Structure-based virtual screening of plant secondary metabolites for potential anti-tubercular activity

Tuberculosis remains a major global health challenge, worsened by the rise of multidrug-resistant and extensively drug-resistant strains. Natural products have historically contributed to antimicrobial drug discovery, and medicinal plant–derived phytochemicals offer a promising source of safer and cost-effective antitubercular agents. This study aimed to identify potential phytochemical inhibitors of essential Mycobacterium tuberculosis targets using a comprehensive computational drug discovery strategy, with a focus on identifying dual-target inhibitors to combat drug resistance. Literature mining identified 310 medicinal plants with reported antitubercular activity, resulting in 4390 unique phytochemicals. Three-dimensional structures were retrieved and evaluated for drug likeness and toxicity using computational profiling. Molecular docking was performed against arabinosyl transferase and the transcription initiation complex. High-affinity ligands were further analyzed using binding free energy calculations and extended molecular dynamics simulations to assess binding stability and interaction profiles. Several phytochemicals demonstrated strong binding affinities against both targets, surpassing those of standard antitubercular drugs. Molecular dynamics analyses confirmed stable protein–ligand interactions, supported by consistent structural and interaction parameters. This study identified promising phytochemicals with dual-target inhibitory potential against Mycobacterium tuberculosis . The findings provide a rational and cost-effective basis for prioritizing natural compounds for experimental validation and development as novel antitubercular agents.