Abstract

Mycobacterium tuberculosis has instigated a serious challenge toward the effective treatment of tuberculosis. The reoccurrence of the resistant strains of the disease to accessible drugs/medications has mandate for the development of more effective anti-tubercular agents with efficient activities. Time expended and costs in discovering and synthesizing new hypothetical drugs with improved biological activity have been a major challenge toward the treatment of multi-drug resistance strain M. tuberculosis (TB). Meanwhile, to solve the problem stated, a new approach i.e. QSAR which establish connection between novel drugs with a better biological against M. tuberculosis is adopted. The anti-tubercular model established in this study to forecast the biological activities of some anti-tubercular compounds selected and to design new hypothetical drugs is subjective to the molecular descriptors; AATS7s, VE2_Dzi, SpMin7-Bhe and RDF110i. The significant of the model were observed with R2 of 0.8738, R2 adj of 0.8351 Q_cvˆ2 of 0.7127 which served as criteria to substantiate the QSAR model. More also, the model significant with the QSAR external validation criterial ‘‘(R2test) of 0.7532. Ligand-receptor interactions between quinoline derivatives and the receptor (DNA gyrase) was carried out using molecular docking technique by employing the PyRx virtual screening software and discovery studio visualizer software. Furthermore, docking study indicates that compounds 10 of the derivatives with promising biological activity have the utmost binding energy of -18.8 kcal/mol. Meanwhile, the interaction of the standard drug; isoniazid with the target enzyme was observed with the binding energy -14.6 kcal/mol which was significantly lesser than the binding energy of the ligand (compound 10). This implies that ligand 10 could be used as a structural template to design better hypothetical anti-tubercular drugs with more efficient activities. The presumption of this research aid the medicinal chemists and pharmacist to design and synthesis a novel drug candidate against the tuberculosis. Moreover, in-vitro and in-vivo test could be carried out to validate the computational results.

Highlights

  • Over the years, tuberculosis has been a serious threat to mankind which is caused by M. tuberculosis

  • Optimum model for forecasting the derivatives of 2, 4-disubstituted quinoline against M. tuberculosis was successfully achieved by adopting the combination of computational and theoretical method

  • Name of descriptor(s) Average Broto-Moreau autocorrelation - lag 7/weighted by I-state Average coefficient sum of the last eigenvector from Barysz matrix/weighted by first ionization potential Smallest absolute eigenvalue of Burden modified matrix - n 7/weighted by relative Sanderson electronegativities RDF90i is 3D radial distribution function at 2.5 inter-atomic distance weighted by atomic masses

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Summary

Introduction

Tuberculosis has been a serious threat to mankind which is caused by M. tuberculosis. World Health Organization (2018), has reported cases of 9.0 million infected people, 360,000 HIV patient whom were leaving with tuberculosis, death of 230,000 children and death of 1.6 million people worldwide [1]. Some of the notable commercial sold drugs administered to people infected with tuberculosis are isoniazide (INH), pyrazinamide (PZA), rifampicin (RMP) and para-amino salicylic acid (PAS). The emergence of multi-drug resistance strain of M.TB toward the aforementioned medications has steered to advances in searching for new and better approach that is precise and fast in developing a novel compound with improved biological activity against M. tuberculosis. Extensively used computational method i.e. QSAR is a theoretical approach in designing and predicting new hypothetical drug candidate [2]. Multi-variant QSAR model is expressed mathematically to relates the biological activity of each compound with its respective molecular structures

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