Molecular docking and dynamics simulations reveal the potential of anti-HCV drugs to inhibit COVID-19 main protease

Abstract

Background: Drug repurposing is the fastest effective method to provide treatment for coronavirus disease (COVID-19). Drugs that targeting a closely related virus with similar genetic material such as hepatitis C virus (HCV) and more specifically targeting a similar viral protease would be an excellent choice. Methods: In this study, we carried out a virtual screening for fifteen anti HCV drugs against COVID-19 main protease using computational molecular docking techniques. Moreover, Velpatasvir (4) and Sofosbuvir (13) drugs were further evaluated through molecular dynamics simulations followed by calculating the binding free energy using the molecular mechanics generalised born/solvent accessibility (MM-GBSA) approach. Results: The binding affinity descending order was N3 natural inhibitor (1), Velpatasvir (4), Sofosbuvir (13), Ombitasvir (3), Glecaprevir (2), Asunaprevir (8), Paritaprevir (10), Grazoprevir (11), Elbasvir (6), Ledipasvir (5), Daclatasvir (7), Pibrentasvir (9), Simeprevir (12), Dasabuvir (14), Taribavirin (16) and finally Ribavirin (15). Molecular dynamics simulation reveals that Sofosbuvir (13) has exciting properties and it was stable within the active site; it also showed good MM-GBSA compared to the natural inhibitor N3. Conclusion: Our results could be auspicious for fast repurposing of the examined drugs either alone or in combinations with each other for the treatment of the COVID-19. Furthermore, this work provides a clear spot on the structure-activity relationship (SAR) for targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease and helps the design and synthesis of new drugs in the future targeting it as well.