Computer-aided drug design approaches for the identification of potent inhibitors targeting elongation factor G of Mycobacterium tuberculosis

Abstract

Elongation factor G (EF-G) is essential for protein synthesis in Mycobacterium tuberculosis (Mtb), positioning it as a promising target for anti-tubercular drug development. This study employs Structure-Based Drug Design (SBDD) to identify potential small molecule inhibitors that specifically target EF-G. Initially, binding hotspots on EF-G were pinpointed, and the binding modes of various compounds were analyzed. Through protein-protein interaction studies, several promising candidates were validated. Virtual screening and molecular docking techniques were utilized to evaluate the binding affinities and interactions of 20 candidate molecules with Mtb EF-G. Additionally, toxicity profiles of these compounds were assessed using predictive models, which indicated non-carcinogenic properties. To further refine the selection process, Support Vector Machine (SVM) and Random Forest models were applied to predict cell wall permeability. Notably, Asinex (8853) and Asinex (102619) emerged as top candidates, boasting high probability scores for effective permeability. Molecular docking and molecular dynamics (MD) simulations revealed that Asinex (8853), Asinex (102619), and Otava (79226) exhibited strong binding affinities and favorable conformations within the active site of Mtb EF-G. These findings suggest that these compounds have significant potential as inhibitors, warranting further investigation into their efficacy as novel anti-tubercular agents. Overall, this study emphasizes the value of Structure-Based Drug Design in identifying promising therapeutic candidates against tuberculosis by targeting essential bacterial factors like EF-G.