Homology modeling and molecular docking simulation of some novel imidazo[1,2-a]pyridine-3-carboxamide (IPA) series as inhibitors of Mycobacterium tuberculosis

Abstract

Abstract Background Tuberculosis (TB) remains a serious global health challenge that is caused by Mycobacterium tuberculosis and has killed numerous people. This necessitated the urgent need for the hunt and development of more potent drugs against the fast-emerging extensively drug-resistant (XDR) and multiple-drug-resistant (MDR) M. tuberculosis strains. Mycobacterium tuberculosis cytochrome b subunit of the cytochrome bc1 complex (QcrB) was recognized as a potential drug target in M. tuberculosis (25618/H37Rv) for imidazo[1,2-a]pyridine-3-carboxamides whose crystal strucuture is not yet reported in the Protein Data Bank (PDB). The concept of homology modeling as a powerful and useful computational method can be applied, since the M. tuberculosis QcrB protein sequence data are available. Results The homology model of QcrB protein in M. tuberculosis was built from the X-ray structure of QcrB in M. smegmatis as a template using the Swiss-Model online workspace. The modeled protein was assessed, validated, and prepared for the molecular docking simulation of 35 ligands of N-(2-phenoxy)ethyl imidazo[1,2-a] pyridine-3-carboxamide (IPA) to analyze their theoretical binding affinities and modes. The docking results showed that the binding affinity values ranged from − 6.5 to − 10.1 kcal/mol which confirms their resilience potency when compared with 6.0kcal/mol of isoniazid standard drug. However, ligands 2, 7, 22, 26, and 35 scored higher binding affinity values of − 9.60, − 9.80, − 10.10, − 10.00, and − 10.00 kcal/mol, and are respectively considered as the best ligands among others with better binding modes in the active site of the modeled QcrB protein. Conclusion The information derived in this research revealed some potential hits and paved a route for structure-based drug discovery of new hypothetical imidazo pyridine amide analogs as anti-tubercular drug candidates.

Keywords

• Molecular docking
• Binding affinity
• Active sites
• Homology
• Modeling
• Hydrogen bonds