Computational small molecule drug discovery for multidrug-resistant tuberculosis: emerging targets and recent medicinal chemistry advances.

Abstract

Tuberculosis (TB) remains a major global health challenge, further intensified by the emergence of multidrug-resistant (MDR-TB) and extensively drug-resistant (XDR-TB) strains, which compromise the effectiveness of existing therapeutic regimens. Despite significant progress in TB chemotherapy, prolonged treatment duration, drug-associated toxicity, bacterial persistence, and the continuous evolution of resistance mechanisms highlight the urgent need for innovative therapeutic strategies and next-generation antitubercular agents. This review provides a comprehensive overview of the evolving landscape of TB drug discovery, covering current therapeutic approaches, mechanisms of drug resistance, and recent advances in medicinal chemistry-driven small-molecule development. The discovery and optimization of novel chemical entities, drug repurposing strategies, and target-based approaches are discussed, with particular emphasis on fragment-based drug discovery (FBDD), structure-based drug design (SBDD), and computer-aided drug design (CADD). Recent advances targeting essential and emerging mycobacterial vulnerabilities, including DprE1, InhA, ATP synthase, MmpL3, DNA gyrase, mycobacterial carbonic anhydrases (MtCAs), PanC, and other critical metabolic pathways, are highlighted to demonstrate the expanding opportunities for mechanism-guided antitubercular drug discovery. Furthermore, the integration of computational approaches, including molecular docking, molecular dynamics simulations, artificial intelligence (AI), and machine learning (ML), has significantly accelerated hit identification, lead optimization, and prediction of drug-like properties. These approaches are transforming conventional drug discovery by enabling rational design of potent molecules with improved efficacy and pharmacological profiles. However, challenges associated with target validation, drug penetration, bacterial persistence, resistance development, and clinical translation remain major obstacles. The convergence of medicinal chemistry, advanced computational technologies, and a deeper understanding of Mycobacterium tuberculosis biology represents a promising strategy for developing effective therapies against both drug-sensitive and drug-resistant TB.