Identification of a natural product inhibitor of SARS-CoV-2 Mpro through integrated virtual screening, DFT, and molecular dynamics simulations

Approximately 220,000 natural product compounds from ZINC15 were screened using ADMET filtering, molecular docking against Mpro (PDB ID: 6LU7), and docking against hMAT1A and CYP450 isoforms to evaluate hepatotoxicity and drug clearance. Top compounds were subjected to DFT calculations, followed by MD simulations with post-MD analyzes of the top lead molecule (Lig14) (COM trajectory extraction, sub-diffusive behavior, MM-GBSA, and alchemical solvation free-energy calculations).

Mutational analysis was performed on relevant mutants (G143S, G143D, G143N, C145Y, E166K) to assess resistance profiles. The dataset contains (1) filtered ligand library details; (2) DFT-optimized structured files for the top four compounds; (3) MD trajectory files for the lead molecule (Lig14); and (4) mutational analysis (PDB files and sequences) for wild-type and mutant Mpro complexes. This resource facilitates method validation, comparative analysis, and future computational drug discovery research.