Theoretical investigation of a few selected compounds as potent anti-tubercular agents and molecular docking evaluation: A multi-linear regression approach

Abstract

Emergence of multi-drug resistant strains of Mycobacterium tuberculosis to the available drugs has demanded for the development of more potent anti-tubercular agents with efficient pharmacological activities. Time consumed and expenses in discovering and synthesizing new drug targets with improved biological activity have been a major challenge toward the treatment of multi-drug resistance strain M. tuberculosis. To solve the above problem, Quantitative Structure Activity Relationship (QSAR) is a recent approach developed to discover a novel drug with a better biological against M. Tuberculosis. A validated QSAR model developed in this study to predict the biological activities of some anti-tubercular compounds and to design new hypothetical drugs is influenced with the molecular descriptors; AATS7s, VR1-Dzi, VR1-Dzs, SpMin7-Bhe and RDF110i. The internal validation test for the derived model was found to have correlation coefficient (R²) of 0.8875, adjusted correlation coefficient (R²_adj) value of 0.8234 and leave one out cross validation coefficient (Qcv²) value of 0.8012 while the external validation test was found to have (R²_test) of 0.7961 and Y-randomization Coefficient (cRp²) of 0.6832. Molecular docking shows that ligand 13 of 2,4-disubstituted quinoline derivatives have promising higher binding score of -18.8 kcal/mol compared to the recommended drugs; isoniazid -14.6 kcal/mol. The proposed QSAR model and molecular docking studies will provides valuable approach for the modification of the lead compound, designing and synthesis more potent anti-tubercular agents.