In silico prediction of mozenavir as a potential drug for SARS-CoV-2 infection via binding multiple drug targets

Abstract

Since the epidemic began in November 2019, no viable medicine against SARS-CoV-2 has been discovered. The typical medication discovery strategy requires several years of rigorous research and development as well as a significant financial commitment, which is not feasible in the face of the current epidemic. Through molecular docking and dynamic simulation studies, we used the FDA-approved drug mezonavir against the most important viral targets, including spike (S) glycoprotein, Transmembrane serine protease 2 (TMPRSS2), RNA-dependent RNA polymerase (RdRp), Main protease (Mpro), human angiotensin-converting enzyme 2 (ACE-2), and furin. These targets are critical for viral replication and infection propagation because they play a key role in replication/transcription and host cell recognition. Molecular docking revealed that the antiviral medication mozenavir showed a stronger affinity for SARS-CoV-2 target proteins than reference medicines in this investigation. We discovered that mozenavir increases the complex's stability and validates the molecular docking findings using molecular dynamics modeling. Furin, a target protein of COVID-19, has a greater binding affinity (-12.04 kcal/mol) than other COVID-19 target proteins, forming different hydrogen bonds and polar and hydrophobic interactions, suggesting that it might be used as an antiviral treatment against SARS-CoV-2. Overall, the present in silico results will be valuable in identifying crucial targets for subsequent experimental investigations that might help combat COVID-19 by blocking the protease furin's proteolytic activity.