Computational Identification of Bepotastine as a Potential Inhibitor of Mycobacterium bovis UDP-N-acetylmuramic Acid L-alanine Ligase MurC through Molecular Docking, Molecular Dynamics, Binding Free-Energy and ADMET Analyses

This dataset supports the manuscript entitled “Computational Identification of Bepotastine as a Potential Inhibitor of Mycobacterium bovis UDP-N-acetylmuramic Acid L-alanine Ligase MurC through Molecular Docking, Molecular Dynamics, Binding Free-Energy and ADMET Analyses.” The study used an integrated computational workflow to identify and prioritize potential inhibitors of Mycobacterium bovis UDP-N-acetylmuramic acid L-alanine ligase MurC (Mb-MurC; PDB ID: 7BVA). The deposited files include supporting computational data generated during molecular docking, protein–ligand interaction analysis, molecular dynamics simulation, MM-PBSA binding free-energy estimation, theoretical dissociation constant analysis, and ADMET/toxicity prediction. The dataset may include docking output files, selected protein–ligand complex structures, molecular dynamics analysis files, residue–ligand distance analysis data, MM-PBSA output files, ADMET prediction results, figures, supplementary tables, and related processed data used to support the conclusions reported in the manuscript. These files are provided to support transparency, reproducibility, and further evaluation of the computational workflow. The results are predictive in nature and should be interpreted as in silico findings requiring experimental validation through biochemical MurC inhibition assays, direct binding studies, cytotoxicity testing, hERG screening, and whole-cell antimycobacterial assays.