In-silico pharmacophoric and molecular docking-based drug discovery against the Main Protease (Mpro) of SARS-CoV-2, a causative agent COVID-19.

COVID-19 (Coronavirus Disease 2019) caused by a novel 'SARS-CoV-2' virus resulted in public health emergencies across the world. An effective vaccine to cure this virus is not yet available, thus requires concerted efforts at various scales. In this study, we employed Computer-Aided Drug Design (CADD) based approach to identify the drug-like compounds - inhibiting the replication of the main protease (M) of SARS-CoV-2. Our database search using an online tool "ZINC pharmer" retrieved ~1500 compounds based on pharmacophore features. Lipinski's rule was applied to further evaluate the drug-like compounds, followed by molecular docking-based screening, and the selection of screening ligand complex with M based on S-score (higher than reference inhibitor) and root-mean-square deviation (RMSD) value (less than reference inhibitor) using AutoDock 4.2. Resultantly, ~200 compounds were identified having strong interaction with M of SARS-CoV-2. After evaluating their binding energy using the AutoDock 4.2 software, three compounds (ZINC20291569, ZINC90403206, ZINC95480156) were identified that showed highest binding energy with M of SARS-CoV-2 and strong inhibition effect than the N3 (reference inhibitor). A good binding energy, drug likeness and effective pharmacokinetic parameters suggest that these candidates have greater potential to stop the replication of SARS-CoV-2, hence might lead to the cure of COVID-19.