Structure-based computational screening of 470 natural quercetin derivatives for identification of SARS-CoV-2 M^pro inhibitor.

ABSTRACT: Coronavirus disease 2019 (COVID-19) is a global pandemic infecting the respiratory system through a notorious virus known as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to viral mutations and the risk of drug resistance, it is crucial to identify new molecules having potential prophylactic or therapeutic effect against SARS-CoV-2 infection. In the present study, we aimed to identify a potential inhibitor of SARS-CoV-2 through virtual screening of a compound library of 470 quercetin derivatives by targeting the main protease-Mpro (PDB ID: 6LU7). The study was carried out with computational techniques such as molecular docking simulation studies (MDSS), molecular dynamics (MD) simulations, and molecular mechanics generalized Born surface area (MMGBSA) techniques. Am

SUBMITTER: Kakhar Umar A 

PROVIDER: S-EPMC10022500 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature