157 SER 680 5 GLU 161 SER 680 6 GLU 166 ARG 785 7 ARG 169 ASN 682 8 ARG 169 SER 683 9 GLU 173 LYS 783 Table 6 Salt bridge interactions between MHC-I (Chain D) and vaccine construct (Chain G) No. MHC-I residue Position Vaccine residue Position 1 ARG 169 GLU 786 2 GLU 173 LYS 725 3 GLU 173 LYS 783 Table 7 Hydrogen bond interactions between MHC-II (Chain B) and vaccine construct (Chain C) S. No Residue (MHC-II) Position Residue (Vaccine) Position 1 ARG 71 GLU 786 2 HIS 81 VAL 679 3 GLY 84 TYR 677 4 SER 88 PRO 389 5 ARG 93 SER 421 6 GLU 96 ARG 423 7 SER 179 ARG 435 8 THR 181 GLY 430 Table 8 Salt bridges between Chain B (MHC-II) and Chain C (Vaccine) of the MHC-II vaccine complex. S. No Residue (MHC-II) Position Residue (Vaccine) Position 1 ARG 71 GLU 786 2 GLU 96 ARG 423 Table 9 Hydrogen bond interactions between TLR4 (Chain A) and vaccine construct (Chain B) S. No Residue (TR4) Position Residue (Vaccine) Position 1 ARG 494 ASP 85 2 ARG 494 SER 109 3 HIS 496 TYR 83 4 ARG 522 TYR 83 5 ASN 524 GLN 82 6 THR 526 ARG 80 7 SER 542 ILE 37 8 SER 542 GLU 59 9 GLU 543 ARG 80 10 GLU 742 LYS 70 11 HIS 811 GLN 93 Table 10 Salt bridge interactions between TLR4 (Chain A) and vaccine construct (Chain B) S. No Residue (TR4) Position Residue (Vaccine) Position 1 ARG 494 ASP 85 2 HIS 496 ASP 85 3 GLU 543 ARG 80 4 ASP 717 LYS 90 5 GLU 742 LYS 70 Multi-Epitope Vaccine Construction The vaccine design was developed using multi-epitope fusion, incorporating a total of 41 epitopes: 2 B-cell epitopes, 14 MHC class I epitopes, and 25 MHC class II epitopes. The adjuvant was included at the N-terminal end of β-defensin to enhance immunogenicity. An EAAAK linker was employed to conjugate the adjuvant with the epitope sequence to maintain structural integrity and functional separation. Cytotoxic T-lymphocyte (CTL) epitopes were connected using AAY linkers to facilitate proteasomal processing, while helper T-lymphocyte (HTL) epitopes were joined using GPGPG linkers to ensure effective antigen presentation. KK linkers were utilized to integrate B-cell epitopes to preserve structural flexibility [ 24 ]. Additionally, a 6×His tag was included at the C-terminal end to enable purification and detection of the recombinant protein. The resulting construct represents a rationally designed chimeric sequence optimized for immunogenicity and structural stability (Fig. 3 ). Antigenicity, Allergenicity, Toxicity Evaluation. VaxiJen v2.0 was used to determine the antigenicity potential of the designed vaccine construct and the value of 0.7163 was obtained, which is above the threshold and indicates high antigenicity. Prediction of allergenicity with AllerTOP v2.0 showed the construct to be non-allergenic, regardless of the adjuvant. In addition, toxicity assessment using ToxinPred indicated that the construct is non-toxic, supporting its suitability for further development [ 25 ]. Physicochemical Properties and Solubility Analysis ExPASy ProtParam server was used to examine physicochemical properties of the vaccine construct. The construct is a combination of 813 amino acid residues and has an approximate molecular weight of 88,024.13 Da. The theoretical isoelectric point (pI) was estimated at 10.11, which indicated that it was a basic protein nature. The instability index was calculated as 34.70, which makes the construct stable. The index of aliphatic is 72.64, which is a moderate thermostability, and the GRAVY equals − 0.569, which is a hydrophilic profile [ 26 ]. Solubility prediction using the SOLpro server yielded a high probability score of 0.999990, suggesting that the construct is likely to be efficiently expressed and purified in microbial systems. Secondary Structure Analysis Secondary structure prediction of the multi-epitope vaccine construct was performed using the PDBsum server (Fig. 4 ). The analysis revealed a structurally diverse composition, including 24 α-helices, 18 β-strands, and 7 β-sheets. Additionally, 7 β-hairpins, 97 β-turns, and 26 γ-turns were identified. A total of 28 helix–helix interactions, along with one disulfide bond, were observed, indicating structural stability and appropriate folding of the construct. The dominance of α-helices and β-structures suggests a stable conformation that supports epitope integrity. Tertiary Structure Modeling and Refinement The three-dimensional structure of the vaccine construct was predicted using I-TASSER, generating five models ranked by C-score (− 5 to 2). Model 1, with the highest C-score of − 1.87, was selected for further analysis (Fig. 5 a). It showed a TM-score of 0.43 ± 0.15 and an RMSD of 13.04 ± 4.2 Å, indicating moderate accuracy [ 27 ]. The model was refined using GalaxyRefine, resulting in improved structural quality. The refined structure exhibited a GDT-HA score of 0.8927, an RMSD of 0.557 Å, and a MolProbity score of 2.521, along with a reduced clash score (18.6) and fewer poor rotamers (1.2%). Additionally, 74.2% of residues were located in favored regions of the Ramachandran plot, compared to 58.8% in the initial model, indicating improved stereochemical quality and stability (Fig. 5 b). Tertiary Structure Validation The refined tertiary structure (Model 1) was evaluated using PROCHECK and ProSA-web to determine its stereochemical quality and structural reliability. Ramachandran plot analysis showed that 74.2% of residues were located within the most favored regions. Although this value is slightly lower than that typically observed for highly resolved protein structures, it suggests an acceptable level of stereochemical quality (Fig. 5 c). Therefore, while further refinement may enhance structural accuracy, the current model provides a reasonable framework for subsequent computational analyses, including docking and interaction studies. When the ProSA-web server was used to validate the structure it gave a Z-score of -4.18 which is in the range of experimentally determined proteins of similar size hence justifying the reliability of the refined structure (Fig. 5 d). Molecular Docking Analysis Molecular docking analysis demonstrated stable interactions between the multi-epitope vaccine construct and key immune receptors, including MHC class I, MHC class II, and Toll-like receptor 4 (TLR4), as illustrated in Fig. 6 . The top-ranked complexes exhibited strong binding affinities, with the lowest energy scores of − 1120.8, − 1035.5, and − 1061.6 for MHC class I, MHC class II, and TLR4, respectively. The interactions involved receptor and vaccine chains forming stable complexes across all systems. Interaction analysis revealed the formation of multiple hydrogen bonds, salt bridges, and non-bonded contacts, indicating favorable binding and structural stability. Key residues contributing to binding included ARG108, GLU161, ARG169, and GLU173 (MHC class I); ARG71, GLU96, SER179, and THR181 (MHC class II); and ARG494, HIS496, ASN524, GLU543, and GLU742 (TLR4) [ 28 , 29 ]. Detailed interaction profiles are provided in Supplementary Tables 5–10. Overall, these findings suggest a strong binding potential for the vaccine construct with immune receptors, although experimental validation is required to confirm biological activity [ 30 ]. Molecular Dynamics Simulation The stability and flexibility of the vaccine construct in the presence of MHC class I, MHC class II, and Toll-like receptor 4 (TLR4) was tested by molecular dynamics simulation and normal mode analysis (NMA). Deformability analysis indicated limited structural fluctuations across all complexes, suggesting overall stability (Figures. 9a–c). The calculated eigenvalues (1.519198 × 10⁻⁶, 3.967976 × 10⁻⁶, and 6.638750 × 10⁻⁶) reflect an appropriate balance between rigidity and flexibility for the MHC class I, MHC class II, and TLR4 complexes, respectively [ 31 ]. Additional analyses, including variance, B-factor, covariance matrix, and elastic network modeling, demonstrated consistent atomic mobility patterns and coordinated dynamic behavior across all systems, supporting the structural integrity of the vaccine–receptor complexes (Figures. 9d–l). Overall, these results indicate that the complexes maintain stability while allowing necessary conformational flexibility. Codon Optimization and In Silico Cloning Java Codon Adaptation Tool (JCat) was used to optimize the nucleotide sequence of the construct of the designed multi-epitope vaccine to be expressed in Escherichia coli. The streamlined sequence had a codon adaptation index (CAI) of 0.9584 and a GC content of 49.85% which is considered to be conducive to effective translation and a consistent expression of the genes in E. coli. The optimal gene sequence of 2443 base pairs was then cloned in vitro into pET-28a(+) expression construct with Eco53kI and PshAI restriction sites. The overall size of the resulting recombinant plasmid was 6024 bp. The construct was visualized with SnapGene to verify the correct insertion of the vaccine gene into the multiple cloning site (MCS), which is located between the T7 promoter and T7 terminator to enable the vaccine gene to be expressed upon the induction by IPTG (Fig. 8 ). The construct has 6XHis tags as well to enable purification of the protein expressed. In addition, the vector contains a kanamycin resistance gene (KanR) for selection, along with essential replication elements such as ori, f1 ori, and rop, ensuring plasmid maintenance and stability. The presence of multiple restriction sites within the MCS further provides flexibility for alternative cloning strategies [ 32 ]. Immune Simulation The immunogenic potential of the designed multi-epitope vaccine construct was evaluated using the C-ImmSim server to simulate host immune responses. The antibody profile (Fig. 9 c) indicated a strong primary immune response, marked by a rapid increase in combined IgM and IgG levels, followed by sustained elevations in IgM and IgG1 + IgG2 titers, suggesting effective humoral immunity. A notable reduction in antigen levels was observed after vaccination, indicating efficient antigen clearance [ 34 ]. Analysis of B-cell dynamics (Fig. 9 b) demonstrated a significant increase in total B-cell populations, along with the generation of memory B-cells and evidence of immunoglobulin class switching (IgM, IgG1, and IgG2). These findings suggest the development of long-term immune memory and affinity maturation. The helper T-cell (TH) response (Fig. 9 a) showed a marked expansion in total TH cell populations, including memory TH cells, indicating effective activation of cellular immune responses. Cytokine profiling (Fig. 9 d) revealed elevated levels of IFN-γ and IL-2, along with moderate increases in IL-12 and TNF-α, suggesting a Th1-biased immune response, which plays a key role in antiviral immunity. Overall, the vaccine construct induces a robust, sustained, and multi-component immune response involving both humoral and cellular mechanisms [ 35 ]. Discussion The present study outlines an immunoinformatics-driven approach for the rational design of a multi-epitope subunit vaccine targeting the hemagglutinin–neuraminidase (HN) glycoprotein of Sosuga virus (SOSV), an emerging zoonotic pathogen of public health concern. The selection of HN as the target antigen is supported by its role in viral attachment, entry, and interaction with host immune mechanisms, as well as its surface exposure, making it suitable for epitope-based vaccine design [ 36 ]. A systematic screening strategy enabled the identification of B-cell and T-cell epitopes with favorable antigenicity, non-allergenicity, and non-toxic profiles. The inclusion of both MHC class I and class II epitopes supports activation of cytotoxic and helper T-cell responses, while B-cell epitopes contribute to humoral immunity. The integration of 41 epitopes resulted in high global population coverage (99.79%), although the structural complexity of such a construct requires further validation. The incorporation of β-defensin as an adjuvant, linked via an EAAAK spacer, was intended to enhance immunogenicity through activation of innate immune pathways. The use of AAY and GPGPG linkers facilitates antigen processing and presentation while maintaining structural integrity. Physicochemical analysis indicated that the construct is stable, hydrophilic, and suitable for recombinant expression, supported by favorable solubility predictions. Structural modeling provided a preliminary three-dimensional framework of the vaccine construct. Although validation metrics, including Ramachandran analysis, indicate moderate stereochemical quality, the model is adequate for initial computational studies. Further refinement and experimental validation are required to confirm structural accuracy. Molecular docking demonstrated favorable interactions with key immune receptors, including MHC class I, MHC class II, and Toll-like receptor 4 (TLR4), suggesting potential for antigen presentation and receptor engagement. However, these results represent theoretical predictions and do not confirm biological activity or immune activation [ 37 ]. Normal mode analysis supported the stability and flexibility of the vaccine–receptor complexes, indicating their ability to maintain structural integrity while allowing necessary conformational changes, although this approach simplifies real biological conditions. Immune simulation suggested that the vaccine construct may induce both humoral and cellular immune responses, including increased antibody levels, memory cell formation, and cytokine production. Elevated IFN-γ and IL-2 levels indicate a Th1-biased response associated with antiviral immunity. However, these findings require experimental validation [ 38 ]. The optimization of codons and in silico cloning were used to verify that the gene could be expressed in Escherichia coli and production could be done on a large scale. Despite these promising findings, the study is limited by its reliance on computational predictions. Factors such as protein folding, post-translational modifications, immune variability, and long-term safety remain to be evaluated experimentally. In conclusion, this study presents a rational framework for the design of a multi-epitope vaccine against SOSV. The proposed construct shows promising in silico characteristics; however, comprehensive in vitro and in vivo studies are essential to confirm its safety, immunogenicity, and efficacy. Conclusion In this study, a multi-epitope subunit vaccine targeting the hemagglutinin–neuraminidase (HN) protein of Sosuga virus was designed using an integrated immunoinformatics approach. The selected epitopes exhibited favorable antigenicity, non-allergenicity, and non-toxic characteristics and were assembled using appropriate linkers along with a β-defensin adjuvant to enhance immunogenic potential. Structural modeling and validation suggested that the vaccine construct adopts a stable conformation with acceptable stereochemical properties. Molecular docking analyses indicated favorable interaction patterns with MHC class I, MHC class II, and TLR4 receptors, suggesting the potential for effective immune recognition. These observations were supported by normal mode analysis, which demonstrated both structural stability and flexibility of the docked complexes. The prediction of ability to generate humoral and cellular immune responses was based on the outcomes of immune simulation. Moreover, codon optimization and in silico cloning tests validated the possibility of effective expression in Escherichia coli. Generally, the suggested multi-epitope vaccine construct is a promising vaccine against Sosuga virus. Nevertheless, in vitro and in vivo experiments should be carried out to establish the safety of its application, immunogenicity, and protective efficacy. Abbreviations SOSV Sosuga virus HN Hemagglutinin–neuraminidase MHC I–Major Histocompatibility Complex Class I MHC II–Major Histocompatibility Complex Class II TLR4 Toll–like receptor 4 CTL Cytotoxic T lymphocyte HTL Helper T lymphocyte IEDB Immune Epitope Database Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and material All data generated or analyzed during this study are included in this published article and its supplementary information files. Competing interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this work. Authors' contributions Vijayabharathi Saravanan (VS) conceptualized and designed the study, performed data analysis, and drafted the manuscript. Dharshini Jaisankar (DJ) contributed to data interpretation and manuscript revision. Monisha Punniyakotti (MP) assisted in analysis and critically reviewed the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. Declaration of generative AI and AI-assisted technologies in the manuscript preparation process During the preparation of this work, the authors used Grammarly to assist with language editing, formatting, and improvement of manuscript clarity. 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Infect Dis Model 9:763–774. https://doi.org/10.1016/j.idm.2024.04.005 Mahapatra SR, Dey J, Raj TK, Misra N, Suar M (2023) Designing a Next-Generation Multiepitope-Based Vaccine against Staphylococcus aureus Using Reverse Vaccinology Approaches. Pathogens 12:376. https://doi.org/10.3390/pathogens12030376 Chatterjee R, Mahapatra SR, Dey J, Raj Takur K, Raina V, Misra N, Suar M (2023) An immunoinformatics and structural vaccinology study to design a multi-epitope vaccine against Staphylococcus aureus infection. J Mol Recognit 36. https://doi.org/10.1002/jmr.3007 Das Mitra S, Kumar B, Rajegowda S, Bandopadhyay S, Karunakar P, Pais R (2024) Reverse vaccinology & immunoinformatics approach to design a multiepitope vaccine (CV3Ag-antiMRSA) against methicillin resistant Staphylococcus aureus (MRSA) – a pathogen affecting both human and animal health. J Biomol Struct Dyn 42:11792–11811. https://doi.org/10.1080/07391102.2023.2265471 Li L, Chen Y, Wu S, Wu C, Xie J, Shah A, Xie X, Tan J, Qin Y, Zeng Y, Jan AU, Yang T, Ullah S (2026) Immunoinformatics based designing of a broad-spectrum multi-epitope vaccine against co-infection of human metapneumovirus, respiratory syncytial virus, and influenza A virus. Sci Rep 16:10244. https://doi.org/10.1038/s41598-026-40812-z Allemailem KS, Alrumaihi F, Almatroudi A (2025) Immunoinformatics-based design of a next generation multi-epitope vaccine candidate against Shigella boydii using a hierarchical subtractive proteomics approach. Sci Rep 16:3359. https://doi.org/10.1038/s41598-025-33252-8 Sharma A, Das, Magdaleno JSL, Singh H, Orduz AFC, Cavallo L, Chawla M (2025) Immunoinformatics-driven design of a multi-epitope vaccine targeting neonatal rotavirus with focus on outer capsid proteins VP4 and VP7 and non structural proteins NSP2 and NSP5. Sci Rep 15:11879. https://doi.org/10.1038/s41598-025-95256-8 Pajand O, Larimi AG, Ahmad S, Mahooti M, Mohammadi G, Sanami S (2026) Computational design of a novel multi-epitope vaccine candidate against group A rotavirus. Virol J 23:72. https://doi.org/10.1186/s12985-026-03099-0 Sarvmeili J, Baghban Kohnehrouz B, Gholizadeh A, Shanehbandi D, Ofoghi H (2024) Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer. Sci Rep 14:10297. https://doi.org/10.1038/s41598-024-61025-2 Sethi G, Lakra AK, Nirmal K, Hwang JH (2025) In silico design of a multi-epitope vaccine against Cryptosporidium parvum using structural and immunoinformatics approaches. PLoS ONE 20:e0334754. https://doi.org/10.1371/journal.pone.0334754 Pang F, Long Q, Liang S (2024) Designing a multi-epitope subunit vaccine against Orf virus using molecular docking and molecular dynamics. Virulence 15. https://doi.org/10.1080/21505594.2024.2398171 Kanwal A, Shah M, Khan MU, Latif M, Anum H, Younas S, Aljasham AT, Ojha SC (2025) Computational development of multi-epitope vaccine to induce adaptive immunity against multi-drug resistant Prevotella intermedia. BMC Infect Dis. https://doi.org/10.1186/s12879-025-12105-9 . 25: Sami MRS, Rani NA, Elahi MME, Hossain MS, Al Mueid MA, Rahim Z, Patil RB, Moin AT, Bithi IJ, Nahar S, Konika IJ, Roy S, Preya JA, Ahmed J (2024) An immunoinformatics and extensive molecular dynamics study to develop a polyvalent multi-epitope vaccine against cryptococcosis. PLoS ONE 19:e0315105. https://doi.org/10.1371/journal.pone.0315105 Kousar S, Manzoor I, Muhammad S, Almohaimeed HM, Hasan T, Fenibo EO, Matambo T (2026) Immunoinformatic-based design of a multi-epitope subunit vaccine against Ruminococcus torques using subtractive proteomics and molecular dynamics simulations. Sci Rep. https://doi.org/10.1038/s41598-026-45572-4 Shahab M, Alzahrani A, Duan X, Aslam M, Abida I, Mohd, Kamal M, Alam Md, Zheng G (2023) An Immunoinformatics Approach to Design Novel and Potent Multi-Epitope-Based Vaccine to Target Lumpy Skin Disease. Biomedicines 11:398. https://doi.org/10.3390/biomedicines11020398 Pahlavan Y, Yeganeh O, Asghariazar V, Karami C (2024) Multi-epitope vaccine against SARS-CoV-2 targeting the spike RBD: an immunoinformatics approach. Future Sci OA 10. https://doi.org/10.2144/fsoa-2023-0081 Pradhan SS, Balena V, Bera BC, Anand T, Khetmalis R, Madhwal A, Kandasamy S, Pavulraj S, Bernela M, Mor P, Tripathi BN, Virmani N (2025) Multiple Gene Deletion Mutants of Equine Herpesvirus 1 Exhibit Strong Protective Efficacy Against Wild Virus Challenge in a Murine Model. Vaccines (Basel) 13:45. https://doi.org/10.3390/vaccines13010045 Afshan G, Yaseen N, Ali SH, Khan AU (2025) Immunoinformatics-Based development of a Multi-Epitope vaccine candidate targeting coinfection by Klebsiella pneumoniae and Acinetobacter baumannii. BMC Infect Dis 25. https://doi.org/10.1186/s12879-025-11242-5 Tang X, Zhang W, Zhang Z (2025) Developing T Cell Epitope-Based Vaccines Against Infection: Challenging but Worthwhile. Vaccines (Basel). 13 Lu Q, Wu H, Meng J, Wang J, Wu J, Liu S, Tong J, Nie J, Huang W (2024) Multi-epitope vaccine design for hepatitis E virus based on protein ORF2 and ORF3. Front Microbiol 15. https://doi.org/10.3389/fmicb.2024.1372069 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9694926","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":639816510,"identity":"974a7c18-dc54-40f0-b966-9d4fc9f77dae","order_by":0,"name":"Vijayabharathi 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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Dharshini","middleName":"","lastName":"Jaisankar","suffix":""},{"id":639816514,"identity":"5a127837-f10d-4979-81e1-464f3803b4ba","order_by":2,"name":"Monisha Punniyakotti","email":"","orcid":"","institution":"PSG College Of Pharmacy","correspondingAuthor":false,"prefix":"","firstName":"Monisha","middleName":"","lastName":"Punniyakotti","suffix":""}],"badges":[],"createdAt":"2026-05-12 16:53:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9694926/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9694926/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109245713,"identity":"3ccb6441-665a-4b12-b89a-38441772f920","added_by":"auto","created_at":"2026-05-14 07:55:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25551,"visible":true,"origin":"","legend":"\u003cp\u003eTransmembrane helix prediction in the HN protein of SOSV by TMHMM v2.0.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/39e9ba32bfb0799becd63ea3.png"},{"id":109245727,"identity":"74aab171-94e7-42dc-bad1-67d9c032ca74","added_by":"auto","created_at":"2026-05-14 07:55:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":110704,"visible":true,"origin":"","legend":"\u003cp\u003eLinear B-cell epitope prediction of the HN protein using BepiPred-2.0.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/744b2c468117b4acc5aa7a79.png"},{"id":109245712,"identity":"78d560b8-eafc-41c1-9f4b-da3e3db415c8","added_by":"auto","created_at":"2026-05-14 07:55:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":62109,"visible":true,"origin":"","legend":"\u003cp\u003eStructural plan and amino acid sequence of the multi-epitope vaccine construct designed.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/ab8d4faf5fea55207ed6d567.png"},{"id":109245646,"identity":"785a4572-8b0b-42ea-aeb8-338422317371","added_by":"auto","created_at":"2026-05-14 07:55:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":161959,"visible":true,"origin":"","legend":"\u003cp\u003eSecondary structure representation of the multi-epitope vaccine construct generated using the PDBsum server.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/62d21fcbb8bb226cc46a7cc3.png"},{"id":109245724,"identity":"5990d59e-8a5f-451b-a5e4-a36a74c14d47","added_by":"auto","created_at":"2026-05-14 07:55:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":110423,"visible":true,"origin":"","legend":"\u003cp\u003eTertiary structure modeling and validation of the vaccine construct: (a) I-TASSER model, (b) refined structure superimposition, (c) Ramachandran plot, and (d) ProSA Z-score.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/fc33dce9315fc40980c7d56c.png"},{"id":109245647,"identity":"195c4961-ca25-44f4-bd70-5c1946432d53","added_by":"auto","created_at":"2026-05-14 07:55:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":126959,"visible":true,"origin":"","legend":"\u003cp\u003eImmunogenic interaction of the multi-epitope vaccine construct with immune receptors: (a) MHC class I-vaccine complex, (b) MHC class II-vaccine complex and (c) TLR4-vaccine complex. The receptor proteins (green) combine with the vaccine construct (red), and the complexes are stable. The major interacting residues are indicated with each complex.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/2116622c160a9bc011eda9dd.png"},{"id":109245730,"identity":"4f7af1a5-12f0-47f4-b540-b09940decdd4","added_by":"auto","created_at":"2026-05-14 07:55:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":145943,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular dynamics and normal mode analysis of the multi-epitope vaccine complexes with (a) MHC class I, (b) MHC class II, and (c) Toll-like receptor 4 (TLR4), illustrating deformability, eigenvalue, variance, B-factor, covariance, and elastic network profiles.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/4f379ce29be918ab722bc627.png"},{"id":109245746,"identity":"39c45e39-05ca-4821-b032-e3ef5bcbc9e0","added_by":"auto","created_at":"2026-05-14 07:55:43","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":90142,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Recombinant plasmid map of the pET-28a(+) vector containing the vaccine construct. (B) Schematic representation of in silico cloning and insertion of the optimized gene sequence into the expression vector [33].\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/bdd0cf5f49f3aa57f938f8b6.png"},{"id":109245648,"identity":"c9cddf95-4386-4160-b3b3-5b00fa703392","added_by":"auto","created_at":"2026-05-14 07:55:17","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":77468,"visible":true,"origin":"","legend":"\u003cp\u003eIn silico immunological simulation of the multi-epitope vaccination conducted over a 35-day duration. (a) Helper T-cell (TH) population dynamics showing expansion and memory formation. (b) B-cell population dynamics illustrating memory B-cell generation and immunoglobulin class switching. (c) Antibody response and antigen clearance (IgM, IgG1, IgG2). (d) Cytokine profile indicating immune activation and a Th1-biased response.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/c30fae17d8643f8d20d7c294.png"},{"id":109295995,"identity":"ebb954d4-459c-418a-9ef5-3dfe86b79135","added_by":"auto","created_at":"2026-05-15 08:43:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1333888,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/59a81a6f-69cc-4a80-8326-22d8d5741eae.pdf"},{"id":109245725,"identity":"376a42ca-2715-4f87-b1f0-35e863edda64","added_by":"auto","created_at":"2026-05-14 07:55:30","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":26914,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-9694926/v1/a88919a8fca6a1f594c92019.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Immunoinformatics-driven design and in silico evaluation of a multi-epitope vaccine targeting the hemagglutinin–neuraminidase protein of Sosuga virus","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSosuga virus (SOSV), a member of the \u003cem\u003eParamyxoviridae\u003c/em\u003e family, is an emerging zoonotic pathogen of increasing public health concern. Sporadic outbreaks in sub-Saharan Africa highlight its potential for wider transmission, particularly with increasing human\u0026ndash;wildlife interactions. Infection is associated with severe outcomes, with mortality rates reported between 60% and 90%. Transmission primarily occurs through contact with infected animals or bodily fluids, with limited human-to-human spread also suggested. Currently, no licensed vaccines or specific antiviral therapies are available, emphasizing the necessity of effective preventive strategies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA major challenge in SOSV vaccine development is the limited understanding of its immunogenic components. The hemagglutinin\u0026ndash;neuraminidase (HN) glycoprotein plays a key role in viral attachment, entry, and immune evasion and is essential for viral replication. Its surface accessibility and conserved nature among paramyxoviruses make it a promising target for vaccine design. In addition, HN can induce both humoral and cellular immune responses, supporting its suitability as an immunogen [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConventional vaccine development approaches are time-consuming and resource-intensive, particularly for emerging pathogens. In contrast, immunoinformatics enables rapid identification and optimization of immunogenic epitopes, facilitating the rational design of multi-epitope vaccines with improved antigenicity and safety profiles [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, an immunoinformatics-based methodology was utilized to create and assess a multi-epitope subunit vaccination targeting the HN protein of SOSV. The workflow integrates epitope prediction, structural modeling, molecular docking, and immune simulation to propose a candidate vaccine for further experimental validation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRetrieval and Physicochemical Characterization of HN Protein\u003c/h2\u003e \u003cp\u003eThe amino acid sequence of the Sosuga virus hemagglutinin-neuraminidase (HN) protein (UniProt ID: W5SB61) was downloaded on UniProt and was chosen as the target antigen because it is involved in viral entry and immune recognition. TMHmm v2.0 was used to analyze transmembrane topology. To reduce possible cross-reactivity, sequence specificity was confirmed with BLASTp against the Homo sapiens proteome. ExPASy ProtParam tool was used to calculate physicochemical properties, such as molecular weight, isoelectric point (pI), instability index, aliphatic index, and GRAVY [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePDBsum was used in predicting the secondary structure. Prediction of antigenicity, allergenicity and toxicity were done using VaxiJen v2.0 (threshold: 0.4), AllerTOP v2.0, and ToxinPred respectively, and solubility using PepCalc.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrediction of B-Cell and T-Cell Epitopes\u003c/h3\u003e\n\u003cp\u003ePredicted epitopes in linear B-cells were done using the BepiPred-2.0 (IEDB) and epitopes with a score exceeding the default score were selected. The IEDB resource of MHC class I and II alleles was used to identify T-cell epitopes. In the case of MHC class I, NetMHCpan EL 4.1 was employed with 9-mer peptides, whereas epitopes of MHC class II were chosen depending on the binding affinity and percentile rank [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003ePopulation Coverage Analysis\u003c/h3\u003e\n\u003cp\u003eThe IEDB population coverage tool was used to determine population coverage of the selected epitopes with global data set, taking into consideration both MHC class I and II alleles. The main outputs were population coverage (percent), average epitope hits and PC90 values [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eScreening of Epitopes\u003c/h3\u003e\n\u003cp\u003eSelected epitopes were screened for antigenicity, allergenicity, and toxicity using VaxiJen v2.0 (\u0026gt;\u0026thinsp;0.4), AllerTOP v2.0, and ToxinPred, respectively. Only epitopes meeting all criteria were retained [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMulti-Epitope Vaccine Construction\u003c/h3\u003e\n\u003cp\u003eAppropriate linkers were used to assemble selected epitopes, and β-defensin 1 (UniProt ID: P60022) was included as an N-terminal adjuvant. The adjuvant, AAY with CTL epitopes and GPGPG with HTL epitopes were linked using EAAAK, whereas the B-cell epitopes were linked using appropriate linkers [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStructural Modeling, Refinement, and Validation\u003c/h2\u003e \u003cp\u003eSecondary and tertiary structures were predicted using PDBsum and I-TASSER, respectively. The best model (based on C-score) was refined using GalaxyRefine and validated through Ramachandran plot analysis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMolecular Docking and Dynamics Simulation\u003c/h3\u003e\n\u003cp\u003eMolecular docking was performed using ClusPro to evaluate interactions with immune receptors, including TLR4. Structural stability and flexibility were assessed using iMODS [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eCodon Optimization and In Silico Cloning\u003c/h3\u003e\n\u003cp\u003eThe sequence of the vaccine was optimized to be expressed in Escherichia coli (K12) with JCat and inserted in silico into the pET-28a(+) expression vector with Eco53kI and BstZ17I sites. SnapGene was used to validate cloning [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eImmune Simulation\u003c/h2\u003e \u003cp\u003eImmune responses were simulated using C-ImmSim to evaluate cytokine production, antigen clearance, and memory cell generation under default conditions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePhysicochemical Characterization of Sosuga Virus Hemagglutinin-Neuraminidase Protein\u003c/h2\u003e \u003cp\u003eTransmembrane analysis of the HN protein using TMHMM v2.0 identified a single helix spanning residues 10\u0026ndash;55, with the remaining regions exposed, supporting its suitability for epitope prediction (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis protein had an antigenicity score of 0.4678 (VaxiJen v2.0). It comprises 582 amino acids and a molecular weight of 64,738.41 Da and theoretical pI of 7.75. The instability index (38.14) is a sign of stability whereas the aliphatic index (90.69) is an indicator of thermostability. The GRAVY value (-0.110) indicates hydrophilic nature profile. It had an estimated half-life of about 30 hours and its composition is confirmed by the molecular formula (C₂₈₆₈H₄₅₅₆N₇₆₂O₈₆₉S₃₅) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eB-Cell Epitope Prediction\u003c/h2\u003e \u003cp\u003eLinear B-cell epitopes of the HN protein were identified using the BepiPred-2.0 tool with a threshold value of 0.5. A total of 18 potential epitopes were detected across the protein sequence (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe predicted epitopes showed score values ranging from 0.182 to 0.670, with an average of 0.475, indicating variability in antigenic potential across different regions. Further filtering based on antigenicity and allergenicity led to the selection of two epitopes with favorable immunological characteristics, both predicted to be non-allergenic. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eComprehensive details of these selected epitopes, including their positions, lengths, and antigenicity scores, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003ePredicted B-cell epitopes with antigenicity and allergenicity profiles\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStart\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEpitope sequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAntigenicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAllergenicity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVKSECSNRDHVTEIINLQQKELSLMNN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-allergen\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRVSKNSMKVRESVRLNITSTTRPGVEGCNIN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-allergen\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eT-cell epitope mapping\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003eMHC Class I Epitope Prediction\u003c/h2\u003e \u003cp\u003eMHC class I epitopes of the HN protein were predicted using the IEDB 2.22 method with \u003cem\u003eHomo sapiens\u003c/em\u003e HLA alleles. A total of 137 candidate epitopes were identified, from which the top 1% with the highest binding affinity were selected. After screening for antigenicity, allergenicity, toxicity, and solubility, 14 epitopes were retained (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most exhibited percentile ranks\u0026thinsp;\u0026lt;\u0026thinsp;0.5 and antigenicity scores ranging from 0.4300 to 1.7288. Notably, epitopes such as NLQQKELSL, LQQKELSLM, and RLNITSTTR showed strong binding and immunogenic potential [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMHC CLASS 1 epitopes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStart\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePeptide\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAntigenicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePercentile Rank\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*32:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKMLGKNITF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*30:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKVRESVRLNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-B*15:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLQQKELSLM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.6228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.6358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*31:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMLGKNITFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-B*40:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNETQDYETI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-B*08:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNLQQKELSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.7288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*33:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSMKVRESVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*31:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRLNITSTTR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.6984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.7975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*31:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRVSKNSMKVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*32:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSKMLGKNITF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*31:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSMKVRESVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-B*08:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSMKVRESVRL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A*31:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVSKNSMKVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-B*07:02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWPYRVSKNSM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.7402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMHC Class II Epitope Prediction\u003c/h2\u003e \u003cp\u003eMHC class II prediction identified 152 candidate epitopes based on IEDB criteria (percentile rank\u0026thinsp;\u0026le;\u0026thinsp;10.0 and IC₅₀ \u0026lt; 1000 nM). Screening for antigenicity and allergenicity resulted in 25 selected epitopes with favorable binding properties (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelected MHC Class II epitopes of SOSV HN protein based on antigenicity and binding affinity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStart\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCore Peptide\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeptide\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAntigenicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*12:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIINLQQKEL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDHVTEIINLQQKELS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.0544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.7558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*12:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIINLQQKEL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHVTEIINLQQKELSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.4036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.7692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*04:05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIRKALSPKE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eINVIIRKALSPKESN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.6221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*15:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMKVRESVRL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKNSMKVRESVRLNIT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB3*02:02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVRLNITSTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKVRESVRLNITSTTR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.1509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*15:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLSLMNNKSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLQQKELSLMNNKSAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.2790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*04:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVTEIINLQQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNRDHVTEIINLQQKE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DPA1*02:01/DPB1*14:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRESVRLNIT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMKVRESVRLNITSTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.1656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DPA1*01:03/DPB1*04:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eISDNRFSEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePVGISDNRFSEASKM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.1143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB3*02:02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLMNNKSAVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQKELSLMNNKSAVCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*15:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLSLMNNKSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQQKELSLMNNKSAVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.7260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*08:02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLSPKESNSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRKALSPKESNSDSIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.2402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*15:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMKVRESVRL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSKNSMKVRESVRLNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.7298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DPA1*02:01/DPB1*14:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRESVRLNIT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSMKVRESVRLNITST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.2603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.0773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB5*01:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYRVSKNSMK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSWWPYRVSKNSMKVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*12:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIINLQQKEL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTEIINLQQKELSLMN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.3609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DPA1*01:03/DPB1*02:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eISDNRFSEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVGISDNRFSEASKML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.9434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.1115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB1*12:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIINLQQKEL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVTEIINLQQKELSLM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.3023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.7455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB5*01:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYRVSKNSMK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWPYRVSKNSMKVRES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.7876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-DRB5*01:01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYRVSKNSMK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWWPYRVSKNSMKVRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.8475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.6657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePopulation Coverage Analysis\u003c/h2\u003e \u003cp\u003ePopulation coverage analysis using the IEDB tool demonstrated a global coverage of 99.79%, indicating broad applicability of the selected MHC class I and II epitopes (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The average epitope hit per individual was 7.21, suggesting multiple epitope\u0026ndash;HLA interactions, while the PC90 value of 4.15 indicates that at least 90% of the population is predicted to recognize a minimum of four epitope\u0026ndash;HLA combinations. These results support the potential effectiveness of the proposed vaccine construct across diverse populations [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGlobal population coverage analysis of the selected MHC class I and II epitopes, indicating projected population coverage (%), average epitope hits per individual, and PC90 values, as predicted using the IEDB population coverage tool.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMHC Class\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoverage (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage Hit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePC90\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCombined\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eHydrogen\u003c/b\u003e bond interactions between MHC-I (Chain D) and vaccine construct (Chain G)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMHC-I residue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVaccine residue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eASN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLYS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eASN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eASN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e683\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLYS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eSalt\u003c/b\u003e bridge interactions between MHC-I (Chain D) and vaccine construct (Chain G)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMHC-I residue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVaccine residue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLYS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLYS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHydrogen bond interactions between MHC-II (Chain B) and vaccine construct (Chain C)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidue (MHC-II)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResidue (Vaccine)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTYR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePRO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e435\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGLY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e430\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSalt bridges between Chain B (MHC-II) and Chain C (Vaccine) of the MHC-II vaccine complex.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidue (MHC-II)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResidue (Vaccine)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eHydrogen\u003c/b\u003e bond interactions between TLR4 (Chain A) and vaccine construct (Chain B)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidue (TR4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResidue (Vaccine)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eASP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTYR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTYR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eASN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGLN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eILE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLYS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGLN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSalt bridge interactions between TLR4 (Chain A) and vaccine construct (Chain B)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidue (TR4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResidue (Vaccine)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eASP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eASP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eASP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLYS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLYS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eMulti-Epitope Vaccine Construction\u003c/h2\u003e \u003cp\u003eThe vaccine design was developed using multi-epitope fusion, incorporating a total of 41 epitopes: 2 B-cell epitopes, 14 MHC class I epitopes, and 25 MHC class II epitopes. The adjuvant was included at the N-terminal end of β-defensin to enhance immunogenicity. An EAAAK linker was employed to conjugate the adjuvant with the epitope sequence to maintain structural integrity and functional separation. Cytotoxic T-lymphocyte (CTL) epitopes were connected using AAY linkers to facilitate proteasomal processing, while helper T-lymphocyte (HTL) epitopes were joined using GPGPG linkers to ensure effective antigen presentation. KK linkers were utilized to integrate B-cell epitopes to preserve structural flexibility [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, a 6\u0026times;His tag was included at the C-terminal end to enable purification and detection of the recombinant protein. The resulting construct represents a rationally designed chimeric sequence optimized for immunogenicity and structural stability (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAntigenicity, Allergenicity, Toxicity Evaluation.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eVaxiJen v2.0 was used to determine the antigenicity potential of the designed vaccine construct and the value of 0.7163 was obtained, which is above the threshold and indicates high antigenicity. Prediction of allergenicity with AllerTOP v2.0 showed the construct to be non-allergenic, regardless of the adjuvant. In addition, toxicity assessment using ToxinPred indicated that the construct is non-toxic, supporting its suitability for further development [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003ePhysicochemical Properties and Solubility Analysis\u003c/h2\u003e \u003cp\u003eExPASy ProtParam server was used to examine physicochemical properties of the vaccine construct. The construct is a combination of 813 amino acid residues and has an approximate molecular weight of 88,024.13 Da. The theoretical isoelectric point (pI) was estimated at 10.11, which indicated that it was a basic protein nature. The instability index was calculated as 34.70, which makes the construct stable. The index of aliphatic is 72.64, which is a moderate thermostability, and the GRAVY equals\u0026thinsp;\u0026minus;\u0026thinsp;0.569, which is a hydrophilic profile [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSolubility prediction using the SOLpro server yielded a high probability score of 0.999990, suggesting that the construct is likely to be efficiently expressed and purified in microbial systems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSecondary Structure Analysis\u003c/h2\u003e \u003cp\u003eSecondary structure prediction of the multi-epitope vaccine construct was performed using the PDBsum server (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The analysis revealed a structurally diverse composition, including 24 α-helices, 18 β-strands, and 7 β-sheets. Additionally, 7 β-hairpins, 97 β-turns, and 26 γ-turns were identified.\u003c/p\u003e \u003cp\u003eA total of 28 helix\u0026ndash;helix interactions, along with one disulfide bond, were observed, indicating structural stability and appropriate folding of the construct. The dominance of α-helices and β-structures suggests a stable conformation that supports epitope integrity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eTertiary Structure Modeling and Refinement\u003c/h2\u003e \u003cp\u003eThe three-dimensional structure of the vaccine construct was predicted using I-TASSER, generating five models ranked by C-score (\u0026minus;\u0026thinsp;5 to 2). Model 1, with the highest C-score of \u0026minus;\u0026thinsp;1.87, was selected for further analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). It showed a TM-score of 0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 and an RMSD of 13.04\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 \u0026Aring;, indicating moderate accuracy [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe model was refined using GalaxyRefine, resulting in improved structural quality. The refined structure exhibited a GDT-HA score of 0.8927, an RMSD of 0.557 \u0026Aring;, and a MolProbity score of 2.521, along with a reduced clash score (18.6) and fewer poor rotamers (1.2%). Additionally, 74.2% of residues were located in favored regions of the Ramachandran plot, compared to 58.8% in the initial model, indicating improved stereochemical quality and stability (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eTertiary Structure Validation\u003c/h2\u003e \u003cp\u003eThe refined tertiary structure (Model 1) was evaluated using PROCHECK and ProSA-web to determine its stereochemical quality and structural reliability. Ramachandran plot analysis showed that 74.2% of residues were located within the most favored regions. Although this value is slightly lower than that typically observed for highly resolved protein structures, it suggests an acceptable level of stereochemical quality (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eTherefore, while further refinement may enhance structural accuracy, the current model provides a reasonable framework for subsequent computational analyses, including docking and interaction studies. When the ProSA-web server was used to validate the structure it gave a Z-score of -4.18 which is in the range of experimentally determined proteins of similar size hence justifying the reliability of the refined structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eMolecular Docking Analysis\u003c/h2\u003e \u003cp\u003eMolecular docking analysis demonstrated stable interactions between the multi-epitope vaccine construct and key immune receptors, including MHC class I, MHC class II, and Toll-like receptor 4 (TLR4), as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe top-ranked complexes exhibited strong binding affinities, with the lowest energy scores of \u0026minus;\u0026thinsp;1120.8, \u0026minus;\u0026thinsp;1035.5, and \u0026minus;\u0026thinsp;1061.6 for MHC class I, MHC class II, and TLR4, respectively. The interactions involved receptor and vaccine chains forming stable complexes across all systems.\u003c/p\u003e \u003cp\u003eInteraction analysis revealed the formation of multiple hydrogen bonds, salt bridges, and non-bonded contacts, indicating favorable binding and structural stability. Key residues contributing to binding included ARG108, GLU161, ARG169, and GLU173 (MHC class I); ARG71, GLU96, SER179, and THR181 (MHC class II); and ARG494, HIS496, ASN524, GLU543, and GLU742 (TLR4) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDetailed interaction profiles are provided in Supplementary Tables\u0026nbsp;5\u0026ndash;10. Overall, these findings suggest a strong binding potential for the vaccine construct with immune receptors, although experimental validation is required to confirm biological activity [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eMolecular Dynamics Simulation\u003c/h2\u003e \u003cp\u003eThe stability and flexibility of the vaccine construct in the presence of MHC class I, MHC class II, and Toll-like receptor 4 (TLR4) was tested by molecular dynamics simulation and normal mode analysis (NMA). Deformability analysis indicated limited structural fluctuations across all complexes, suggesting overall stability (Figures. 9a\u0026ndash;c). The calculated eigenvalues (1.519198 \u0026times; 10⁻⁶, 3.967976 \u0026times; 10⁻⁶, and 6.638750 \u0026times; 10⁻⁶) reflect an appropriate balance between rigidity and flexibility for the MHC class I, MHC class II, and TLR4 complexes, respectively [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditional analyses, including variance, B-factor, covariance matrix, and elastic network modeling, demonstrated consistent atomic mobility patterns and coordinated dynamic behavior across all systems, supporting the structural integrity of the vaccine\u0026ndash;receptor complexes (Figures. 9d\u0026ndash;l). Overall, these results indicate that the complexes maintain stability while allowing necessary conformational flexibility.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eCodon Optimization and In Silico Cloning\u003c/h2\u003e \u003cp\u003eJava Codon Adaptation Tool (JCat) was used to optimize the nucleotide sequence of the construct of the designed multi-epitope vaccine to be expressed in Escherichia coli. The streamlined sequence had a codon adaptation index (CAI) of 0.9584 and a GC content of 49.85% which is considered to be conducive to effective translation and a consistent expression of the genes in E. coli. The optimal gene sequence of 2443 base pairs was then cloned in vitro into pET-28a(+) expression construct with Eco53kI and PshAI restriction sites. The overall size of the resulting recombinant plasmid was 6024 bp. The construct was visualized with SnapGene to verify the correct insertion of the vaccine gene into the multiple cloning site (MCS), which is located between the T7 promoter and T7 terminator to enable the vaccine gene to be expressed upon the induction by IPTG (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The construct has 6XHis tags as well to enable purification of the protein expressed.\u003c/p\u003e \u003cp\u003eIn addition, the vector contains a kanamycin resistance gene (KanR) for selection, along with essential replication elements such as ori, f1 ori, and rop, ensuring plasmid maintenance and stability. The presence of multiple restriction sites within the MCS further provides flexibility for alternative cloning strategies [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eImmune Simulation\u003c/h2\u003e \u003cp\u003eThe immunogenic potential of the designed multi-epitope vaccine construct was evaluated using the C-ImmSim server to simulate host immune responses. The antibody profile (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ec) indicated a strong primary immune response, marked by a rapid increase in combined IgM and IgG levels, followed by sustained elevations in IgM and IgG1\u0026thinsp;+\u0026thinsp;IgG2 titers, suggesting effective humoral immunity. A notable reduction in antigen levels was observed after vaccination, indicating efficient antigen clearance [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnalysis of B-cell dynamics (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb) demonstrated a significant increase in total B-cell populations, along with the generation of memory B-cells and evidence of immunoglobulin class switching (IgM, IgG1, and IgG2). These findings suggest the development of long-term immune memory and affinity maturation. The helper T-cell (TH) response (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea) showed a marked expansion in total TH cell populations, including memory TH cells, indicating effective activation of cellular immune responses.\u003c/p\u003e \u003cp\u003eCytokine profiling (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ed) revealed elevated levels of IFN-γ and IL-2, along with moderate increases in IL-12 and TNF-α, suggesting a Th1-biased immune response, which plays a key role in antiviral immunity. Overall, the vaccine construct induces a robust, sustained, and multi-component immune response involving both humoral and cellular mechanisms [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study outlines an immunoinformatics-driven approach for the rational design of a multi-epitope subunit vaccine targeting the hemagglutinin\u0026ndash;neuraminidase (HN) glycoprotein of Sosuga virus (SOSV), an emerging zoonotic pathogen of public health concern. The selection of HN as the target antigen is supported by its role in viral attachment, entry, and interaction with host immune mechanisms, as well as its surface exposure, making it suitable for epitope-based vaccine design [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA systematic screening strategy enabled the identification of B-cell and T-cell epitopes with favorable antigenicity, non-allergenicity, and non-toxic profiles. The inclusion of both MHC class I and class II epitopes supports activation of cytotoxic and helper T-cell responses, while B-cell epitopes contribute to humoral immunity. The integration of 41 epitopes resulted in high global population coverage (99.79%), although the structural complexity of such a construct requires further validation.\u003c/p\u003e \u003cp\u003eThe incorporation of β-defensin as an adjuvant, linked via an EAAAK spacer, was intended to enhance immunogenicity through activation of innate immune pathways. The use of AAY and GPGPG linkers facilitates antigen processing and presentation while maintaining structural integrity. Physicochemical analysis indicated that the construct is stable, hydrophilic, and suitable for recombinant expression, supported by favorable solubility predictions.\u003c/p\u003e \u003cp\u003eStructural modeling provided a preliminary three-dimensional framework of the vaccine construct. Although validation metrics, including Ramachandran analysis, indicate moderate stereochemical quality, the model is adequate for initial computational studies. Further refinement and experimental validation are required to confirm structural accuracy.\u003c/p\u003e \u003cp\u003eMolecular docking demonstrated favorable interactions with key immune receptors, including MHC class I, MHC class II, and Toll-like receptor 4 (TLR4), suggesting potential for antigen presentation and receptor engagement. However, these results represent theoretical predictions and do not confirm biological activity or immune activation [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNormal mode analysis supported the stability and flexibility of the vaccine\u0026ndash;receptor complexes, indicating their ability to maintain structural integrity while allowing necessary conformational changes, although this approach simplifies real biological conditions.\u003c/p\u003e \u003cp\u003eImmune simulation suggested that the vaccine construct may induce both humoral and cellular immune responses, including increased antibody levels, memory cell formation, and cytokine production. Elevated IFN-γ and IL-2 levels indicate a Th1-biased response associated with antiviral immunity. However, these findings require experimental validation [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe optimization of codons and in silico cloning were used to verify that the gene could be expressed in Escherichia coli and production could be done on a large scale. Despite these promising findings, the study is limited by its reliance on computational predictions. Factors such as protein folding, post-translational modifications, immune variability, and long-term safety remain to be evaluated experimentally.\u003c/p\u003e \u003cp\u003eIn conclusion, this study presents a rational framework for the design of a multi-epitope vaccine against SOSV. The proposed construct shows promising in silico characteristics; however, comprehensive in vitro and in vivo studies are essential to confirm its safety, immunogenicity, and efficacy.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, a multi-epitope subunit vaccine targeting the hemagglutinin\u0026ndash;neuraminidase (HN) protein of Sosuga virus was designed using an integrated immunoinformatics approach. The selected epitopes exhibited favorable antigenicity, non-allergenicity, and non-toxic characteristics and were assembled using appropriate linkers along with a β-defensin adjuvant to enhance immunogenic potential.\u003c/p\u003e \u003cp\u003eStructural modeling and validation suggested that the vaccine construct adopts a stable conformation with acceptable stereochemical properties. Molecular docking analyses indicated favorable interaction patterns with MHC class I, MHC class II, and TLR4 receptors, suggesting the potential for effective immune recognition. These observations were supported by normal mode analysis, which demonstrated both structural stability and flexibility of the docked complexes.\u003c/p\u003e \u003cp\u003eThe prediction of ability to generate humoral and cellular immune responses was based on the outcomes of immune simulation. Moreover, codon optimization and in silico cloning tests validated the possibility of effective expression in Escherichia coli.\u003c/p\u003e \u003cp\u003eGenerally, the suggested multi-epitope vaccine construct is a promising vaccine against Sosuga virus. Nevertheless, in vitro and in vivo experiments should be carried out to establish the safety of its application, immunogenicity, and protective efficacy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOSV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSosuga virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHemagglutinin\u0026ndash;neuraminidase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eI\u0026ndash;Major Histocompatibility Complex Class I\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eII\u0026ndash;Major Histocompatibility Complex Class II\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTLR4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eToll\u0026ndash;like receptor 4\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCytotoxic T lymphocyte\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHTL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHelper T lymphocyte\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIEDB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmune Epitope Database\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVijayabharathi Saravanan (VS) conceptualized and designed the study, performed data analysis, and drafted the manuscript. Dharshini Jaisankar (DJ) contributed to data interpretation and manuscript revision. Monisha Punniyakotti (MP) assisted in analysis and critically reviewed the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the manuscript preparation process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the authors used Grammarly to assist with language editing, formatting, and improvement of manuscript clarity. The authors critically reviewed, edited, and verified all content and take full responsibility for the accuracy, integrity, and originality of the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGhaffar SA, Tahir H, Muhammad S, Shahid M, Naqqash T, Faisal M, Albekairi TH, Alshammari A, Albekairi NA, Manzoor I (2024) Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches. 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Vaccines (Basel). 13\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu Q, Wu H, Meng J, Wang J, Wu J, Liu S, Tong J, Nie J, Huang W (2024) Multi-epitope vaccine design for hepatitis E virus based on protein ORF2 and ORF3. Front Microbiol 15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmicb.2024.1372069\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2024.1372069\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Sosuga virus, hemagglutinin-neuraminidase, β-defensin, TLR4, MHC class I; MHC class II","lastPublishedDoi":"10.21203/rs.3.rs-9694926/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9694926/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSosuga virus (SOSV) is a zoonotic paramyxovirus that is characterized by a high mortality rate, and the lack of approved vaccines or specific antiviral treatment contributes to its high importance in terms of public health. This paper adopted an immunoinformatics-based approach to develop a multi-epitope subunit vaccine against the protein hemagglutinin-neuraminidase (HN) of SOSV. B-cell and T-cell epitopes that had the potential to be antigens, allergens, toxically active and cover a large portion of the population were identified and screened to promote safety and general immunogenic relevance. The epitopes were then put together as a chimeric construct with the aid of the appropriate linkers, with an addition of 2-defensin to boost the activation of the immune.\u003c/p\u003e \u003cp\u003eThe designed vaccine construct was further evaluated for physicochemical and structural properties. The construct exhibited strong antigenicity (VaxiJen score: 0.7163) and high solubility (0.999990), with stable structural parameters. Population coverage analysis demonstrated 99.79% global coverage, indicating broad applicability. Molecular docking revealed stable interactions with immune receptors, with binding energies of \u0026minus;\u0026thinsp;1120.8 (MHC-I), \u0026minus;\u0026thinsp;1035.5 (MHC-II), and \u0026minus;\u0026thinsp;1061.6 (TLR4). Normal mode analysis supported structural stability and flexibility of the complexes. Immune simulation predicted robust humoral and cellular responses, including antibody production and memory cell formation. Codon optimization indicated efficient expression potential in \u003cem\u003eEscherichia coli\u003c/em\u003e (CAI: 0.9584; GC content: 49.85%).\u003c/p\u003e \u003cp\u003eOn the whole, the multi-epitope vaccine construct suggested is a potential vaccine against SOSV; nevertheless, it needs to be proved by experimental methods that it is immunogenic, safe, and can offer protection.\u003c/p\u003e","manuscriptTitle":"Immunoinformatics-driven design and in silico evaluation of a multi-epitope vaccine targeting the hemagglutinin–neuraminidase protein of Sosuga virus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 07:54:44","doi":"10.21203/rs.3.rs-9694926/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":"18ee2eaa-dc76-4ab3-9d9c-c532eb758014","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"checksComplete","content":"","date":"2026-05-13T14:50:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Computer-Aided Molecular Design","date":"2026-05-12T16:38:28+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T07:54:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 07:54:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9694926","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9694926","identity":"rs-9694926","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}