Litcius/Paper detail

Potential anti‐SARS‐CoV‐2 drug candidates identified through virtual screening of the ChEMBL database for compounds that target the main coronavirus protease

Motonori Tsuji

2020FEBS Open Bio76 citationsDOIOpen Access PDF

Abstract

A novel coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), or 2019 novel coronavirus] has been identified as the pathogen of coronavirus disease 2019. The main protease (M pro , also called 3‐chymotrypsin‐like protease) of SARS‐CoV‐2 is a potential target for treatment of COVID‐19. A M pro homodimer structure suitable for docking simulations was prepared using a crystal structure (PDB ID: 6Y2G ; resolution 2.20 Å). Structural refinement was performed in the presence of peptidomimetic α‐ketoamide inhibitors, which were previously disconnected from each Cys145 of the M pro homodimer, and energy calculations were performed. Structure‐based virtual screenings were performed using the ChEMBL database. Through a total of 1 485 144 screenings, 64 potential drugs (11 approved, 14 clinical, and 39 preclinical drugs) were predicted to show high binding affinity with M pro . Additional docking simulations for predicted compounds with high binding affinity with M pro suggested that 28 bioactive compounds may have potential as effective anti‐SARS‐CoV‐2 drug candidates. The procedure used in this study is a possible strategy for discovering anti‐SARS‐CoV‐2 drugs from drug libraries that may significantly shorten the clinical development period with regard to drug repositioning.

Topics & Concepts

chEMBLProteaseVirtual screeningCoronavirusProtein Data Bank (RCSB PDB)Docking (animal)PeptidomimeticDrug repositioningSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Drug discoveryChemistryDrugCoronavirus disease 2019 (COVID-19)Antiviral drugComputational biologyPharmacologyVirologyBiologyMedicineBiochemistryEnzymeInfectious disease (medical specialty)PeptideDiseaseNursingPathologyComputational Drug Discovery MethodsSARS-CoV-2 and COVID-19 Researchvaccines and immunoinformatics approaches