In the rapidly evolving coronavirus disease (COVID-19) pandemic, repurposing existing drugs and evaluating commercially available inhibitors against druggable targets of the virus could be an effective strategy to accelerate the drug discovery process. The 3C-Like proteinase (3CL pro ) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified as an important drug target due to its role in viral replication. The lack of a potent 3CL pro inhibitor and the availability of the X-ray crystal structure of 3CL pro (PDB-ID 6LU7) motivated us to perform computational studies to identify commercially available potential inhibitors. A combination of modeling studies was performed to identify potential 3CL pro inhibitors from the protease inhibitor database MEROPS ( https://www.ebi.ac.uk/merops/index.shtml ). Binding energy evaluation identified key residues for inhibitor design. We found 15 potential 3CL pro inhibitors with higher binding affinity than that of an α-ketoamide inhibitor determined via X-ray structure. Among them, saquinavir and three other investigational drugs aclarubicin, TMC-310911, and faldaprevir could be suggested as potential 3CL pro inhibitors. We recommend further experimental investigation of these compounds.
【저자키워드】 Virtual drug screening, Computational models, 【초록키워드】 COVID-19, coronavirus disease, SARS-CoV-2, coronavirus, pandemic, Drug discovery, drug, 3CL pro, virus, inhibitors, database, binding affinity, Replication, Protease inhibitor, X-ray, drug target, target, inhibitor, Combination, acute respiratory syndrome, Computational study, residue, 6LU7, these compounds, proteinase, effective, TMC-310911, identify, lack, was performed, in viral, suggested, accelerate, aclarubicin, MEROPS, 【제목키워드】 COVID-19, molecular docking, Molecular dynamics simulation, Protease inhibitor, approach,