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

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. Among the natural derivatives, compound 382 (PubChem CID 65604) showed the best binding affinity to Mpro (-11.1 kcal/mol). Compound 382 interacted with LYS5, TYR126, GLN127, LYS137, ASP289, PHE291, ARG131, SER139, GLU288, and GLU290 of the Mpro protein. The SARS-CoV-2 Mpro-382 complex showed acceptable stability during the 100 ns MD simulations. The SARS-CoV-2 Mpro-382 complex also showed an MM-GBSA binding free energy value of -54.0 kcal/mol. The binding affinity, stability, and free energy results for 382 and Mpro were better than those of the native ligand and the standard inhibitors ledipasvir and cobicistat. The conclusion of our study was that compound 382 has the potential to inhibit SARS-Cov-2 Mpro. However, further investigations such as