Molecular and pharmacological impacts of phytochemicals on the enoyl-acyl carrier protein reductase: potential therapeutic implications in tuberculosis.

Abstract

Tuberculosis (TB) remains a major global health challenge, necessitating the development of novel therapeutic interventions. Enoyl-acyl carrier protein (ACP) reductase (InhA), a key enzyme in the fatty acid biosynthesis pathway of Mycobacterium tuberculosis, has emerged as a promising target for anti-TB drug discovery. Exploration of InhA-inhibitors is important for advancing the drug discovery process. This study systematically investigates the molecular and pharmacological interactions of bioactive phytochemicals from Indian traditional medicinal plants with InhA to elucidate their therapeutic potential. Among 42 screened phytocompounds, the top five (Ebastine, 2-Phenylaminoadenosine, Gosogliptin, Lorcainide, and Levomefolic acid) showed promising binding affinities towards InhA (PDB: 2X22), with binding free energy ranging from -9.6 to -10.9 kcal/mol. Comprehensive computational analyses, including pharmacokinetic predictions, drug-likeness evaluation, and biological activity assessment, highlighted their potential as a drug candidate. These top-ranking ligands exhibited potential target-lead interactions, forming stable hydrogen bonds and hydrophobic contacts crucial for inhibitory activity. This multidisciplinary computational approach, including molecular docking and dynamic simulations, identifies these phytochemicals as high-affinity and stable inhibitors of InhA. These identified phytocompounds could serve as promising scaffolds for further optimization and experimental validation in the quest for new plant-based anti-TB agents. Insight Our study targets the essential mycobacterial enzyme, enoyl-ACP reductase (InhA), a validated pathway crucial for tuberculosis drug discovery. Understanding structural characteristics of InhA and its interaction with potential phytochemical ligands enhances our grasp of the mechanisms underlying anti-mycobacterial activity. Computational tools such as molecular docking, molecular dynamics simulations, and predictive toxicology models, provides a rational framework for selecting promising leads for further experimental validation. This integrated approach not only facilitates the translation of traditional medicinal plant knowledge into evidence-based drug discovery but also maximizes the efficiency of the drug development pipeline.