Multi-targeting approach for nsp3, nsp9, nsp12 and nsp15 proteins of SARS-CoV-2 by Diosmin as illustrated by molecular docking and molecular dynamics simulation methodologies.

Abstract

Novel coronavirus SARS-CoV-2 continues to spread rapidly worldwide and causing serious health and economic loss. In the absence of any effective treatment, various in-silico approaches are being explored towards the therapeutic discovery against COVID-19. Targeting multiple key enzymes of SARS-CoV-2 with a single potential drug could be an important in-silico strategy to tackle the therapeutic emergency. A number of Food and Drug Administration (FDA) approved drugs entered into clinical stages were originated from multi-target approaches with an increased rate, 16–21% between 2015 and 2017. In this study, we selected an FDA-approved library (Prestwick Chemical Library of 1520 compounds) and implemented in-silico virtual screening against multiple protein targets of SARS-CoV-2 on the Glide module of Schrödinger software (release 2020-1). Compounds were analyzed for their docking scores and the top-ranked against each targeted protein were further subjected to Molecular Dynamics (MD) simulations to assess the binding stability of ligand–protein complexes. A multi-targeting approach was optimized that enabled the analysis of several compounds’ binding efficiency with more than one protein targets. It was demonstrated that Diosmin (6) showed the highest binding affinity towards multiple targets with binding free energy (kcal/mol) values of −63.39 (nsp3); −62.89 (nsp9); −31.23 (nsp12); and −65.58 (nsp15). Therefore, our results suggests that Diosmin (6) possesses multi-targeting capability, a potent inhibitor of various non-structural proteins of SARS-CoV-2, and thus it deserves further validation experiments before using as a therapeutic against COVID-19 disease.