Identification of potential inhibitors of Mtb InhA: a pharmacoinformatics approach
- PMID: 37526169
- DOI: 10.1080/07391102.2023.2242499
Identification of potential inhibitors of Mtb InhA: a pharmacoinformatics approach
Abstract
The emergence of superbugs of multi-drug resistant (MDR/RR) and extensively drug-resistant (XDR) Mycobacterium tuberculosis (Mtb) strains at a faster rate is posing a serious threat to Tuberculosis (TB) control worldwide. Mtb enoyl-acyl carrier protein reductase (InhA) is a well-established target of the front-line anti-TB prodrug Isoniazid (INH), which requires activation by Catalase-peroxidase enzyme (KatG) in order to inhibit InhA enzyme, that is crucial for the biosynthesis of the mycobacterial cell wall. Currently, due to widespread resistance to this drug, it is necessary to identify new clinical candidates that directly inhibit InhA enzyme and do not require activation by KatG, thereby circumventing most of the resistance mechanisms. In the present study, high-throughput virtual screening of ASINEX database was carried out to identify potential direct inhibitors of Mtb InhA. Best twenty compounds with good binding energies ranging between -12.36 and -9.27 kcal/mol were selected as promising virtual screening hits. These molecules were subjected to ADME study followed by toxicity prediction. Finally, four top-ranked molecules which are structurally diverse and possess best binding affinity than the co-crystalized ligand have been chosen for MD simulation studies followed by MM-GBSA analysis to validate and ensure the stability of hits in the active site of the enzyme. Based on the 100 ns MD simulation studies and binding free energy estimates, three hit molecules B244, B369, and B310 could be considered as potential inhibitors for Mtb InhA, which are likely to be potent against INH-resistant Mtb strains after successful experimental validation.Communicated by Ramaswamy H. Sarma.
Keywords: MM-GBSA; Tuberculosis (TB); enoyl-acyl carrier protein reductase (InhA); molecular docking; molecular dynamics; structure-based virtual screening.
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