Strategic targeting of AckA in Mycobacterium tuberculosis using peptide inhibitors.

Tuberculosis (TB) continues to pose a significant global health challenge, exacerbated by the rise of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains, which undermine the efficacy of existing therapies. Recent research focuses on anti-tubercular peptides as promising therapeutics due to their direct antimicrobial action and ability to enhance antibiotic efficacy by disrupting mycobacterial membranes. This study aims to identify and characterize potent anti-tubercular peptides targeting Acetate Kinase (AckA), a key enzyme in the metabolism of Mycobacterium tuberculosis. Through peptide virtual screening (PVS), followed by evaluations of cell penetration, toxicity, and MM/GBSA binding energy calculations, we identified five potential lead peptides, namely, DBAASP4864, DBAASP17881, DBAASP7096, DBAASP1043, and DBAASP5585, sourced from curated antimicrobial peptide databases (APD3, DBAASP, DRAMP, AntiTb, SATPdb, and CAMPR3). These candidates were selected based on favorable physicochemical properties, minimal toxicity, and strong binding affinities. Molecular dynamics simulations (MDS) demonstrated the structural stability of the peptide AckA complexes, with increased hydrogen bond formation observed over the simulation trajectories. Further validation through principal component analysis (PCA) and free energy landscape (FEL) mapping revealed a dominant low-energy basin, supporting the conformational stability of the complexes. MM/PBSA analysis confirmed strong binding interactions, and key residues, namely, Asn195, Asp266, Phe267, Gly314, and Asn318, were identified as critical contributors to peptide binding and complex stabilization. The study reveals peptide dynamics, highlighting their therapeutic potential and clinical applicability, while providing a strong foundation for experimental validation and developing next-generation anti-tubercular agents targeting drug-sensitive and drug-resistant M. tuberculosis strains.