Authors : Shweta Kesrwani; Garima Awasthi; Ankur Mohan

Volume/Issue : Volume 11 - 2026, Issue 6 - June

Google Scholar : https://tinyurl.com/2wz7fyth

Scribd : https://tinyurl.com/4pcu4u9v

DOI : https://doi.org/10.38124/ijisrt/26jun067

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Tuberculosis caused by Mycobacterium tuberculosis is one of the main factors responsible for fatal lung diseases and affects the developing countries more because these regions suffer from tuberculosis infections owing to their cold climate conditions. The rise in number of cases related to MDR-TB and XDR-TB has made it very important that new chemical templates be created for inhibiting these enzymes produced by mycobacteria. The present study aims at determining whether there is any ability of these inhibitors to prevent the three important enzymes of MTB, which include DprE1 hexagonal crystal structure (PDB ID: 4FEH), InhA enoyl acyl carrier protein reductase (PDB ID: 5W07) and C171Q KasA beta ketoacyl synthase (PDB ID: 4C6X). Overall, 61 ligands obtained from the PubChem database underwent screening via Lipinski's Rule of Five, transformation via Open Babel 3.1.1, optimization by using torsional calculations, and conversion to the PDBQT file format. For characterizing the active sites, DogSiteScorer was used, which is part of ProteinsPlus, and then docking through PyRx 0.8 with the use of AutoDock Vina as a docking algorithm. Delamanid (CID: 6480466) demonstrated stronger binding to DprE1 (-12.9 kcal/mol), InhA (-12.3 kcal/mol), and KasA (-12.1 kcal/mol). The structure of the compound was analyzed by considering its interactions with the proteins using BIOVIA Discovery Studio. The coordinates of the pharmacophores from the Delamanid molecules were used for the virtual screening of ZINCPharmer and fragment generation via DeepFrag. AI-based pharmacophore optimization is one of the promising approaches in designing new anti-tuberculosis medications.

Keywords : Mycobacterium tuberculosis, DprE1, InhA, KasA, Delamanid, Molecular Docking, Pharmacophore Modeling, Virtual Screening, DeepFrag, AI-Assisted Drug Discovery.

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