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In silico identification and in vitro antiviral validation of potential inhibitors against Chikungunya virus

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Abstract

The Chikungunya virus (CHIKV) has become endemic in the Africa, Asia and Indian subcontinent, with its continuous re-emergence causing a significant public health crisis. The unavailability of specific antivirals and vaccines against the virus has highlighted an urgent need for novel therapeutics. In the present study, we have identified small molecule inhibitors targeting the envelope proteins of the CHIKV to interfere with the fusion process, eventually inhibiting the cell entry of the virus particles. We employed high throughput computational screening of large datasets against two different binding sites in the E1–E2 dimer to identify potential candidate inhibitors. Among them, four high affinity inhibitors were selected to confirm their anti-CHIKV activity in the in vitro assay. Quercetin derivatives, Taxifolin and Rutin, binds to the E1–E2 dimer at different sites and display inhibition of CHIKV infection with EC50 values 3.6 μM and 87.67 μM, respectively. Another potential inhibitor with ID ChemDiv 8015-3006 binds at both the target sites and shows anti-CHIKV activity at EC50 = 41 μM. The results show dose-dependent inhibitory effects of Taxifolin, Rutin and ChemDiv 8015-3006 against the CHIKV with minimal cytotoxicity. In addition, molecular dynamics studies revealed the structural stability of these inhibitors at their respective binding sites in the E1–E2 protein. In conclusion, our study reports Taxifolin, Rutin and ChemDiv 8015-3006 as potential inhibitors of the CHIKV entry. Also, this study suggests a few potential candidate inhibitors which could serve as a template to design envelope protein specific CHIKV entry inhibitors.

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All data generated or analysed during the study are included in this published article [and its supplementary information files].

References

  1. Lumsden WHR (1955) An epidemic of virus disease in Southern Province, Tanganyika territory, in 1952–1953 II. General description and epidemiology. Trans R Soc Trop Med Hyg 49:33–57. https://doi.org/10.1016/0035-9203(55)90081-X

    Article  CAS  PubMed  Google Scholar 

  2. Chikungunya fact sheet. https://www.who.int/news-room/fact-sheets/detail/chikungunya. Accessed 21 Sep 2021

  3. Coffey LL, Failloux A-B, Weaver SC (2014) Chikungunya virus-vector interactions. Viruses 2014(6):4628–4663. https://doi.org/10.3390/V6114628

    Article  Google Scholar 

  4. Couderc T, Lecuit M (2015) Chikungunya virus pathogenesis: from bedside to bench. Antivir Res 121:120–131. https://doi.org/10.1016/J.ANTIVIRAL.2015.07.002

    Article  CAS  PubMed  Google Scholar 

  5. Cunha MS, Costa PAG, Correa IA et al (2020) Chikungunya virus: an emergent arbovirus to the South American continent and a continuous threat to the world. Front Microbiol. https://doi.org/10.3389/FMICB.2020.01297

    Article  PubMed  PubMed Central  Google Scholar 

  6. Strauss JH, Strauss EG (1994) The alphaviruses: gene expression, replication, and evolution. Microbiol Rev 58:491–562. https://doi.org/10.1128/MR.58.3.491-562.1994

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Kendall C, Khalid H, Müller M et al (2019) Structural and phenotypic analysis of Chikungunya virus RNA replication elements. Nucleic Acids Res 47:9296–9312. https://doi.org/10.1093/NAR/GKZ640

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Yap ML, Klose T, Urakami A et al (2017) Structural studies of Chikungunya virus maturation. Proc Natl Acad Sci USA 114:13703–13707. https://doi.org/10.1073/PNAS.1713166114

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Jose J, Snyder JE, Kuhn RJ (2009) A structural and functional perspective of alphavirus replication and assembly. Future Microbiol 4:837–856. https://doi.org/10.2217/FMB.09.59

    Article  CAS  PubMed  Google Scholar 

  10. Simizu B, Yamamoto K, Hashimoto K, Ogata T (1984) Structural proteins of Chikungunya virus. J Virol 51:254–258. https://doi.org/10.1128/JVI.51.1.254-258.1984

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Li L, Jose J, Xiang Y et al (2010) Structural changes of envelope proteins during alphavirus fusion. Nature 468:705–708. https://doi.org/10.1038/nature09546

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Schnierle BS (2019) Cellular attachment and entry factors for Chikungunya virus. Viruses 11:1–9. https://doi.org/10.3390/v11111078

    Article  CAS  Google Scholar 

  13. Marsh M, Helenius A (1989) Virus entry into animal cells. Adv Virus Res 36:107–151. https://doi.org/10.1016/S0065-3527(08)60583-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Song H, Zhao Z, Chai Y et al (2019) Molecular basis of arthritogenic alphavirus receptor MXRA8 binding to Chikungunya virus envelope protein. Cell 177:1714-1724.e12. https://doi.org/10.1016/j.cell.2019.04.008

    Article  CAS  PubMed  Google Scholar 

  15. van Duijl-Richter MKS, Hoornweg TE, Rodenhuis-Zybert IA, Smit JM (2015) Early events in Chikungunya virus infection—from virus cell binding to membrane fusion. Viruses 7:3647–3674. https://doi.org/10.3390/v7072792

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kielian M (2006) Class II virus membrane fusion proteins. Virology 344:38–47. https://doi.org/10.1016/J.VIROL.2005.09.036

    Article  CAS  PubMed  Google Scholar 

  17. Voss JE, Vaney MC, Duquerroy S et al (2010) Glycoprotein organization of Chikungunya virus particles revealed by X-ray crystallography. Nature 468:709–712. https://doi.org/10.1038/nature09555

    Article  CAS  PubMed  Google Scholar 

  18. Holmes AC, Basore K, Fremont DH, Diamond MS (2020) A molecular understanding of alphavirus entry. PLOS Pathog 16:e1008876. https://doi.org/10.1371/JOURNAL.PPAT.1008876

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zeng X, Mukhopadhyay S, Brooks CL (2015) Residue-level resolution of alphavirus envelope protein interactions in pH-dependent fusion. Proc Natl Acad Sci USA 112:2034–2039. https://doi.org/10.1073/PNAS.1414190112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kuo S-C, Chen Y-J, Wang Y-M et al (2012) Cell-based analysis of Chikungunya virus E1 protein in membrane fusion. J Biomed Sci 19:44. https://doi.org/10.1186/1423-0127-19-44

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Verma J, Subbarao N, Rajala MS (2020) Envelope proteins as antiviral drug target. J Drug Target. https://doi.org/10.1080/1061186X.2020.1792916

    Article  PubMed  Google Scholar 

  22. Weber Christopher, Sliva Katja, von Rhein Christine et al (2015) The green tea catechin, epigallocatechin gallate inhibits Chikungunya virus infection. Antivir Res 113:1–3. https://doi.org/10.1016/J.ANTIVIRAL.2014.11.001

    Article  CAS  PubMed  Google Scholar 

  23. Khan M, Santhosh SR, Tiwari M et al (2010) Assessment of in vitro prophylactic and therapeutic efficacy of chloroquine against Chikungunya virus in vero cells. J Med Virol 82:817–824. https://doi.org/10.1002/jmv.21663

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Delogu I, Pastorino B, Baronti C et al (2011) In vitro antiviral activity of arbidol against Chikungunya virus and characteristics of a selected resistant mutant. Antivir Res 90:99–107. https://doi.org/10.1016/j.antiviral.2011.03.182

    Article  CAS  PubMed  Google Scholar 

  25. Mounce BC, Cesaro T, Carrau L et al (2017) Curcumin inhibits Zika and Chikungunya virus infection by inhibiting cell binding. Antivir Res 142:148–157. https://doi.org/10.1016/j.antiviral.2017.03.014

    Article  CAS  PubMed  Google Scholar 

  26. Haese N, Powers J, Streblow DN (2020) Small molecule inhibitors targeting Chikungunya. Virus. https://doi.org/10.1007/82_2020_195

    Article  Google Scholar 

  27. Kovacikova K, van Hemert MJ (2020) Small-molecule inhibitors of Chikungunya virus: mechanisms of action and antiviral drug resistance. Antimicrob Agents Chemother. https://doi.org/10.1128/AAC.01788-20

    Article  PubMed  PubMed Central  Google Scholar 

  28. Deeba F, Malik MZ, Naqvi IH et al (2017) Potential entry inhibitors of the envelope protein (E2) of Chikungunya virus: in silico structural modeling, docking and molecular dynamic studies. VirusDisease 28:39–49. https://doi.org/10.1007/s13337-016-0356-2

    Article  PubMed  PubMed Central  Google Scholar 

  29. Rashad Adel A, Keller Paul A (2013) Structure based design towards the identification of novel binding sites and inhibitors for the Chikungunya virus envelope proteins. J Mol Graph Model 44:241–252. https://doi.org/10.1016/J.JMGM.2013.07.001

    Article  CAS  PubMed  Google Scholar 

  30. Ho Y-J, Wang Y-M, Lu J et al (2015) Suramin inhibits Chikungunya virus entry and transmission. PLoS ONE 10:e0133511. https://doi.org/10.1371/JOURNAL.PONE.0133511

    Article  PubMed  PubMed Central  Google Scholar 

  31. RCSB PDB - 3N42: crystal structures of the mature envelope glycoprotein complex (furin cleavage) of Chikungunya virus. https://www.rcsb.org/structure/3N42. Accessed 21 Sep 2021

  32. Nguyen PTV, Yu H, Keller PA (2017) Molecular docking studies to explore potential binding pockets and inhibitors for Chikungunya virus envelope glycoproteins. Interdiscip Sci Comput Life Sci 103(10):515–524. https://doi.org/10.1007/S12539-016-0209-0

    Article  Google Scholar 

  33. Irwin JJ, Shoichet BK (2004) ZINC—a free database of commercially available compounds for virtual screening. J Chem Inf Model. https://doi.org/10.1021/CI049714+

    Article  Google Scholar 

  34. DrugBank Online | Database for Drug and Drug Target Info. https://go.drugbank.com/. Accessed 21 Sep 2021

  35. Wishart DS, Feunang YD, Guo AC et al (2018) DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 46:D1074–D1082. https://doi.org/10.1093/NAR/GKX1037

    Article  CAS  PubMed  Google Scholar 

  36. Schrödinger Release 2021-4: LigPrep, Schrödinger, LLC, New York, NY, 2021

  37. Shelley JC, Cholleti A, Frye LL et al (2007) Epik: a software program for pKa prediction and protonation state generation for drug-like molecules. J Comput Aided Mol Des 21:681–691. https://doi.org/10.1007/s10822-007-9133-z

    Article  CAS  PubMed  Google Scholar 

  38. Schrödinger Release 2021-3: Epik, Schrödinger, LLC, New York, NY, 2021

  39. Schrödinger Release 2021-4: Glide, Schrödinger, LLC, New York, NY, 2021

  40. Friesner RA, Banks JL, Murphy RB et al (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749. https://doi.org/10.1021/jm0306430

    Article  CAS  PubMed  Google Scholar 

  41. Halgren TA, Murphy RB, Friesner RA et al (2004) Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem 47:1750–1759. https://doi.org/10.1021/jm030644s

    Article  CAS  PubMed  Google Scholar 

  42. Protein Preparation Wizard | Schrödinger. https://www.schrodinger.com/protein-preparation-wizard. Accessed 28 Oct 2020

  43. Houston DR, Walkinshaw MD (2013) Consensus docking: improving the reliability of docking in a virtual screening context. J Chem Inf Model 53:384–390. https://doi.org/10.1021/ci300399w

    Article  CAS  PubMed  Google Scholar 

  44. Wang R, Lai L, Wang S (2002) Further development and validation of empirical scoring functions for structure-based binding affinity prediction. J Comput Aided Mol Des 16:11–26. https://doi.org/10.1023/A:1016357811882

    Article  CAS  PubMed  Google Scholar 

  45. Laskowski RA, Swindells MB (2011) LigPlot+: multiple ligand-protein interaction diagrams for drug discovery. J Chem Inf Model 51:2778–2786. https://doi.org/10.1021/ci200227u

    Article  CAS  PubMed  Google Scholar 

  46. PyMOL open source—BioGrids consortium—supported software. https://biogrids.org/software/titles/pymol-open-source. Accessed 28 Oct 2020

  47. Shrinet J, Jain S, Sharma A et al (2012) Genetic characterization of Chikungunya virus from New Delhi reveal emergence of a new molecular signature in Indian isolates. Virol J 91(9):1–8. https://doi.org/10.1186/1743-422X-9-100

    Article  CAS  Google Scholar 

  48. Jain J, Pai S, Sunil S (2018) Standardization of in vitro assays to evaluate the activity of polyherbal siddha formulations against Chikungunya virus infection. VirusDisease 29(1):32–39

    Article  Google Scholar 

  49. Berendsen HJC, van der Spoel D, van Drunen R (1995) GROMACS: a message-passing parallel molecular dynamics implementation. Comput Phys Commun 91:43–56. https://doi.org/10.1016/0010-4655(95)00042-E

    Article  CAS  Google Scholar 

  50. Hornak V, Abel R, Okur A et al (2006) Comparison of multiple amber force fields and development of improved protein backbone parameters. Proteins Struct Funct Genet 65:712–725

    Article  CAS  Google Scholar 

  51. Sousa Da Silva AW, Vranken WF (2012) ACPYPE—AnteChamber PYthon Parser interfacE. BMC Res Notes. https://doi.org/10.1186/1756-0500-5-367

    Article  PubMed  PubMed Central  Google Scholar 

  52. Acpype Server. http://bio2byte.be/acpype/. Accessed 28 Oct 2020

  53. Mahoney MW, Jorgensen WL (2000) A five-site model for liquid water and the reproduction of the density anomaly by rigid, nonpolarizable potential functions. J Chem Phys 112:8910–8922. https://doi.org/10.1063/1.481505

    Article  CAS  Google Scholar 

  54. Boehr David D, Nussinov Ruth, Wright Peter E (2009) The role of dynamic conformational ensembles in biomolecular recognition. Nat Chem Biol 5:789–796. https://doi.org/10.1038/NCHEMBIO.232

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Menaa F, Menaa A, Tréton J (2014) Polyphenols against skin aging. Polyphenols in human health and disease. Academic Press, Cambridge, pp 819–830

    Chapter  Google Scholar 

  56. Sunil C, Xu B (2019) An insight into the health-promoting effects of taxifolin (dihydroquercetin). Phytochemistry 166:112066. https://doi.org/10.1016/J.PHYTOCHEM.2019.112066

    Article  CAS  PubMed  Google Scholar 

  57. Cai C, Liu C, Zhao L et al (2018) Effects of taxifolin on osteoclastogenesis in vitro and in vivo. Front Pharmacol. https://doi.org/10.3389/FPHAR.2018.01286

    Article  PubMed  PubMed Central  Google Scholar 

  58. Topal F, Nar M, Gocer H et al (2015) Antioxidant activity of taxifolin: an activity–structure relationship. J Enzyme Inhib Med Chem 31:674–683. https://doi.org/10.3109/14756366.2015.1057723

    Article  CAS  PubMed  Google Scholar 

  59. Bernatova I, Liskova S (2021) Mechanisms modified by (−)-epicatechin and taxifolin relevant for the treatment of hypertension and viral infection: knowledge from preclinical studies. Antioxidants 10:467. https://doi.org/10.3390/ANTIOX10030467

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Khan MM, Ahmad A, Ishrat T et al (2009) Rutin protects the neural damage induced by transient focal ischemia in rats. Brain Res 1292:123–135. https://doi.org/10.1016/J.BRAINRES.2009.07.026

    Article  CAS  PubMed  Google Scholar 

  61. Machado DG, Bettio LEB, Cunha MP et al (2008) Antidepressant-like effect of rutin isolated from the ethanolic extract from Schinus molle L. in mice: evidence for the involvement of the serotonergic and noradrenergic systems. Eur J Pharmacol 587:163–168. https://doi.org/10.1016/J.EJPHAR.2008.03.021

    Article  CAS  PubMed  Google Scholar 

  62. Qian BJ, Wu CF, Lu MM et al (2017) Effect of complexes of cyanidin-3-diglucoside-5-glucoside with rutin and metal ions on their antioxidant activities. Food Chem 232:545–551. https://doi.org/10.1016/J.FOODCHEM.2017.04.010

    Article  CAS  PubMed  Google Scholar 

  63. Ibrahim AK, Youssef AI, Arafa AS, Ahmed SA (2013) Anti-H5N1 virus flavonoids from Capparis sinaica Veill. Nat Prod Res 27:2149–2153. https://doi.org/10.1080/14786419.2013.790027

    Article  CAS  PubMed  Google Scholar 

  64. Chéron N, Yu C, Kolawole AO et al (2015) Repurposing of rutin for the inhibition of norovirus replication. Arch Virol 1609(160):2353–2358. https://doi.org/10.1007/S00705-015-2495-Y

    Article  Google Scholar 

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Acknowledgements

We acknowledge the financial assistance provided by the University Grant Commission in the form of Junior Research Fellowship (JRF) to Jyoti Verma and DBT JRF fellowship to Abdul Hasan. ICGEB Core funds from ICGEB to SS is duly acknowledged.

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No funding or grant was received for conducting this study.

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Authors and Affiliations

  1. School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India

    Jyoti Verma & Naidu Subbarao

  2. Vector Borne Diseases Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, India

    Abdul Hasan & Sujatha Sunil

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  1. Jyoti Verma
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  2. Abdul Hasan
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  3. Sujatha Sunil
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  4. Naidu Subbarao
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Contributions

The in silico work was designed and carried out by JV and NS. The in vitro experimental study was designed and performed by AH and SS. All the authors contributed to manuscript writing. All authors read and approve the final manuscript.

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Correspondence to Sujatha Sunil or Naidu Subbarao.

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Verma, J., Hasan, A., Sunil, S. et al. In silico identification and in vitro antiviral validation of potential inhibitors against Chikungunya virus. J Comput Aided Mol Des 36, 521–536 (2022). https://doi.org/10.1007/s10822-022-00463-4

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