Pharmacophore-Based Virtual Screening of Potential SARS-CoV-2 Main Protease Inhibitors from Library of Natural Products

Background: The SARS-CoV-2 main protease (M-pro) is an attractive target for drug discovery. Methods: A pharmacophore model was built using the three-dimensional (3D) pharmacophore generation algorithm HypoGen in Discovery Studio 2019. The best pharmacophore model was selected for validation using a test set of 24 compounds and was used as a 3D query for further screening of an in-house database of natural compounds. Lipinski's rule of five was used to assess the drug-like properties of the hit compounds. The filtered compounds were then subjected to bioactivity evaluations. The active compounds were docked into the active site of the SARS-CoV-2 M-pro crystal structure (PDB ID: 7D1M). Results: A suitable 3D pharmacophore model, Hypo1, was found to be the best model, consisting of four features (one hydrophobic feature, one hydrogen bond donor, and two hydrogen bond acceptors). Pharmacophore-based virtual screening with Hypo1 as the query to search an in-house database of 34 439 natural compounds resulted in 1502 hits. Among these, 255 compounds satisfied Lipinski's rule of five. The highest ranking 10 compounds were selected for further experimental testing, and one hit (W-7) illustrated inhibitory activity against SARS-CoV-2 M-pro with an IC50 value of 75 mu M. Docking studies revealed that this hit compound retained the necessary interactions within the active site of SARS-CoV-2 M-pro. Conclusion The identified lead natural compound could provide a scaffold for the further development of SARS-CoV-2 M-pro inhibitors.