Computational Studies to Identify Potential Main Protease Inhibitors for SARS-CoV-2

Abstract

<jats:p>The Coronavirus pandemic has put the entire humanity in total shock and has forced the world to go under total lockdown. It is time for the entire scientific community across the globe to find a solution for this deadly and unseen enemy. In silico studies play a vital role in situations like this, as experimental studies are not feasible by all researchers particularly with relevance to BSL4 procedures. In this study, using the high resolution crystal structure of SARS-CoV-2 main protease (PDB: 5R82), we have identified molecules which can potentially inhibit the main protease (Mpro). We used a three-tier docking protocol making use of three different databases. We analysed the residues which are lying near the ligand binding pocket of the main protease structure and it shows a wide cavity, which can accommodate chemically diverse ligands, occupying different sub-pockets. Using the small fragment bound in the 5R82, we have identified several larger molecules whose functional groups make interactions with the active site residues covering. This study also presumably steers the structure determination of many ligand-main protease complexes using x- ray diffraction methods. These molecules can be used as ‘in silico leads’ and further be explored in the development of SARS-CoV-2 drugs.</jats:p>