Identification of SARS-CoV-2 Main Protease Inhibitors Using Structure Based Virtual Screening and Molecular Dynamics Simulation of DrugBank Database

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly pathogenic to humans and has created an unprecedented global health care threat. Globally, intense efforts are going on to discover a vaccine or new drug molecules to control the COVID-19. However, till today, there is no effective therapeutics or treatment available for COVID-19. In this study, we aim to find out potential small molecule inhibitors for SARS-CoV-2 main protease (M-pro) from the known DrugBank database version 5.1.8. We applied structure-based virtual screening of the database containing 11875 numbers of drug candidates to identify potential hits for SARS-CoV-2 M-pro inhibitors. Seven potential inhibitors having admirable XP glide score ranging from -15.071 to -8.704 kcal/mol and good binding affinity with the active sites amino acids of M-pro were identified. The selected hits were further analyzed with 50 ns molecular dynamics (MD) simulation to examine the stability of protein-ligand complexes. The root mean square deviation and potential energy plot indicates the stability of the complexes during the 50 ns MD simulation. The MM-GBSA analysis also showed good binding energy of the selected hits (-83.2718 to -58.6618 kcal/mol). Further analysis revealed critical hydrogen bonds and hydrophobic interactions between compounds and the target protein. The compounds bind to biologically important regions of M-pro, indicating their potential to inhibit the functionality of this component.