Targeting drug-resistant <i>Mycobacterium tuberculosis</i> : an integrated computational approach to identify DprE2 inhibitors

<i>Mycobacterium tuberculosis</i> remains one of the leading causes of death from a single infectious agent, posing a major global health challenge. The rise of drug-resistant strains has intensified the need for novel therapeutic agents. Pretomanid and delamanid, two recently developed antitubercular drugs, are bicyclic nitroimidazoles that act as prodrugs, requiring activation by specific mycobacterial enzymes. However, the precise molecular targets of their active metabolites are not fully explained. Recent studies have identified DprE2, an essential enzyme in the biosynthesis of decaprenylphosphoryl-β-D-arabinofuranose (DPA) and arabinogalactan, as a potential target of delamanid. In this study, we applied structure-based pharmacophore modelling to identify potential inhibitors targeting DprE2. High-throughput virtual screening, followed by molecular docking, was used to evaluate binding affinities. ADMET predictions were incorporated to assess drug likeness and pharmacokinetic profiles. Nine promising hits were shortlisted, and their binding stability was further evaluated using 250 ns molecular dynamics simulations. Binding free energy calculations using the MM-GBSA method were then applied to refine the selection, identifying five potent lead molecules. These candidates show strong potential for further development as DprE2 inhibitors, offering a new path in the fight against drug-resistant tuberculosis.