Tackling COVID-19: identification of potential main protease inhibitors via structural analysis, virtual screening, molecular docking and MM-PBSA calculations

The widespread of the COVID-19 disease, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), had severely affected the entire world. Unfortunately, no successful vaccines or antiviral drugs are currently available which leaves the scientific community under huge pressure to tackle this pandemic. Among the identified promising druggable targets, specific to this virus, is the main protease (M^pro) enzyme, which is vital for viral replication, transcription and packaging within the host cells. In this study, selective inhibition of the M^pro was sought via thorough analysis of its available structural data in the Protein Data Bank. To this end, COVID-19 M^pro crystal complexes were explored and the key interacting residues (KIRs) within its active site, that are expected to be vital for effective ligand binding, were identified. Based on these KIRs, 3D pharmacophore models were generated and used in virtual screening of different databases. Retrieved hits were docked into the active site of the enzyme and their MM-PBSA based free binding energies were calculated. Finally, ADMET descriptors were calculated to aid the selection of top scoring hits with best ADMET properties. Nine compounds with different chemotypes were identified as potential M^pro inhibitors. Further, MD simulations of a virtual complex of M^pro with one of the promising hits revealed stable binding which is indicative of good inhibitory potential. The identified compounds in this study are expected to support the global drug discovery efforts in fighting against this highly contagious virus by narrowing the searchable chemical space for potential effective therapeutics. Communicated by Ramaswamy H. Sarma.

Keywords: COVID-19; docking; key interacting residues; main protease; pharmacophore modeling.