Virtually screened inhibitors for Human Papilloma Virus infections

Virtually screened inhibitors for Human Papilloma Virus infections | 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 Virtually screened inhibitors for Human Papilloma Virus infections Vemula Vani, Manikandan Alagumuthu, Sanjay Prasad, Nikita Paul, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3998798/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 Human papillomavirus (HPV) infection is one of the most common sexually transmitted diseases. The current treatment methods consist of the use of chemotherapeutic agents or the application of surgical procedures to remove the developed tumors. The alternatives to treat HPV- associated diseases is the discovery of accessible drug-based therapies. In HPV infected cell, E6 protein complexes with E6AP to form p53 degradation complex and induce tumorigenesis. The objective of this study is to discover potential small molecule inhibitors against HPV16 E6 protein using virtual screening approach. Three novel HPV 16 E6 inhibitors viz. compound 5, compound 7 and compound 10 were designed using a fragment-based approach. The structural information of these three novel compounds was used in virtual screening against in- trials subset of ZINC database and a total of 9800 hits were identified. The obtained molecules from the database were further screened by three stages of virtual screening using GLIDE module of Schrodinger software. The results reveal that Five hit molecules (ZINC000034853956, ZINC000001534965, ZINC000095617673, ZINC000005764481 and ZINC000071606215) showed better glide score in comparison with reference molecule, Luteolin. These molecules exhibited crucial interactions with E6 protein of HPV 16. The pharmacokinetic properties of these hit molecules were analyzed using QikProp program. The results indicate that all the five molecules were found to have good pharmacokinetic properties and human oral absorption. All the five hit molecules were predicted to be no toxic and except ZINC000005764481, all other four molecules showed druglike behavior. Therefore, the four hit molecules (ZINC000034853956, ZINC000001534965, ZINC000095617673 and ZINC000071606215) can be used as lead molecules in the development of HPV 16 E6 inhibitors for treatment of HPV related diseases. HPV16 E6 Anti-cervical cancer small molecule inhibitors Virtual screening ZINC Molecular docking ADME Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Human papillomavirus (HPV) is big threat to human and it’s a sexually transmitted disease (STD). As they are oncogenic in nature, some of the HPV strains were known as high-risk (HR) types, being the major cause of cervical cancer [ 1 ] . HPV-16 is considered to be the most prevalent type of cervical cancer, approximately 55% of all cases [ 2 ] . The approved prophylactic vaccines, Cervarix [ 3 ] and Gardasil [ 4 ] are used for the prevention of HPV infection. But, in the case of people already infected, current methods of treatment include the use of chemotherapy or surgical methods to remove the developed tumors [ 5 ] . These methods of treatment are costly, invasive, and non-specific which limits their availability to the patients, especially in developing countries. So, one of the main alternative approaches to treat HPV-related diseases is the discovery of cost-effective drug-based therapies against the virus. The E6 and E7 proteins of HPV, take control of the regulatory functions of the cell cycle and promote the proliferation of infected cells. Further, in HR HPV types, the continuous expression of these two proteins causes genomic instability, which plays a critical role in tumorigenesis [ 6 ] . The E7 protein is involved in the degradation of Retinoblastoma (pRb) family members promoting the S-phase progression. Consequently, HPV genome replication is promoted thereby collateral cellular DNA damage and chromosomal abnormalities can be produced [ 7 ] . Normally, cells with genomic instability are targeted by p53 for apoptosis. However, the E6 protein enables cell immortalization by forming a complex with the cellular E3 ligase E6-associated protein (E6AP) and targeting p53 for degradation through the ubiquitin-proteasome pathway [ 6 , 8 ] . E6 is a small protein of 158 residues consisting of two Zn2 + binding domains linked by a helix linker of 36 amino acids [ 8 ] . E6 can bind to several cellular proteins through a PDZ-domain-binding motif or by an inter-domain groove that acts as a LxxLL binding pocket [ 8 ] . In the E6-E6AP interaction, the E6 pocket recognizes the LxxLL helical motif of the HECT domain of E6AP, which in turn allows p53 to form the p53 degradation complex [ 9 ] . Since HPV-induced tumors contain high levels of non-mutated p53 [ 10 ] , the disruption of E6-E6AP interaction is a promising therapeutic approach that focuses on the reactivation of p53 protein functions to induce cellular apoptosis of HPV- infected cells. Moreover, the E6 pocket consists of a specific structure that cellular LxxLL -binding proteins do not have [ 11 ] . This structural difference can be used to improve binding selectivity against a viral protein concerning cellular components. Therefore, the E6 pocket protein is one of the major targets for drug development against HPV infection and its oncogenic effects. The inhibition of the E6-E6AP interaction was demonstrated by several studies through different molecules like alpha-helical peptides [ 12 , 13 ] , intrabodies [ 14 ] , and small molecules [ 15 – 17 ] . The majority of these compounds have demonstrated limited bioavailability or moderate activity. Finding pharmacologically active substances to treat HPV infection is therefore necessary. The process of developing new drugs requires a lot of time and money. It takes more than ten years, and each approved therapeutic molecule costs, on average, $ 2.8 billion [ 18 ] . Computer-aided drug discovery (CADD) is an attractive approach to drug development, particularly in the early stages. CADD can be used to improve the efficacy of the hit discovery process through computational techniques, particularly virtual screening (VS) by screening large databases to identify a small group of candidate molecules with desirable pharmacological properties. This computational approach made the drug discovery process more goal-oriented, saving resources of time and money [ 19 , 20 ] . Hence, the objective of our study is to discover potential small molecule inhibitors against HPV16 E6 protein using a virtual screening approach. These small molecule inhibitors can be used as chemotherapeutic agents in the treatment of cervical cancer as an alternative to surgery. MATERIALS AND METHODS Hardware and software Using a bioinformatics workstation running Windows 10 and equipped with a 1 TB solid state drive, 32 GB RAM, a 4.8 GHz processor, and an Intel core i7 10700 processor, the study was conducted. Maestro 12.5, ZINC database, Osiris property Explorer, and Protox II server software were employed for the software. Data Set Every external data set used in this research is openly accessible on the internet. The HPV 16 E6 protein's X-ray crystal structure was retrieved in PDB format from RCSB-PDB ( http://www.rcsb.org/ ) using PDB ID: 4GIZ ( https://www.rcsb.org/structure/4GIZ ) [ 21 ] . The crystal structure of the whole human HPV oncoprotein E6 in complex with the ubiquitin ligase E6AP LXXLL peptide is represented by 4GIZ, which has a resolution of 2.55 Å. Using a fragment-based strategy, three new HPV 16 E6 inhibitors—compounds 5, 7, and 10—were created [ 22 ] . The in-trials subset of the ZINC database was screened using the structural data of these three new drugs. 9800 hits in all were obtained in SDF file format and taken into account for the VS procedure. Creation of Phase Database The ZINC database's SDF files were used to generate a phase database. It is a free virtual screening database of substances that are sold commercially. Over 230 million chemicals in three-dimensional dockable forms are stored in ZINC [ 23 ] . The ligand structures were built, each ligand's conformers were created, and Epik [ 24 ] was used to assign the appropriate ionization states. The pre-processing stage ensures that the ligand molecules are free of metals, solvent molecules, counter-ions, tautomeric states, and the proper bond orders [ 25 , 26 ] . It also ensures that the ligand molecules are in appropriate protonation states. Results were shown to be somewhat worse when just the most stable tautomeric states of molecules were considered, according to a paper [ 27 ] . Therefore, during the database construction process, high-energy tautomeric states of molecules were removed. The ligands were pre-filtered further by Lipinski’s rule of five using the QikProp module of Schrödinger to remove the false positives from the analysis [ 28 ] . Target protein preparation and Grid generation Using the Protein Preparation Wizard in the Schrodinger suite, the target protein PDB ID: 4GIZ ( https://www.rcsb.org/structure/4GIZ ) was preprocessed by implying parameters such as assigning bond orders, zero-order bonds to metal atoms, converting selenomethionine to methionine, filling in absent hydrogens, capping termini, side chains, and loops, and removing waters beyond 5Å distance surrounding the co-crystallized ligand [Protein Preparation Wizard; Epik, Schrödinger, LLC, New York, NY, 2021]. Only the C chain, which contains the E6 moiety, was kept in the crystal structure; the other five chains (A, B, C, D, E, and F) were removed. With the OPLS-2005 force field and a root mean square deviation (RMSD) of 0.30 Å, the protein's hydrogen bonds were decreased and optimized to renovate the surrounding hydrogen atoms. The Schrodinger Receptor Grid Generation module [Glide, Schrödinger, LLC, New York, NY, 2021] was utilized to create the protein grid. The exact amino acid residue number (32, 50, 53, 62, 64, 67, 70, 102, 128, 131) that makes up the binding pocket of the HPV 16 E6 protein is chosen to define the receptor grid generation module [ 13 ] . Using the OPLS_2005 force field, the protein atoms were fixed inside the default Van der Waals radius scaling factor of 1 Å with partial charge cutoff 0.25 Å. Molecular docking The docking investigations of the ligands were carried out using the Schrödinger GLIDE module [29, 30]. Using high throughput virtual screening (HTVS) and standard precision (SP) and extra precision (XP) docking with default parameters, the ligands were docked step-by-step [28, 31]. Large database VS uses HTVS as the first docking phase because it's a quick process. 10% of the final compounds were sent on to the SP docking stage after HTVS. Following SP docking, the top 10% of all compounds were taken into account and moved on to the XP docking stage. The last phase in the VS procedure is the XP docking [32]. ADME and Toxicity analysis Using the QikProp module of the Schrodinger interface, the hit compounds' ADME (Absorption, Distribution, Metabolism, and Excretion) properties were estimated [QikProp, Schrödinger, LLC, New York, NY, 2021]. In addition to Lipinski's rule of five and Jorgensen rule of three, it is used to assess drug-likeness and pharmaceutical qualities such as molecular weight, aqueous solubility (QPlogS), octanol/water (logP), brain/blood partition coefficient (QPlogBB), CNS, hydrogen bond donors, and acceptors. Online web server tools such as Osiris property explorer ( https://www.organic-chemistry.org/prog/peo/ ) and ProTox-Ⅱ algorithm ( https://tox-new.charite.de/protox_II/ ) were utilized to forecast the toxicity profile of the hit compounds [33]. Using Osiris Property Explorer, the compounds' toxicity and drug-likeness were anticipated. The hit chemicals' potential for mutagenicity, carcinogenicity, or reproductive harm was estimated using Osiris. Their oral toxicity (LD 50 ) was predicted using the ProTox-TM algorithm. As a unique approach to toxicity prediction, the prediction detects dangerous fragments in a molecule and is based on the similarity of compounds with known median lethal doses (LD 50 ). MD Simulation and DFT calculations Molecular Dynamics (MD) simulations were used to quantify the stability of the interaction between the two target molecules in the docked complex of compounds 5, 7, and 10. These complexes were simulated via molecular dynamics using the GROMACS 5.1 program and the GROMOS-96 force field, which is crucial for protein dynamics [34, 35]. The source format for estimating the ADMET properties of relevant compounds was the SMILES (Simplified Molecular-Input Line-Entry System) format. The compounds' SMILES format was utilized and examined for pkCSM. RESULTS AND DISCUSSION De novo design of novel compounds Using a fragment-based strategy, three new HPV 16 E6 inhibitors—compounds 5, 7, and 10—were created (Fig. 2 ). These three substances had good GI absorption, a favorable druglikeness score, and were determined to be non-toxic [12]. Virtual screening of the ZINC database Nine thousand hits were found when the structural data of these three new compounds was virtually screened against the ZINC database's in-trials subset. The target protein, HPV 16 E6, was initially docked with the reference molecule, luteolin, and the corresponding glide energy and score were computed. Using the Schrodinger software's GLIDE module, three virtual screening phases were applied to the molecules that were collected from the database. Approximately 952 molecules were retrieved by HTVS docking in the first step. 10% of the ligands from the HTVS result moved on to the SP docking step, yielding 96 hit molecules. In the last phase, the top 10% of highly-scoring compounds from the SP docking study were taken into consideration for XP docking. Five-hit compounds (ZINC000034853956, ZINC000001534965, ZINC000095617673, ZINC000005764481, and ZINC000071606215) demonstrated a higher glide score than the reference molecule, Luteolin, according to the XP docking data (Table 1 & Fig. 1 ). Figure 1 summarizes the workflow and shows the methods taken to identify hit compounds. Figure 2 displays the two-dimensional (2D) structures of the five hit molecules that were obtained. Table 1 Glide score of screened hit molecules with reference compound, Luteolin S.NO Ligand ZINC ID Glide gscore (kcal/mol) Glide energy (kcal/mol) 1 Luteolin -7.734 -33.583 2 ZINC000011616585 -9.338 -32.880 3 ZINC000034853956 -10.203 -41.838 4 ZINC000001534965 -9.023 -42.657 5 ZINC000095617673 -8.778 -39.864 6 ZINC000005764481 -8.563 -38.549 7 ZINC000071606215 -8.550 -42.409 Studies of interactions between screened hit compounds The Schrodinger software's ligand interaction diagram (LID) was utilized to examine the interaction patterns of selected hit compounds. The outcomes are shown in Fig. 3 . Green lines represented hydrophobic contacts, while purple lines showed the presence of hydrogen bonds. The stability of ligands in the complex structure is significantly influenced by the hydrogen bond interaction. ZINC000071606215 generated five hydrogen bonds with the HPV 16 E6 protein, while ZINC000034853956 and ZINC000005764481 established four. ZINC000001534965 and ZINC000095617673, the other two compounds, demonstrated two hydrogen bonds with the HPV16 E6 protein. Table 2 shows the hydrogen bond interactions of screened hit compounds. Table 2 Analysis of hydrogen bond interactions of screened hit molecules with HPV16 E6 protein S.No ZINC ID No of H bonds Interacting atoms E6 Protein-Ligand Distance (Å) 1 ZINC000034853956 4 Cys 51…Lig(O) Lig(OH)… Cys 51 Lig(NH)… Cys 51 Lig(OH)… Tyr 32 1.88 1.77 2.30 1.96 2 ZINC000001534965 2 Arg131…Lig(O) Ser74… Lig(OH) 1.79 2.12 3 ZINC000095617673 2 Arg10…Lig(O) Cys 51…Lig(OH) 2.50 2.34 4 ZINC000005764481 4 Lig(OH)… Cys 51 Lig(OH)… Gln 107 Lig(OH)… Gln 107 Ser74… Lig(OH) 2.04 2.06 2.07 1.74 5 ZINC000071606215 5 Cys 51…Lig(O) Lig(OH)… Cys 51 Lig(NH)… Cys 51 Lig(OH)… Tyr 32 Arg131…Lig(O) 1.92 1.83 2.42 2.09 2.29 Table 3 Analysis of hydrophobic interactions of screened hit molecules with HPV16 E6 protein S.NO ZINC ID Hydrophobic interactions Mimetic interactions No. of Mimetic interactions 1 ZINC000034853956 Leu50, Cys51, Val53, Ala61, Ile52, Phe45, Val62, Val31, Tyr32, Leu67, Tyr70, Ile128 Val31, Tyr32, Leu50, Val62, Leu67, Tyr70 6 2 ZINC000001534965 Leu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Cys66, Leu67, Tyr70 Val31, Tyr32, Leu50, Val62, Leu67, Tyr70 6 3 ZINC000095617673 Leu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Leu100, Leu67, Tyr70 Val31, Tyr32, Leu50, Val62, Leu67, Tyr70 6 4 ZINC000005764481 Leu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Ile52, Leu67, Tyr70 Val31, Tyr32, Leu50, Val62, Leu67, Tyr70 6 5 ZINC000071606215 Leu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Ile52, Leu67, Tyr70, Ile128 Val31, Tyr32, Leu50, Val62, Leu67, Tyr70 6 Property Analysis of Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Because it reduces possible dangers during clinical trials, the examination of ADMET characteristics is essential to the computer-based drug-designing process. The QikProp tool was utilized to examine the pharmacokinetic characteristics of these hit compounds, and the ProTox II server was utilized to forecast the molecules' potential for oral toxicity. All five compounds were determined to have good pharmacokinetic characteristics and oral absorption by humans, as shown by the results shown in Table 4 . With the exception of ZINC000005764481, all five of these compounds were projected to be harmless, and the other four all exhibited drug-like characteristics. To estimate the oral toxicity of these lead-hit compounds, the ProTox II server was utilized. It is clear from Table 5 's data that these five lead compounds are classified as Class 4 toxins. ZINC000005764481 displayed a negative drug-likeness score (-0.61) out of these 5 lead compounds. Positive drug-likeness scores were displayed by the remaining four compounds (ZINC000034853956, ZINC000001534965, ZINC000095617673, and ZINC000071606215). Osiris was used to assess additional toxicity characteristics such as the hit compounds' mutagenicity, irritating factor, tumorigenic potential, drug score, and drug-likeness. The four lead compounds were determined to be non-toxic and to have a positive drug likeness score, indicating that they behave like drugs and are among the most promising inhibitors of the HPV-16 E6 protein. Table 4 ADME analysis of screened hit molecules S. No ZINC ID MW CNS Donor HB Accpt HB QPlog Po/w QPlogS QPlog BB QPlogKP stars HOA QPlogPoct QPlogPw SASA FOSA 1 ZINC000034853956 368.432 -2 4 7.200 1.879 -2.874 -1.304 -4.980 0 3 22.796 15.258 661.909 223.704 2 ZINC000001534965 421.467 -2 2 5.400 4.611 -5.107 -1.471 -2.891 0 3 20.104 10.531 668.407 197.518 3 ZINC000095617673 369.392 -2 3 4.400 4.202 -5.530 -1.760 -3.032 0 3 20.984 11.832 674.928 111.952 4 ZINC000005764481 304.385 -2 4 5.850 1.348 -3.103 -1.134 -3.886 0 3 18.880 13.648 527.054 244.519 5 ZINC000071606215 368.432 -2 4 6.700 1.974 -2.851 -1.124 -5.048 0 3 22.727 14.740 643.170 234.509 MW- Molecular weight CNS-Predicted central nervous system activity on a -2 (inactive) to + 2 (active) scale Donor HB – Donor hydrogen bond Acceptor HB- Acceptor hydrogen bond QPlogPo/w-Predicted water/ octanol partition coefficient QPlogS- Predicted aqueous solubility QPlogBB- Predicted brain/blood partition coefficient QPlogKP- Predicted skin permeability Stars-Number of property or descriptor values that fall outside the 95% range of similar values for known drugs HOA-Human oral absorption QPlogPoct- Predicted octanol/ gas partition coefficient QPlogPw- Predicted water/gas partition coefficient SASA- Solvent accessible surface area FOSA- Hydrophobic solvent accessible surface area Table 5 Toxicity analysis of screened hit molecules S. No ZINC ID Mutagenic Tumorigenic Irritant Reproductive effect Druglikeness Toxicity Class 1 ZINC000034853956 Nil Nil Nil Nil 6.71 Class 4 2 ZINC000001534965 Nil Nil Nil Nil 1.08 Class 4 3 ZINC000095617673 Nil Nil Nil YES 2.94 Class 4 4 ZINC000071606215 Nil Nil Nil Nil 5.69 Class 4 Results of MD simulations The docked complex of the selected compounds was subjected to MD Simulation studies in order to examine its stability in terms of molecular interactions and root mean square deviation (RMSD) over a 200 ns duration. The Protein-Ligand complex's pre- and post-analysis are shown in Fig. 6 . The docked complex is shown in Fig. 6 A, and the overlapping, un-docked protein with the Protein-Ligand complex is shown in Fig. 6 B. The green hue denotes the minor variation that resulted from the drug's impact after it bound to the target protein. The stability of the protein-peptide complexes was examined using the RMSD of the backbone atoms. The estimated average RMSD for these complexes ranged from 1.0 to 1.4 nm (Fig. 6 C). Upon completion of the 200ns simulation, all protein-ligand complexes had attained their stable conformations. The estimated root-mean-square fluctuations (RMSF) (Fig. 6 D) showed some small fluctuations in the loop region. The concentration of active site residues did not change at 0.4 nm variation. Figure 7 A presents the results of the ZINC000001534965 Molecular Electrostatic Potential (MESP) study. Dark blue indicates the region that is most electropositive, while dark red indicates the electronegative region (which ranges from − 0.4241 to 0.5011). Areas in ZINC000001534965 that had a strong carbonyl group connection were found to be very electropositive, while areas that had a hydroxyphenyl ring connected to a chromen ring were found to be electronegative. Furthermore, the MESP analysis demonstrated that all molecules contained electron transport. The electron transfer that results in a complete valence shell makes the molecule more stable. Because ZINC000001534965 has fewer aromatic rings (Fig. 7 B), it is a better suited inhibitor of E6-E6AP. The ZINC000001534965's ionization potential is caused by HOMO energies (-26.542 eV), and the compounds' electron affinities are caused by LUMO energies (-27.254 eV). The HOMO region in ZINC000001534965 was dispersed over the hydroxyl and carbonyl ends, whereas the LUMO was located on the end of the aromatic ring that was connected to the other carbonyl group (Fig. 7 C & 7 D). The majority of these DFT calculations support the medicinally beneficial substances. CONCLUSION One of the most prevalent sexually transmitted diseases that causes cervical cancer in women is the human papillomavirus (HPV). The most common kind of cervical cancer is HPV-16. It is made up of the related protein E6AP linked to the oncogenic protein E6. HPV-transformed cells undergo cellular death when E6-E6AP is disrupted. Therefore, one of the main targets for medication research against HPV infection is the E6 pocket protein. Structure-based drug design is an effective technique for finding novel therapeutic candidates targeting significant targets. In this study, a virtual screening strategy was used to discover possible small molecule inhibitors against HPV16 E6. Based on the reference compound's docking score, five hit molecules were screened. After examining the pharmacokinetic characteristics, toxicity, and binding affinity of these five compounds, it was determined that four of them (ZINC000034853956, ZINC000001534965, ZINC000095617673, and ZINC000071606215) were the most likely to block the HPV16 E6 protein. These four molecules may serve as lead compounds in the creation of novel medications intended to cure illnesses brought on by HPV. Declarations Author Contribution MA & VV designed the work and contributed equally in experiments, data processing article writing etc. SP, NP, GN, NP and VP are carried out coputational experiments and processed data. ACKNOWLEDGEMENT All authors wish to thank the management of Gokula Education Foundation, M. S. Ramaiah College of Arts, Science, and Commerce Bangalore for sponsoring this project through seed funding (Ref No: PO/CIR/2020- 21/017). We also thank the Principal, the Head of the Department, and the faculty of the Department of Microbiology of the college for their support and cooperation during the course of this work. References Allison DB, Maleki Z (2016) HPV-related head and neck squamous cell carcinoma: An update and review. J Am Soc Cytopathol . 5(4), 203–15. Forman D, de Martel C, Lacey CJ, Soerjomataram I, Lortet-Tieulent J, Bruni L, Vignat J, Ferlay J, Bray F, Plummer M, Franceschi S (2012) Global burden of human papillomavirus and related diseases. 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Cappel D, Hall ML, Lenselink EB, Beuming T, Qi J, Bradner J, Sherman W (2016) Relative Binding Free Energy Calculations Applied to Protein Homology Models. J Chem Inf Model. , 56(12), 2388-2400. Di Capua A, Sticozzi C, Brogi S, Brindisi M, Cappelli A, Sautebin L, Rossi A, Pace S, Ghelardini C, Di Cesare Mannelli L, Valacchi G, Giorgi G, Giordani A, Poce G, Biava M, Anzini M (2016) Synthesis and biological evaluation of fluorinated 1,5-diarylpyrrole-3-alkoxyethyl ether derivatives as selective COX-2 inhibitors endowed with anti-inflammatory activity. Eur J Med Chem . 109, 99-106. Rajput VS, Mehra R, Kumar S, Nargotra A, Singh PP, Khan IA (2016) Screening of antitubercular compound library identifies novel shikimate kinase inhibitors of Mycobacterium tuberculosis. Appl Microbiol Biotechnol . 100(12), 5415-26. Banerjee P, Eckert A. O, Schrey A. K, Preissner R (2018) ProTox-II: a web server for the prediction of toxicity of chemicals . Nucleic Acids Res . 46(W1), W257–63. Oostenbrink C, Villa A, Mark AE, van Gunsteren WF (2004)A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J Comput Chem . 25(13), 1656-76. Sajjan R, Manikandan A, Mirza S Baig (2021) Dual Targeting of 3CLpro and PLpro of SARS-CoV-2: A Novel Structure-Based Design Approach to treat COVID-19. Current Research in Structural Biology , 3, 9-18. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3998798","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":275798154,"identity":"05ea9cfe-738a-4a24-99a0-f94fe803b648","order_by":0,"name":"Vemula Vani","email":"","orcid":"","institution":"M. S. Ramaiah College of Arts, Science and Commerce","correspondingAuthor":false,"prefix":"","firstName":"Vemula","middleName":"","lastName":"Vani","suffix":""},{"id":275798156,"identity":"6f8ee52d-434d-42e2-bd79-8cf7d84470ed","order_by":1,"name":"Manikandan Alagumuthu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYFACxsYDQJIHypOQA5EHHuDX0nDgAJIWY7CWBAL2gLTAQWIDiMSnRbf9cMPhDxXbZPhnHz664ecOi/T5YYcfAm2xk9NtwK7F7Ewi0GFnbvNInEtLu9l7RiJ34+00A6CWZGOzAzi0HABqOdh2m8eAh8fsBm8bUMvsBJCWA4nbcGk5/xCh5ebfNol0w9npH/BruYFky22gLQny0jkEbLkBtOUMyC9n2NJuy7ZJGG6Qzik4kGCAxy/n0x8+qKi4bc/fw3zs5tu2Onn52embP3yosJPDpQUTGIBVGhCrHATkG0hRPQpGwSgYBSMBAABXzmu39detTgAAAABJRU5ErkJggg==","orcid":"","institution":"M. S. Ramaiah College of Arts, Science and Commerce","correspondingAuthor":true,"prefix":"","firstName":"Manikandan","middleName":"","lastName":"Alagumuthu","suffix":""},{"id":275798157,"identity":"428c7a4e-1cb6-48d2-9ff9-2cb03d5b22e6","order_by":2,"name":"Sanjay Prasad","email":"","orcid":"","institution":"Indian Institute of Science","correspondingAuthor":false,"prefix":"","firstName":"Sanjay","middleName":"","lastName":"Prasad","suffix":""},{"id":275798158,"identity":"81b743d2-3d75-450e-b3db-264b96719bc1","order_by":3,"name":"Nikita Paul","email":"","orcid":"","institution":"M. S. Ramaiah College of Arts, Science and Commerce","correspondingAuthor":false,"prefix":"","firstName":"Nikita","middleName":"","lastName":"Paul","suffix":""},{"id":275798159,"identity":"6afcab56-1499-4b9a-ab98-1f2fcc1ceb0b","order_by":4,"name":"G Nithya","email":"","orcid":"","institution":"M. S. Ramaiah College of Arts, Science and Commerce","correspondingAuthor":false,"prefix":"","firstName":"G","middleName":"","lastName":"Nithya","suffix":""},{"id":275798160,"identity":"c4d09f8c-d1d3-43bd-aded-337b475d71bb","order_by":5,"name":"N Pooja","email":"","orcid":"","institution":"M. S. Ramaiah College of Arts, Science and Commerce","correspondingAuthor":false,"prefix":"","firstName":"N","middleName":"","lastName":"Pooja","suffix":""},{"id":275798161,"identity":"bb42770a-c150-451f-bb1f-2d769918b46e","order_by":6,"name":"V Pooja","email":"","orcid":"","institution":"M. S. Ramaiah College of Arts, Science and Commerce","correspondingAuthor":false,"prefix":"","firstName":"V","middleName":"","lastName":"Pooja","suffix":""}],"badges":[],"createdAt":"2024-02-29 06:52:03","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3998798/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3998798/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52039251,"identity":"f31e8b89-0b47-437b-a077-dfae0d509e2e","added_by":"auto","created_at":"2024-03-05 17:40:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103443,"visible":true,"origin":"","legend":"\u003cp\u003eBar graph showing screened hit compounds and reference compound with their respective glide energy\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3998798/v1/ba0b5583918533602730bee4.png"},{"id":52039254,"identity":"306ac5ef-3176-42fe-8909-7e26bbbd58f1","added_by":"auto","created_at":"2024-03-05 17:40:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":58125,"visible":true,"origin":"","legend":"\u003cp\u003e2 D structure of screened hit molecules \u003cstrong\u003ea)\u003c/strong\u003eZINC000001534965 \u003cstrong\u003e(b)\u003c/strong\u003e ZINC000005764481 \u003cstrong\u003e(c)\u003c/strong\u003e ZINC000095617673 \u003cstrong\u003e(d)\u003c/strong\u003eZINC35801098 \u003cstrong\u003e(e)\u003c/strong\u003e ZINC000034853956.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3998798/v1/2323da1e73c421783a8b7cd7.png"},{"id":52039252,"identity":"9ee91d7f-24b6-4ae6-8862-c3cf99e37b28","added_by":"auto","created_at":"2024-03-05 17:40:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":211477,"visible":true,"origin":"","legend":"\u003cp\u003eLigand interaction diagram of screened hit molecules to the binding pocket of HPV 16 E6 Protein a) ZINC000001534965 (b) ZINC000005764481 (c) ZINC000095617673 (d) ZINC000071606215 (e) ZINC000034853956\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3998798/v1/4467162569b135eb84c4c9a8.png"},{"id":52039255,"identity":"3dc47ca2-d5c3-405a-badc-85de8691a415","added_by":"auto","created_at":"2024-03-05 17:40:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":292816,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 6. \u003c/strong\u003ePre- and Post MD simulation analysis of Protein-Ligand complex\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3998798/v1/c275cad217ebda7c150dfc90.png"},{"id":52039253,"identity":"a9232fe8-b2fe-4a16-b26a-52cff7dece2b","added_by":"auto","created_at":"2024-03-05 17:40:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":354399,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 7. \u003c/strong\u003eMolecular electrostatic potential, aromaticity HOMO and LUMO of compounds\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3998798/v1/90ceb1b4fb3b28673c797a77.png"},{"id":52041856,"identity":"890aea49-0755-4f2d-a3cb-cadc7f877e11","added_by":"auto","created_at":"2024-03-05 18:23:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1328134,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3998798/v1/5016be2a-e5e3-4a53-8d9f-9dd97b5a4bcd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Virtually screened inhibitors for Human Papilloma Virus infections","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHuman papillomavirus (HPV) is big threat to human and it\u0026rsquo;s a sexually transmitted disease (STD). As they are oncogenic in nature, some of the HPV strains were known as high-risk (HR) types, being the major cause of cervical cancer \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. HPV-16 is considered to be the most prevalent type of cervical cancer, approximately 55% of all cases \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. The approved prophylactic vaccines, \u003cem\u003eCervarix\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e and \u003cem\u003eGardasil\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e are used for the prevention of HPV infection. But, in the case of people already infected, current methods of treatment include the use of chemotherapy or surgical methods to remove the developed tumors \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. These methods of treatment are costly, invasive, and non-specific which limits their availability to the patients, especially in developing countries. So, one of the main alternative approaches to treat HPV-related diseases is the discovery of cost-effective drug-based therapies against the virus. The E6 and E7 proteins of HPV, take control of the regulatory functions of the cell cycle and promote the proliferation of infected cells. Further, in HR HPV types, the continuous expression of these two proteins causes genomic instability, which plays a critical role in tumorigenesis \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The E7 protein is involved in the degradation of Retinoblastoma (pRb) family members promoting the S-phase progression. Consequently, HPV genome replication is promoted thereby collateral cellular DNA damage and chromosomal abnormalities can be produced \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Normally, cells with genomic instability are targeted by p53 for apoptosis. However, the E6 protein enables cell immortalization by forming a complex with the cellular E3 ligase E6-associated protein (E6AP) and targeting p53 for degradation through the ubiquitin-proteasome pathway \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eE6 is a small protein of 158 residues consisting of two Zn2\u0026thinsp;+\u0026thinsp;binding domains linked by a helix linker of 36 amino acids \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. E6 can bind to several cellular proteins through a PDZ-domain-binding motif or by an inter-domain groove that acts as a \u003cem\u003eLxxLL\u003c/em\u003e binding pocket \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. In the E6-E6AP interaction, the E6 pocket recognizes the \u003cem\u003eLxxLL\u003c/em\u003e helical motif of the HECT domain of E6AP, which in turn allows p53 to form the p53 degradation complex \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Since HPV-induced tumors contain high levels of non-mutated p53 \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, the disruption of E6-E6AP interaction is a promising therapeutic approach that focuses on the reactivation of p53 protein functions to induce cellular apoptosis of HPV- infected cells. Moreover, the E6 pocket consists of a specific structure that cellular \u003cem\u003eLxxLL\u003c/em\u003e-binding proteins do not have \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. This structural difference can be used to improve binding selectivity against a viral protein concerning cellular components. Therefore, the E6 pocket protein is one of the major targets for drug development against HPV infection and its oncogenic effects.\u003c/p\u003e \u003cp\u003eThe inhibition of the E6-E6AP interaction was demonstrated by several studies through different molecules like alpha-helical peptides \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, intrabodies \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, and small molecules \u003csup\u003e[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. The majority of these compounds have demonstrated limited bioavailability or moderate activity. Finding pharmacologically active substances to treat HPV infection is therefore necessary. The process of developing new drugs requires a lot of time and money. It takes more than ten years, and each approved therapeutic molecule costs, on average, \u003cspan\u003e$\u003c/span\u003e2.8\u0026nbsp;billion \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Computer-aided drug discovery (CADD) is an attractive approach to drug development, particularly in the early stages. CADD can be used to improve the efficacy of the hit discovery process through computational techniques, particularly virtual screening (VS) by screening large databases to identify a small group of candidate molecules with desirable pharmacological properties. This computational approach made the drug discovery process more goal-oriented, saving resources of time and money \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Hence, the objective of our study is to discover potential small molecule inhibitors against HPV16 E6 protein using a virtual screening approach. These small molecule inhibitors can be used as chemotherapeutic agents in the treatment of cervical cancer as an alternative to surgery.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHardware and software\u003c/h2\u003e \u003cp\u003eUsing a bioinformatics workstation running Windows 10 and equipped with a 1 TB solid state drive, 32 GB RAM, a 4.8 GHz processor, and an Intel core i7 10700 processor, the study was conducted. Maestro 12.5, ZINC database, Osiris property Explorer, and Protox II server software were employed for the software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData Set\u003c/h2\u003e \u003cp\u003eEvery external data set used in this research is openly accessible on the internet. The HPV 16 E6 protein's X-ray crystal structure was retrieved in PDB format from RCSB-PDB (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rcsb.org/\u003c/span\u003e\u003cspan address=\"http://www.rcsb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using PDB ID: 4GIZ (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org/structure/4GIZ\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org/structure/4GIZ\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. The crystal structure of the whole human HPV oncoprotein E6 in complex with the ubiquitin ligase E6AP LXXLL peptide is represented by 4GIZ, which has a resolution of 2.55 \u0026Aring;. Using a fragment-based strategy, three new HPV 16 E6 inhibitors\u0026mdash;compounds 5, 7, and 10\u0026mdash;were created \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The in-trials subset of the ZINC database was screened using the structural data of these three new drugs. 9800 hits in all were obtained in SDF file format and taken into account for the VS procedure.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eCreation of Phase Database\u003c/h2\u003e \u003cp\u003eThe ZINC database's SDF files were used to generate a phase database. It is a free virtual screening database of substances that are sold commercially. Over 230\u0026nbsp;million chemicals in three-dimensional dockable forms are stored in ZINC\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. The ligand structures were built, each ligand's conformers were created, and Epik\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e was used to assign the appropriate ionization states. The pre-processing stage ensures that the ligand molecules are free of metals, solvent molecules, counter-ions, tautomeric states, and the proper bond orders \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. It also ensures that the ligand molecules are in appropriate protonation states. Results were shown to be somewhat worse when just the most stable tautomeric states of molecules were considered, according to a paper\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Therefore, during the database construction process, high-energy tautomeric states of molecules were removed. The ligands were pre-filtered further by Lipinski\u0026rsquo;s rule of five using the QikProp module of Schr\u0026ouml;dinger to remove the false positives from the analysis\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eTarget protein preparation and Grid generation\u003c/h2\u003e \u003cp\u003eUsing the Protein Preparation Wizard in the Schrodinger suite, the target protein PDB ID: 4GIZ (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org/structure/4GIZ\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org/structure/4GIZ\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was preprocessed by implying parameters such as assigning bond orders, zero-order bonds to metal atoms, converting selenomethionine to methionine, filling in absent hydrogens, capping termini, side chains, and loops, and removing waters beyond 5\u0026Aring; distance surrounding the co-crystallized ligand [Protein Preparation Wizard; Epik, Schr\u0026ouml;dinger, LLC, New York, NY, 2021]. Only the C chain, which contains the E6 moiety, was kept in the crystal structure; the other five chains (A, B, C, D, E, and F) were removed. With the OPLS-2005 force field and a root mean square deviation (RMSD) of 0.30 \u0026Aring;, the protein's hydrogen bonds were decreased and optimized to renovate the surrounding hydrogen atoms. The Schrodinger Receptor Grid Generation module [Glide, Schr\u0026ouml;dinger, LLC, New York, NY, 2021] was utilized to create the protein grid. The exact amino acid residue number (32, 50, 53, 62, 64, 67, 70, 102, 128, 131) that makes up the binding pocket of the HPV 16 E6 protein is chosen to define the receptor grid generation module \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Using the OPLS_2005 force field, the protein atoms were fixed inside the default Van der Waals radius scaling factor of 1 \u0026Aring; with partial charge cutoff 0.25 \u0026Aring;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eMolecular docking\u003c/h2\u003e \u003cp\u003eThe docking investigations of the ligands were carried out using the Schr\u0026ouml;dinger GLIDE module [29, 30]. Using high throughput virtual screening (HTVS) and standard precision (SP) and extra precision (XP) docking with default parameters, the ligands were docked step-by-step [28, 31]. Large database VS uses HTVS as the first docking phase because it's a quick process. 10% of the final compounds were sent on to the SP docking stage after HTVS. Following SP docking, the top 10% of all compounds were taken into account and moved on to the XP docking stage. The last phase in the VS procedure is the XP docking [32].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eADME and Toxicity analysis\u003c/h2\u003e \u003cp\u003eUsing the QikProp module of the Schrodinger interface, the hit compounds' ADME (Absorption, Distribution, Metabolism, and Excretion) properties were estimated [QikProp, Schr\u0026ouml;dinger, LLC, New York, NY, 2021]. In addition to Lipinski's rule of five and Jorgensen rule of three, it is used to assess drug-likeness and pharmaceutical qualities such as molecular weight, aqueous solubility (QPlogS), octanol/water (logP), brain/blood partition coefficient (QPlogBB), CNS, hydrogen bond donors, and acceptors. Online web server tools such as Osiris property explorer (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.organic-chemistry.org/prog/peo/\u003c/span\u003e\u003cspan address=\"https://www.organic-chemistry.org/prog/peo/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and ProTox-Ⅱ algorithm (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tox-new.charite.de/protox_II/\u003c/span\u003e\u003cspan address=\"https://tox-new.charite.de/protox_II/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were utilized to forecast the toxicity profile of the hit compounds [33]. Using Osiris Property Explorer, the compounds' toxicity and drug-likeness were anticipated. The hit chemicals' potential for mutagenicity, carcinogenicity, or reproductive harm was estimated using Osiris. Their oral toxicity (LD\u003csub\u003e50\u003c/sub\u003e) was predicted using the ProTox-TM algorithm. As a unique approach to toxicity prediction, the prediction detects dangerous fragments in a molecule and is based on the similarity of compounds with known median lethal doses (LD\u003csub\u003e50\u003c/sub\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eMD Simulation and DFT calculations\u003c/h2\u003e \u003cp\u003eMolecular Dynamics (MD) simulations were used to quantify the stability of the interaction between the two target molecules in the docked complex of compounds 5, 7, and 10. These complexes were simulated via molecular dynamics using the GROMACS 5.1 program and the GROMOS-96 force field, which is crucial for protein dynamics [34, 35]. The source format for estimating the ADMET properties of relevant compounds was the SMILES (Simplified Molecular-Input Line-Entry System) format. The compounds' SMILES format was utilized and examined for pkCSM.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDe novo design of novel compounds\u003c/h2\u003e \u003cp\u003eUsing a fragment-based strategy, three new HPV 16 E6 inhibitors\u0026mdash;compounds 5, 7, and 10\u0026mdash;were created (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These three substances had good GI absorption, a favorable druglikeness score, and were determined to be non-toxic [12].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eVirtual screening of the ZINC database\u003c/h2\u003e \u003cp\u003eNine thousand hits were found when the structural data of these three new compounds was virtually screened against the ZINC database's in-trials subset. The target protein, HPV 16 E6, was initially docked with the reference molecule, luteolin, and the corresponding glide energy and score were computed. Using the Schrodinger software's GLIDE module, three virtual screening phases were applied to the molecules that were collected from the database. Approximately 952 molecules were retrieved by HTVS docking in the first step. 10% of the ligands from the HTVS result moved on to the SP docking step, yielding 96 hit molecules. In the last phase, the top 10% of highly-scoring compounds from the SP docking study were taken into consideration for XP docking. Five-hit compounds (ZINC000034853956, ZINC000001534965, ZINC000095617673, ZINC000005764481, and ZINC000071606215) demonstrated a higher glide score than the reference molecule, Luteolin, according to the XP docking data (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u0026amp; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the workflow and shows the methods taken to identify hit compounds. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displays the two-dimensional (2D) structures of the five hit molecules that were obtained.\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\u003eGlide score of screened hit molecules with reference compound, Luteolin\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\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\u003eLigand ZINC ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlide gscore (kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlide energy (kcal/mol)\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\u003eLuteolin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-33.583\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\u003eZINC000011616585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-32.880\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\u003eZINC000034853956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-10.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-41.838\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\u003eZINC000001534965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-42.657\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\u003eZINC000095617673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-39.864\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\u003eZINC000005764481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-38.549\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\u003eZINC000071606215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-42.409\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 \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStudies of interactions between screened hit compounds\u003c/h2\u003e \u003cp\u003eThe Schrodinger software's ligand interaction diagram (LID) was utilized to examine the interaction patterns of selected hit compounds. The outcomes are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Green lines represented hydrophobic contacts, while purple lines showed the presence of hydrogen bonds. The stability of ligands in the complex structure is significantly influenced by the hydrogen bond interaction. ZINC000071606215 generated five hydrogen bonds with the HPV 16 E6 protein, while ZINC000034853956 and ZINC000005764481 established four. ZINC000001534965 and ZINC000095617673, the other two compounds, demonstrated two hydrogen bonds with the HPV16 E6 protein. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the hydrogen bond interactions of screened hit compounds.\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\u003eAnalysis of hydrogen bond interactions of screened hit molecules with HPV16 E6 protein\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=\"left\" 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\u003eZINC ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo of H bonds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInteracting atoms E6 Protein-Ligand\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDistance (\u0026Aring;)\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\u003eZINC000034853956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCys 51\u0026hellip;Lig(O)\u003c/p\u003e \u003cp\u003eLig(OH)\u0026hellip; Cys 51\u003c/p\u003e \u003cp\u003eLig(NH)\u0026hellip; Cys 51\u003c/p\u003e \u003cp\u003eLig(OH)\u0026hellip; Tyr 32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003cp\u003e1.77\u003c/p\u003e \u003cp\u003e2.30\u003c/p\u003e \u003cp\u003e1.96\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\u003eZINC000001534965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArg131\u0026hellip;Lig(O)\u003c/p\u003e \u003cp\u003eSer74\u0026hellip; Lig(OH)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003cp\u003e2.12\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\u003eZINC000095617673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArg10\u0026hellip;Lig(O)\u003c/p\u003e \u003cp\u003eCys 51\u0026hellip;Lig(OH)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003cp\u003e2.34\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\u003eZINC000005764481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLig(OH)\u0026hellip; Cys 51\u003c/p\u003e \u003cp\u003eLig(OH)\u0026hellip; Gln 107\u003c/p\u003e \u003cp\u003eLig(OH)\u0026hellip; Gln 107\u003c/p\u003e \u003cp\u003eSer74\u0026hellip; Lig(OH)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003cp\u003e2.06\u003c/p\u003e \u003cp\u003e2.07\u003c/p\u003e \u003cp\u003e1.74\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\u003eZINC000071606215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCys 51\u0026hellip;Lig(O)\u003c/p\u003e \u003cp\u003eLig(OH)\u0026hellip; Cys 51\u003c/p\u003e \u003cp\u003eLig(NH)\u0026hellip; Cys 51\u003c/p\u003e \u003cp\u003eLig(OH)\u0026hellip; Tyr 32\u003c/p\u003e \u003cp\u003eArg131\u0026hellip;Lig(O)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003cp\u003e1.83\u003c/p\u003e \u003cp\u003e2.42\u003c/p\u003e \u003cp\u003e2.09\u003c/p\u003e \u003cp\u003e2.29\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=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of hydrophobic interactions of screened hit molecules with HPV16 E6 protein\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=\"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\u003eZINC ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHydrophobic interactions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMimetic interactions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo. of Mimetic interactions\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\u003eZINC000034853956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeu50, Cys51, Val53, Ala61, Ile52, Phe45, Val62, Val31, Tyr32, Leu67, Tyr70, Ile128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVal31, Tyr32, Leu50, Val62, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\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\u003eZINC000001534965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Cys66, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVal31, Tyr32, Leu50, Val62, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\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\u003eZINC000095617673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Leu100, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVal31, Tyr32, Leu50, Val62, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\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\u003eZINC000005764481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Ile52, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVal31, Tyr32, Leu50, Val62, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\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\u003eZINC000071606215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeu50, Cys51, Val53, Ala61, Val62, Phe45, Val31, Tyr32, Ile52, Leu67, Tyr70, Ile128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVal31, Tyr32, Leu50, Val62, Leu67, Tyr70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\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 \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eProperty Analysis of Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET)\u003c/h2\u003e \u003cp\u003eBecause it reduces possible dangers during clinical trials, the examination of ADMET characteristics is essential to the computer-based drug-designing process. The QikProp tool was utilized to examine the pharmacokinetic characteristics of these hit compounds, and the ProTox II server was utilized to forecast the molecules' potential for oral toxicity. All five compounds were determined to have good pharmacokinetic characteristics and oral absorption by humans, as shown by the results shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. With the exception of ZINC000005764481, all five of these compounds were projected to be harmless, and the other four all exhibited drug-like characteristics. To estimate the oral toxicity of these lead-hit compounds, the ProTox II server was utilized. It is clear from Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e's data that these five lead compounds are classified as Class 4 toxins. ZINC000005764481 displayed a negative drug-likeness score (-0.61) out of these 5 lead compounds. Positive drug-likeness scores were displayed by the remaining four compounds (ZINC000034853956, ZINC000001534965, ZINC000095617673, and ZINC000071606215). Osiris was used to assess additional toxicity characteristics such as the hit compounds' mutagenicity, irritating factor, tumorigenic potential, drug score, and drug-likeness. The four lead compounds were determined to be non-toxic and to have a positive drug likeness score, indicating that they behave like drugs and are among the most promising inhibitors of the HPV-16 E6 protein.\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\u003eADME analysis of screened hit molecules\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\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 \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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\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\u003eZINC ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCNS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDonor HB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAccpt HB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQPlog Po/w\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQPlogS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQPlog BB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eQPlogKP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003estars\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHOA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eQPlogPoct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eQPlogPw\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eSASA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eFOSA\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\u003eZINC000034853956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e368.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-2.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-4.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e22.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e15.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e661.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e223.704\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\u003eZINC000001534965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e421.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-5.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-2.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e20.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e10.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e668.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e197.518\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\u003eZINC000095617673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e369.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-5.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-3.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e20.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e11.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e674.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e111.952\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\u003eZINC000005764481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e304.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-3.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-3.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e18.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e13.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e527.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e244.519\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\u003eZINC000071606215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e368.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-2.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-1.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-5.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e22.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e14.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e643.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e234.509\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\u003eMW- Molecular weight\u003c/p\u003e \u003cp\u003eCNS-Predicted central nervous system activity on a -2 (inactive) to +\u0026thinsp;2 (active) scale\u003c/p\u003e \u003cp\u003eDonor HB \u0026ndash; Donor hydrogen bond\u003c/p\u003e \u003cp\u003eAcceptor HB- Acceptor hydrogen bond\u003c/p\u003e \u003cp\u003eQPlogPo/w-Predicted water/ octanol partition coefficient\u003c/p\u003e \u003cp\u003eQPlogS- Predicted aqueous solubility\u003c/p\u003e \u003cp\u003eQPlogBB- Predicted brain/blood partition coefficient\u003c/p\u003e \u003cp\u003eQPlogKP- Predicted skin permeability\u003c/p\u003e \u003cp\u003eStars-Number of property or descriptor values that fall outside the 95% range of similar values for known drugs\u003c/p\u003e \u003cp\u003eHOA-Human oral absorption\u003c/p\u003e \u003cp\u003eQPlogPoct- Predicted octanol/ gas partition coefficient\u003c/p\u003e \u003cp\u003eQPlogPw- Predicted water/gas partition coefficient\u003c/p\u003e \u003cp\u003eSASA- Solvent accessible surface area\u003c/p\u003e \u003cp\u003eFOSA- Hydrophobic solvent accessible surface area\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\u003eToxicity analysis of screened hit molecules\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=\"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 \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=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\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\u003eZINC ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMutagenic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTumorigenic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIrritant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReproductive\u003c/p\u003e \u003cp\u003eeffect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDruglikeness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eToxicity\u003c/p\u003e \u003cp\u003eClass\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\u003eZINC000034853956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClass 4\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\u003eZINC000001534965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClass 4\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\u003eZINC000095617673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClass 4\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\u003eZINC000071606215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClass 4\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\u003eResults of MD simulations\u003c/h2\u003e \u003cp\u003eThe docked complex of the selected compounds was subjected to MD Simulation studies in order to examine its stability in terms of molecular interactions and root mean square deviation (RMSD) over a 200 ns duration. The Protein-Ligand complex's pre- and post-analysis are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The docked complex is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, and the overlapping, un-docked protein with the Protein-Ligand complex is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eB. The green hue denotes the minor variation that resulted from the drug's impact after it bound to the target protein. The stability of the protein-peptide complexes was examined using the RMSD of the backbone atoms. The estimated average RMSD for these complexes ranged from 1.0 to 1.4 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Upon completion of the 200ns simulation, all protein-ligand complexes had attained their stable conformations. The estimated root-mean-square fluctuations (RMSF) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eD) showed some small fluctuations in the loop region. The concentration of active site residues did not change at 0.4 nm variation.\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003eA presents the results of the ZINC000001534965 Molecular Electrostatic Potential (MESP) study. Dark blue indicates the region that is most electropositive, while dark red indicates the electronegative region (which ranges from \u0026minus;\u0026thinsp;0.4241 to 0.5011). Areas in ZINC000001534965 that had a strong carbonyl group connection were found to be very electropositive, while areas that had a hydroxyphenyl ring connected to a chromen ring were found to be electronegative. Furthermore, the MESP analysis demonstrated that all molecules contained electron transport. The electron transfer that results in a complete valence shell makes the molecule more stable. Because ZINC000001534965 has fewer aromatic rings (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003eB), it is a better suited inhibitor of E6-E6AP. The ZINC000001534965's ionization potential is caused by HOMO energies (-26.542 eV), and the compounds' electron affinities are caused by LUMO energies (-27.254 eV). The HOMO region in ZINC000001534965 was dispersed over the hydroxyl and carbonyl ends, whereas the LUMO was located on the end of the aromatic ring that was connected to the other carbonyl group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003eC \u0026amp; \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). The majority of these DFT calculations support the medicinally beneficial substances.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOne of the most prevalent sexually transmitted diseases that causes cervical cancer in women is the human papillomavirus (HPV). The most common kind of cervical cancer is HPV-16. It is made up of the related protein E6AP linked to the oncogenic protein E6. HPV-transformed cells undergo cellular death when E6-E6AP is disrupted. Therefore, one of the main targets for medication research against HPV infection is the E6 pocket protein. Structure-based drug design is an effective technique for finding novel therapeutic candidates targeting significant targets. In this study, a virtual screening strategy was used to discover possible small molecule inhibitors against HPV16 E6. Based on the reference compound's docking score, five hit molecules were screened. After examining the pharmacokinetic characteristics, toxicity, and binding affinity of these five compounds, it was determined that four of them (ZINC000034853956, ZINC000001534965, ZINC000095617673, and ZINC000071606215) were the most likely to block the HPV16 E6 protein. These four molecules may serve as lead compounds in the creation of novel medications intended to cure illnesses brought on by HPV.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMA \u0026amp; VV designed the work and contributed equally in experiments, data processing article writing etc. SP, NP, GN, NP and VP are carried out coputational experiments and processed data.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENT\u003c/h2\u003e \u003cp\u003eAll authors wish to thank the management of Gokula Education Foundation, M. S. Ramaiah College of Arts, Science, and Commerce Bangalore for sponsoring this project through seed funding (Ref No: PO/CIR/2020- 21/017). We also thank the Principal, the Head of the Department, and the faculty of the Department of Microbiology of the college for their support and cooperation during the course of this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllison DB, Maleki Z (2016) HPV-related head and neck squamous cell carcinoma: An update and review. \u003cem\u003eJ Am Soc Cytopathol\u003c/em\u003e. 5(4), 203\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eForman D, de Martel C, Lacey CJ, Soerjomataram I, Lortet-Tieulent J, Bruni L, Vignat J, Ferlay J, Bray F, Plummer M, Franceschi S (2012) Global burden of human papillomavirus and related diseases. \u003cem\u003eVaccine\u003c/em\u003e. 30 (5), F12-23.\u003c/li\u003e\n\u003cli\u003eMonie A, Hung C. F, Roden R, Wu T. 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Nucleic Acids Res\u003c/em\u003e. 46(W1), W257\u0026ndash;63. \u003c/li\u003e\n\u003cli\u003eOostenbrink C, Villa A, Mark AE, van Gunsteren WF (2004)A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. \u003cem\u003eJ Comput Chem\u003c/em\u003e. 25(13), 1656-76. \u003c/li\u003e\n\u003cli\u003eSajjan R, Manikandan A, Mirza S Baig (2021) Dual Targeting of 3CLpro and PLpro of SARS-CoV-2: A Novel Structure-Based Design Approach to treat COVID-19. \u003cem\u003eCurrent Research in Structural Biology\u003c/em\u003e, 3, 9-18.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"HPV16 E6, Anti-cervical cancer, small molecule inhibitors, Virtual screening, ZINC, Molecular docking, ADME","lastPublishedDoi":"10.21203/rs.3.rs-3998798/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3998798/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHuman papillomavirus (HPV) infection is one of the most common sexually transmitted diseases. The current treatment methods consist of the use of chemotherapeutic agents or the application of surgical procedures to remove the developed tumors. The alternatives to treat HPV- associated diseases is the discovery of accessible drug-based therapies. In HPV infected cell, E6 protein complexes with E6AP to form p53 degradation complex and induce tumorigenesis. The objective of this study is to discover potential small molecule inhibitors against HPV16 E6 protein using virtual screening approach. Three novel HPV 16 E6 inhibitors viz. compound 5, compound 7 and compound 10 were designed using a fragment-based approach. The structural information of these three novel compounds was used in virtual screening against in- trials subset of ZINC database and a total of 9800 hits were identified. The obtained molecules from the database were further screened by three stages of virtual screening using GLIDE module of Schrodinger software. The results reveal that Five hit molecules (ZINC000034853956, ZINC000001534965, ZINC000095617673, ZINC000005764481 and ZINC000071606215) showed better glide score in comparison with reference molecule, Luteolin. These molecules exhibited crucial interactions with E6 protein of HPV 16. The pharmacokinetic properties of these hit molecules were analyzed using QikProp program. The results indicate that all the five molecules were found to have good pharmacokinetic properties and human oral absorption. All the five hit molecules were predicted to be no toxic and except ZINC000005764481, all other four molecules showed druglike behavior. Therefore, the four hit molecules (ZINC000034853956, ZINC000001534965, ZINC000095617673 and ZINC000071606215) can be used as lead molecules in the development of HPV 16 E6 inhibitors for treatment of HPV related diseases.\u003c/p\u003e","manuscriptTitle":"Virtually screened inhibitors for Human Papilloma Virus infections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-05 17:40:49","doi":"10.21203/rs.3.rs-3998798/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":"82996f82-0d89-4e98-86ba-7b92d06b8d0c","owner":[],"postedDate":"March 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-05T18:15:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-05 17:40:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3998798","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3998798","identity":"rs-3998798","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}