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Volume 69, Issue 6

Potential RNA-dependent RNA polymerase inhibitors as prospective therapeutics against SARS-CoV-2 Open Access

Abstract

The emergence of SARS-CoV-2 has taken humanity off guard. Following an outbreak of SARS-CoV in 2002, and MERS-CoV about 10 years later, SARS-CoV-2 is the third coronavirus in less than 20 years to cross the species barrier and start spreading by human-to-human transmission. It is the most infectious of the three, currently causing the COVID-19 pandemic. No treatment has been approved for COVID-19. We previously proposed targets that can serve as binding sites for antiviral drugs for multiple coronaviruses, and here we set out to find current drugs that can be repurposed as COVID-19 therapeutics.

To identify drugs against COVID-19, we performed an virtual screen with the US Food and Drug Administration (FDA)-approved drugs targeting the RNA-dependent RNA polymerase (RdRP), a critical enzyme for coronavirus replication.

Initially, no RdRP structure of SARS-CoV-2 was available. We performed basic sequence and structural analysis to determine if RdRP from SARS-CoV was a suitable replacement. We performed molecular dynamics simulations to generate multiple starting conformations that were used for the virtual screen. During this work, a structure of RdRP from SARS-CoV-2 became available and was also included in the virtual screen.

The virtual screen identified several drugs predicted to bind in the conserved RNA tunnel of RdRP, where many of the proposed targets were located. Among these candidates, quinupristin is particularly interesting because it is expected to bind across the RNA tunnel, blocking access from both sides and suggesting that it has the potential to arrest viral replication by preventing viral RNA synthesis. Quinupristin is an antibiotic that has been in clinical use for two decades and is known to cause relatively minor side effects.

Quinupristin represents a potential anti-SARS-CoV-2 therapeutic. At present, we have no evidence that this drug is effective against SARS-CoV-2 but expect that the biomedical community will expeditiously follow up on our findings.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): broadly neutralizing antivirals , docking , protein evolution and sequence analysis
© 2020 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. The Microbiology Society waived the open access fees for this article.
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2020-05-29
2024-04-24
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References

  1. Salata C, Calistri A, Parolin C, Palù G. Coronaviruses: a paradigm of new emerging zoonotic diseases. Pathog Dis 2019; 77: [View Article]
     [Google Scholar]
  2. Chan JF-W, Yuan S, Kok K-H, To KK-W, Chu H et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. The Lancet 2020; 395:514–523 [View Article]
     [Google Scholar]
  3. Coronaviridae Study Group of the International Committee on Taxonomy of Viruses The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol 20201–9
     [Google Scholar]
  4. de Wit E, van Doremalen N, Falzarano D, Munster VJ. Sars and MERS: recent insights into emerging coronaviruses. Nat Rev Microbiol 2016; 14:523–534 [View Article]
     [Google Scholar]
  5. de Wit E, Feldmann F, Cronin J, Jordan R, Okumura A et al. Prophylactic and therapeutic remdesivir (GS-5734) treatment in the rhesus macaque model of MERS-CoV infection. Proc Natl Acad Sci U S A 2020; 117:6771–6776 [View Article][PubMed]
     [Google Scholar]
  6. Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis
     [Google Scholar]
  7. Rahaman J, Siltberg-Liberles J. Avoiding regions symptomatic of conformational and functional flexibility to identify antiviral targets in current and future coronaviruses. Genome Biol Evol 2016; 8:3471–3484 [View Article]
     [Google Scholar]
  8. Fehr AR, Perlman S. Coronaviruses: An overview of their replication and pathogenesis. Coronaviruses: Methods and Protocols New York: Springer; 2015 pp 1–23
     [Google Scholar]
  9. Kirchdoerfer RN, Ward AB. Structure of the SARS-CoV nsp12 polymerase bound to nsp7 and nsp8 co-factors. Nat Commun 2019; 10: [View Article]
     [Google Scholar]
  10. Gao Y, Yan L, Huang Y, Liu F, Zhao Y et al. Structure of the RNA-dependent RNA polymerase from COVID-19 virus. Science 2020eabb7498 [View Article]
     [Google Scholar]
  11. Stein GE. Safety of newer parenteral antibiotics. Clin Infect Dis 2005; 41:S293–S302 [View Article]
     [Google Scholar]
  12. Waterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ. Jalview Version 2--a multiple sequence alignment editor and analysis workbench. Bioinformatics 2009; 25:1189–1191 [View Article]
     [Google Scholar]
  13. Guindon S, Dufayard J-F, Lefort V, Anisimova M, Hordijk W et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 2010; 59:307–321 [View Article]
     [Google Scholar]
  14. Lefort V, Longueville J-E, Gascuel O. Sms: smart model selection in PhyML. Mol Biol Evol 2017; 34:2422–2424 [View Article]
     [Google Scholar]
  15. Edgar RC. Muscle: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004; 32:1792–1797 [View Article]
     [Google Scholar]
  16. Madeira F, Park YM, Lee J, Buso N, Gur T et al. The EMBL-EBI search and sequence analysis tools Apis in 2019. Nucleic Acids Res 2019; 47:W636–W641 [View Article][PubMed]
     [Google Scholar]
  17. DeLano WL. The PyMOL molecular graphics system, Schrödinger, LLC.
  18. Vertrees J. FindSurfaceResidues - PyMOLWiki. https://pymolwiki.org/index.php/FindSurfaceResidues (accessed 19 March 2020).
  19. Yang H, Yang M, Ding Y, Liu Y, Lou Z et al. The crystal structures of severe acute respiratory syndrome virus main protease and its complex with an inhibitor. Proc Natl Acad Sci U S A 2003; 100:13190–13195 [View Article]
     [Google Scholar]
  20. Jia Z, Yan L, Ren Z, Wu L, Wang J et al. Delicate structural coordination of the severe acute respiratory syndrome coronavirus Nsp13 upon ATP hydrolysis. Nucleic Acids Res 2019; 47:6538–6550 [View Article]
     [Google Scholar]
  21. Ma Y, Wu L, Shaw N, Gao Y, Wang J et al. Structural basis and functional analysis of the SARS coronavirus nsp14–nsp10 complex. Proc Natl Acad Sci U S A 2015; 112:9436–9441 [View Article]
     [Google Scholar]
  22. Lee J, Cheng X, Swails JM, Yeom MS, Eastman PK et al. CHARMM-GUI input generator for NAMD, GROMACS, amber, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J Chem Theory Comput 2016; 12:405–413 [View Article]
     [Google Scholar]
  23. Sandhaus S, Chapagain PP, Tse-Dinh Y-C. Discovery of novel bacterial topoisomerase I inhibitors by use of in silico docking and in vitro assays. Sci Rep 2018; 8:1–9 [View Article]
     [Google Scholar]
  24. Huang J, Rauscher S, Nawrocki G, Ran T, Feig M et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat Methods 2016
     [Google Scholar]
  25. Jiang W, Hardy DJ, Phillips JC, MacKerell AD, Schulten K et al. High-Performance scalable molecular dynamics simulations of a polarizable force field based on classical drude oscillators in NAMD. J Phys Chem Lett 2011; 2:87–92 [View Article]
     [Google Scholar]
  26. Darden T, Perera L, Li L, Pedersen L, Lee P. New tricks for modelers from the crystallography toolkit: the particle mesh Ewald algorithm and its use in nucleic acid simulations. Structure 1999; 7:R55–R60 [View Article]
     [Google Scholar]
  27. Elber R, Ruymgaart AP, Hess B. Shake parallelization. Eur Phys J Spec Top 2011; 200:211–223 [View Article][PubMed]
     [Google Scholar]
  28. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. J Mol Graph 1996; 14:33–38 [View Article]
     [Google Scholar]
  29. Trott O, Olson AJ. Autodock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and Multithreading. J Comput Chem 2010; 31:455–461
     [Google Scholar]
  30. Pihan E, Colliandre L, Guichou J-F, Douguet D. e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design. Bioinformatics 2012; 28:1540–1541 [View Article]
     [Google Scholar]
  31. O'Boyle NM, Banck M, James CA, Morley C, Vandermeersch T et al. Open Babel: an open chemical toolbox. J Cheminform 2011; 3: [View Article]
     [Google Scholar]
  32. Drexler JF, Gloza-Rausch F, Glende Jörg, Corman VM, Muth D et al. Genomic characterization of severe acute respiratory syndrome-related coronavirus in European bats and classification of coronaviruses based on partial RNA-dependent RNA polymerase gene sequences. J Virol 2010; 84:11336–11349 [View Article]
     [Google Scholar]
  33. Asthana S, Shukla S, Vargiu AV, Ceccarelli M, Ruggerone P et al. Different molecular mechanisms of inhibition of bovine viral diarrhea virus and hepatitis C virus RNA-dependent RNA polymerases by a novel benzimidazole. Biochemistry 2013; 52:3752–3764 [View Article]
     [Google Scholar]
  34. Velkov T, Carbone V, Akter J, Sivanesan S, Li J et al. The RNA-Dependent-RNA polymerase, an emerging antiviral drug target for the Hendra virus. Curr Drug Targets 2014; 15:103–113 [View Article]
     [Google Scholar]
  35. Bhatia HK, Singh H, Grewal N, Natt NK. Sofosbuvir: a novel treatment option for chronic hepatitis C infection. J Pharmacol Pharmacother 2014; 5:278–284
     [Google Scholar]
  36. Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res 2008; 36:D901–D906 [View Article][PubMed]
     [Google Scholar]
  37. Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 2018; 46:D1074–D1082 [View Article]
     [Google Scholar]
  38. Campbell EA, Korzheva N, Mustaev A, Murakami K, Nair S et al. Structural mechanism for rifampicin inhibition of bacterial RNA polymerase. Cell 2001; 104:901–912 [View Article]
     [Google Scholar]
  39. Harms JM, Schlünzen F, Fucini P, Bartels H, Yonath A. Alterations at the peptidyl transferase centre of the ribosome induced by the synergistic action of the streptogramins dalfopristin and quinupristin. BMC Biol 2004; 2:4–10 [View Article]
     [Google Scholar]
  40. Ma C, Yang X, Lewis PJ. Bacterial transcription as a target for antibacterial drug development. Microbiol Mol Biol Rev 2016; 80:139–160 [View Article]
     [Google Scholar]
  41. Lee C-Y, Huang C-H, Lu P-L, Ko W-C, Chen Y-H et al. Role of rifampin for the treatment of bacterial infections other than mycobacteriosis. J Infect 2017; 75:395–408 [View Article][PubMed]
     [Google Scholar]
  42. Graifer D, Karpova G. Roles of ribosomal proteins in the functioning of translational machinery of eukaryotes. Biochimie 2015; 109:1–17 [View Article]
     [Google Scholar]
  43. Pfizer SYNERCID- quinupristin and dalfopristin injection, powder, lyophilized, for solution. http://labeling.pfizer.com/ShowLabeling.aspx?id=712 (accessed 25 March 2020).
  44. Holmes NE, Tong SYC, Davis JS, van Hal SJ, Hal S. Treatment of methicillin-resistant Staphylococcus aureus: vancomycin and beyond. Semin Respir Crit Care Med 2015; 36:017–030 [View Article][PubMed]
     [Google Scholar]
  45. Brown J, Freeman BB. Combining Quinupristin/Dalfopristin with other agents for resistant infections. Ann Pharmacother 2004; 38:677–685 [View Article]
     [Google Scholar]
  46. Cheng VCC, Lau SKP, Woo PCY, Yuen KY. Severe acute respiratory syndrome coronavirus as an agent of emerging and reemerging infection. Clin Microbiol Rev 2007; 20:660–694 [View Article][PubMed]
     [Google Scholar]
  47. Pushpakom S, Iorio F, Eyers PA, Jane Escott K, Hopper S et al. Drug repurposing: progress, challenges and recommendations. Nat Publ Gr 2018
     [Google Scholar]
  48. Maximova T, Moffatt R, Ma B, Nussinov R, Shehu A. Principles and overview of sampling methods for modeling macromolecular structure and dynamics. PLoS Comput Biol 2016; 12:e1004619 [View Article]
     [Google Scholar]
  49. Tchesnokov E, Feng J, Porter D, Götte M. Mechanism of inhibition of ebola virus RNA-dependent RNA polymerase by remdesivir. Viruses 11:326 [View Article]
     [Google Scholar]
  50. Kupferschmidt K. Who launches global megatrial of the four most promising coronavirus treatments. Science 2020 [View Article]
     [Google Scholar]
  51. Zhou F, Yu T, Du R, Fan G, Liu Y et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. The Lancet 2020; 395:1054–1062 [View Article]
     [Google Scholar]
  52. Campbell EA, Pavlova O, Zenkin N, Leon F, Irschik H et al. Structural, functional, and genetic analysis of sorangicin inhibition of bacterial RNA polymerase. Embo J 2005; 24:674–682 [View Article]
     [Google Scholar]
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Potential RNA-dependent RNA polymerase inhibitors as prospective therapeutics against SARS-CoV-2
J. Med. Microbiol. 69, 864 (2020); https://doi.org/10.1099/jmm.0.001203
/content/journal/jmm/10.1099/jmm.0.001203
/content/journal/jmm/10.1099/jmm.0.001203
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