In Silico Approach to Identify Potent Bioactive Pyrrole Analogs as Inhibitors against the Enoyl-acyl Carrier Protein (ACP) Reductase Enzyme of Mycobacterium tuberculosis
Background In Mycobacterium tuberculosis the enzyme enoyl-acyl carrier protein ACP reductase InhA catalyzes the elongation of acyl fatty acids which are essential building blocks of the mycobacterial cell wall and precursors of mycolic acids. Millions of people are at risk of contracting new TB infections becoming ill and dying and a comprehensive understanding of the diseasersquos pathophysiology remains lacking.Objectives The objective was to develop potent therapeutic novel bioactive compounds that function as enoyl-acyl carrier protein reductase InhA PDB ID 6R9W inhibitors using an in silico drug design approach.Methods The virtual screening tool Auto Dock 1.5.6 was utilized to conduct molecular docking studies on enoyl-ACP reductase. Biovia Discovery Studio examined the docked complex of the ligand and protein.Results The ten bioactive compounds with the ability to bind to 6R9W exhibited docking scores ranging from -8.1 to -11.1 Kcalmol. Compound 1 which showed the most favourable docking energy -11.1 Kcalmol is an excellent candidate as a cell wall protein inhibitor 6R9W and will be further investigated in vitro.Conclusion Compound 1 with the IUPAC name N-2-hydroxynaphthalen-1-yl phenylmethyl-4-1Hpyrrol-1-yl benzohydrazide is an excellent candidate for the cell wall protein inhibitor 6R9W. It exhibited a strong docking affinity with a binding energy of -11.1 kcalmol. Using an in-silico drug design approach the study highlights the effectiveness of pyrrole scaffolds as enoyl-acyl carrier protein ACP reductase InhA antagonists in novel antitubercular therapies.
Authors
- Sravanthi Avunoori
- Shrinivas D. Joshi (ORCID: https://orcid.org/0000-0002-6520-806X)
- Tabssum Inamdar
Publication Details
- Journal
- Rajiv Gandhi University of Health Sciences Journal of Pharmaceutical Sciences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.26463/rjps.15_3_4
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00