In silico assessment of natural compounds against mycobacterium tuberculosis Rv1509 protein

Abstract Tuberculosis (TB) remains a leading cause of mortality globally, driven by the infectious pathogen, Mycobacterium tuberculosis (M.tb) . A novel DNA methyltransferase (DNA MTase), encoded by the Rv1509 gene and involved in TB pathogenesis, has been identified as a promising therapeutic target of anti-TB drugs. The present research employs an in silico approach to identify potential inhibitors of the Rv1509 -encoded DNA MTase using a computational drug design pipeline. A multi-stage virtual screening of ZINC natural compounds was conducted against Rv1509 . These phytomolecules were retrieved from the ZINC database, following computationally intensive docking and analysis of Absorption, Distribution, Metabolism, and Excretion (ADME) properties, top hits with a docking score ≤ -8.0 kcal/mol and favourable predicted pharmacokinetic profiles were prioritized. Subsequently, molecular dynamics simulations (MD) and principal component analysis (PCA) were employed to corroborate these hits. Of these, ZINC00338392, ZINC01662782, ZINC04104877, and ZINC96316367 ligands exhibited hydrogen bond formation with functional residue of DNA MTase, indicating biological relevance of binding. MD analysis revealed stable protein–ligand complexes during a 200 ns simulation. These computational analyses suggest that natural compounds bind with high predicted affinity to the active site of the Rv1509 -encoded DNA MTase, warranting future experimental validation of their potential as novel leads for anti-TB drug development.