Virtual screening, drug-likeness analysis, and molecular docking study of potential severe acute respiratory syndrome coronavirus 2 main protease inhibitors

Virtual screening, drug-likeness analysis, and molecular docking study of potential severe acute respiratory syndrome coronavirus 2 main protease inhibitors

Due to the length of time required to develop specific antiviral agents, the World Health Organization adopted the strategy of repurposing existing medications to treat Coronavirus disease 2019 infection. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease is possible biological target for potential antiviral drugs. We selected various compounds from PubChem database based on the structure of main protease inhibitors in Protein Data Bank database. Ten compounds showed nontumorigenic and nonmutagenic potential and met Egan’s and Lipinski’s rules. Molecular docking analysis was performed using AutoDock Vina software. Based on number and type of key binding interactions, as well as docking scores, we selected compounds 6, 8, and 17 that demonstrated the highest binding affinity for the target protein. Molecular dynamics simulations were then carried out on the protein-top docked ligand complexes which were subjected to molecular mechanics/generalized Born and surface area calculations. The molecular dynamics simulation results indicated that protein-top docked ligand complexes showed good conformational stability. Among analyzed molecules, compound 17 emerged as the best in silico hit based on the docking score, MM/GBSA binding energy and MD results.

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