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COVID-19 pandemic has created a healthcare crisis across the world and has put human life under life-threatening circumstances. The recent discovery of the crystallized structure of the main protease (M pro ) from SARS-CoV-2 has provided an opportunity for utilizing computational tools as an effective method for drug discovery. Targeting viral replication has remained an effective strategy for drug development. M pro  of SARS-COV-2 is the key protein in viral replication as it is involved in the processing of polyproteins to various structural and nonstructural proteins. Thus, M pro  represents a key target for the inhibition of viral replication specifically for SARS-CoV-2. We have used a virtual screening strategy by targeting M pro  against a library of commercially available compounds to identify potential inhibitors. After initial identification of hits by molecular docking-based virtual screening further MM/GBSA, predictive ADME analysis, and molecular dynamics simulation were performed. The virtual screening resulted in the identification of twenty-five top scoring structurally diverse hits that have free energy of binding (ΔG) values in the range of −26-06 (for compound AO-854/10413043) to −59.81 Kcal/mol (for compound 329/06315047). Moreover, the top-scoring hits have favorable AMDE properties as calculated using in silico algorithms. Additionally, the molecular dynamics simulation revealed the stable nature of protein-ligand interaction and provided information about the amino acid residues involved in binding. Overall, this study led to the identification of potential SARS-CoV-2 M pro  hit compounds with favorable pharmacokinetic properties. We believe that the outcome of this study can help to develop novel M pro  inhibitors to tackle this pandemic. Communicated by Ramaswamy H. Sarma

journal of biomolecular structure and dynamics

Targeting SARS-CoV-2 main protease: structure based virtual screening, in silico ADMET studies and molecular dynamics simulation for identification of potential inhibitors