Using the crystal structure of SARS-CoV-2 papain-like protease (PL pro ) as a template, we developed a pharmacophore model of functional centers of the PL pro inhibitor-binding pocket. With this model, we conducted data mining of the conformational database of FDA-approved drugs. This search identified 147 compounds that can be potential inhibitors of SARS-CoV-2 PL pro . The conformations of these compounds underwent 3D fingerprint similarity clusterization, followed by docking of possible conformers to the binding pocket of PL pro . Docking of random compounds to the binding pocket of protease was also done for comparison. Free energies of the docking interaction for the selected compounds were lower than for random compounds. The drug list obtained includes inhibitors of HIV, hepatitis C, and cytomegalovirus (CMV), as well as a set of drugs that have demonstrated some activity in MERS, SARS-CoV, and SARS-CoV-2 therapy. We recommend testing of the selected compounds for treatment of COVID-19
【저자키워드】 COVID-19, drugs repurposing, Papain-like protease, computational drug design, 【초록키워드】 Treatment, SARS-CoV-2, HIV, therapy, SARS-CoV, drug, docking, protease, MERS, FDA-approved drugs, database, free energy, Hepatitis, CMV, inhibitor, compounds, Interaction, similarity, inhibitors of SARS-CoV-2, Compound, conformation, binding pocket, random, selected, include, conducted, functional, demonstrated, these compound, conformational, 【제목키워드】 FDA-approved drug, Potential,