Computational drug discovery of nitroimidazole compounds targeting Ddn protein of Mycobacterium tuberculosis: insights from QSAR modeling, ADMET, molecular docking, and molecular dynamics simulation studies

Abstract

Still a major worldwide health issue, tuberculosis requires the development of new medicinal drugs. Computational techniques, including QSAR modeling, molecular docking, ADMET analysis, and molecular dynamics simulation, were used in this work, which examines the antitubercular potential of a nitroimidazole derivative targeting the Ddn protein of Mycobacterium tuberculosis. A multiple linear regression-based QSAR model (R² ​= ​0.8313, Q²_LOO ​= ​0.7426) created using QSARINS software shows strong prediction accuracy for anti-TB activity. Using molecular docking experiments (AutoDockTool 1.5.7), DE-5 compound was found to be the most promising molecule with a binding affinity of −7.81 ​kcal/mol and important hydrogen bonding interactions with active site residues PRO A:63, LYS A:79, and MET A:87. High bioavailability, good pharmacokinetics, and low toxicity risk were found by ADMET profiling (SwissADME). A 100 ns molecular dynamics simulation confirmed the stability of the DE-5-Ddn complex, as indicated by minimal Root Mean Square deviation, stable hydrogen bonds, low Root Mean Square Fluctuation, and compact structure reflected in Solvent Accessible Surface Area and radius of gyration values. Furthermore, MM/GBSA computations (−34.33 ​kcal/mol) confirmed a strong binding affinity and hence supporting DE-5's activity potential. These findings suggest that DE-5 is a suitable potential compound to advance the creation of new tuberculosis therapies targeting the Ddn protein. This work opens the path for logical drug design strategies in the TB battle.