Identification of novel mycobacterium tuberculosis leucyl-tRNA synthetase inhibitor using a knowledge-based computational screening approach

Abstract

Objectives: Tuberculosis is a chronic lung disease caused by Mycobacterium tuberculosis (MTB), whose thick cell envelope and drug metabolizing enzymes offering it multidrug resistance. Therefore, there is a need to identify new molecular targets, biologically active as well as clinically safe anti-MTB compounds from natural resources. Methods: In this study, we performed high throughput computational screening of FDA listed natural bioactive compounds for identifying novel anti-MTB leucyl-tRNA (LeuRS) synthetase inhibitors. Results: Initial virtual molecular docking of 136 bioactive compounds has identified Docetaxel, Reserpine and Irinotecan as promising lead molecules owing to their structural plasticity and binding affinity with the active site of MTB-LeuRS. Further, deep molecular docking and molecular dynamics (MD) simulation analysis (at 100 ns) of the above three test compounds along with Oxaborole compound (GSK656) has demonstrated the superior binding affinity and stability of Irinotecan in forming molecular complexes with LeuRS protein. Interestingly, it also showed comparable binding residues and affinity parameters (like flexibility, structural divergence) as the GSK656 inhibitor in binding the tRNASyn domain 2 of LeuRS. A good correlation of pharmacokinetic properties (ADME-Tox) like bioavailability, absorption, solubility, and low toxicity between Irinotecan and GSK656 was evident. Competitive binding of Irinotecan to tRNASyn domain 2 of LeuRS is likely to make it unavailable to bind Leucine amino acid, which may negatively impact the protein biosynthesis and eventually inhibit the bacterial growth and attenuate the pathogen’s virulence. Conclusions: Our findings pave the way for further experimental confirmation of Irinotecan in the quest for a novel anti-LeuRS specific inhibitor to combat drug resistant MTB infection.

Keywords

• Mycobacterium tuberculosis
• Deep docking
• Bioactive compounds
• MD simulation
• tRNA
• Drug resistance