Middle east respiratory syndrome coronavirus (MERS-CoV) is a fatal pathogen that poses a serious health risk worldwide and especially in the middle east countries. Targeting the MERS-CoV 3-chymotrypsin-like cysteine protease (3CLpro) with small covalent inhibitors is a significant approach to inhibit replication of the virus. The present work includes generating a pharmacophore model based on the X-ray crystal structures of MERS-CoV 3CLpro in complex with two covalently bound inhibitors. In silico screening of covalent chemical database having 31,642 compounds led to the identification of 378 compounds that fulfils the pharmacophore queries. Lipinski rules of five were then applied to select only compounds with the best physiochemical properties for orally bioavailable drugs. 260 compounds were obtained and subjected to covalent docking-based virtual screening to determine their binding energy scores. The top three candidate compounds, which were shown to adapt similar binding modes as the reported covalent ligands were selected. The mechanism and stability of binding of these compounds were confirmed by 100 ns molecular dynamic simulation followed by MM/PBSA binding free energy calculation. The identified compounds can facilitate the rational design of novel covalent inhibitors of MERS-CoV 3CLpro enzyme as anti-MERS CoV drugs.
Keywords: 3CLpro; Covalent docking; Covalent inhibitors; MERS-CoV; Molecular dynamics simulation; Pharmacophore modeling.
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