Structure Based Identification of Some Potential Pan-Coronavirus Main Protease Inhibitors via Pharmacophore Modeling and Molecular Dynamics Simulation Within a One Health Framework

Background. The main protease (Mpro/3CLpro) 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 Mpro from PDB ID 6M2N, using inte-grated computational approaches. Methods. Structure-based pharmacophore modeling, virtual screening, molecular docking, MM-GBSA binding energy calculation, and molecu-lar dynamics (MD) simulation were performed using BIOVIA Discovery Studio. The vali-dated pharmacophore model was utilized to screen the ZINC database, followed by dock-ing 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 cat-alytic residues HIS41, CYS145, and GLU166. MD simulation analyses further confirmed that Lig-1 and Lig-2 maintained stable conformations and persistent intermolecular inter-actions throughout the 100 ns simulation period. Conclusion. The findings suggest that Lig-1, followed by Lig-2, may serve as promising CoVs Mpro inhibitors and warrant fur-ther experimental validation. Further experimental validation are required to consolidate the identified compounds as universal inhibitors of the CoVs-Mpro enzyme.