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Current Drug Therapy

Editor-in-Chief

ISSN (Print): 1574-8855
ISSN (Online): 2212-3903

Research Article

In-Silico Analysis of Imidazo[2,1-b][1,3,4]thiadiazole Analogs as Putative Mycobacterium tuberculosis Enoyl Reductase Inhibitors

Author(s): Preeti Wadhwa, Sourav Bagchi and Anuj Sharma*

Volume 12, Issue 1, 2017

Page: [46 - 63] Pages: 18

DOI: 10.2174/1574885511666160930121123

Price: $65

Abstract

Background: Trans-2-Enoyl-ACP reductase (InhA) is an established target towards anti-tuberculosis therapy.

Objective: Computational studies on imidazo[2,1-b][1,3,4]thiadiazole derivatives as putative InhA inhibitors.

Methods: Combined molecular docking and three-dimensional quantitative structureactivity relationship (3D-QSAR) comprising comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on imidazo[2,1-b][1,3,4]thiadiazole derivatives as putative InhA inhibitors.

Results: Docking analysis reveals that hydrogen bonding, α-π and hydrophobic interactions are the governing factors for anti-TB activity. Furthermore, their best poses were used as an alignment tool for the development of 3D-QSAR models. The CoMFA model exhibited statistically significant results where Leave One Out (LOO) crossvalidated (q2), non-cross validated (r2) and predicted correlation coefficient (r2 pred) values were found to be 0.812, 0.982 and 0.667 respectively, therefore unveiled the important key structural requirements for InhA inhibition.

Conclusion: The active site residues GLN100, PRO156, TYR158, LEU197, ALA198, MET199, and LEU218 were identified as crucial binding residues responsible for interactions between inhibitors and InhA. Further, CoMFA analysis theorized that more potent InhA inhibitor could be developed based on proper substitution pattern around the phenyl ring at R2 and R3 position. Conclusively, this comprehensive study, an integration of molecular docking and CoMFA analysis provided insights and new predictive tools for structure-based design and optimization of InhA inhibitors.

Keywords: Tuberculosis, InhA, molecular docking, 3D-QSAR, CoMFA, CoMSIA, imidazo[2, 1-b][1, 3, 4] thiadiazoles, InhA inhibitors.

Graphical Abstract


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