Identification of Potential SARS-CoV-2 Main Protease (Mpro) Inhibitors Through Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Simulation Approaches

Background. The main protease (MPro) of coronaviruses (CoVs) is an essential enzyme involved in viral replication and represents an attractive target for antiviral drug discovery. Based on the similar binding pocket residues within the MPro of different CoVs, the study aimed to identify potential inhibitors of SARS-CoV-2 MPro from PDB ID 6M2N, using integrated computational approaches. Methods. Interaction-based pharmacophore modeling, virtual screening, molecular docking, MM-GBSA binding energy calculation, and molecular dynamics (MD) simulation were performed using BIOVIA Discovery Studio. The validated pharmacophore model was utilized to screen the ZINC database, followed by docking and 100 ns MD simulation analyses of the top-ranked compounds. Results. The pharmacophore model 01 demonstrated favourable predictive performance (AUC = 0.781). Virtual screening identified 483 compounds, from which 21 compounds were selected for docking studies. Among them, ZINC95473654 (Lig-1), ZINC95473725 (Lig-2), and ZINC08792368 (Lig-3) exhibited strong binding affinity toward MPro. Lig-1 demonstrated the best docking score and binding free energy along with stable interactions with key catalytic residues HIS41, CYS145, and GLU166. MD simulation analyses further confirmed that Lig-1, Lig-2 and Lig-3 maintained stable conformations. The hydrogen bond distance monitoring and post MD-MM-GBSA results suggest Lig-1 followed by Lig-3 as an inhibitor for Mpro and persistent intermolecular interactions throughout the 100 ns simulation period. Conclusion. The findings suggest that Lig-1, followed by Lig-3, may serve as promising computational lead compounds targeting SARS-CoV-2 Mpro, representing promising candidates for further experimental validation.