Combinatorial design and virtual screening of potent anti-tubercular fluoroquinolone and isothiazoloquinolone compounds utilizing QSAR and pharmacophore modelling$

Abstract

The virulence of tuberculosis infections resistant to conventional combination drug regimens cries for the design of potent fluoroquinolone compounds to be used as second line antimycobacterial chemotherapeutics. One of the most effective in silico methods is combinatorial design and high throughput screening by a ligand-based pharmacophore prior to experiment. The combinatorial design of a series of 3850 fluoroquinolone and isothiazoloquinolone compounds was then screened virtually by applying a topological descriptor based quantitative structure activity relationship (QSAR) for predicting highly active congeneric quinolone leads against Mycobacterium fortuitum and Mycobacterium smegmatis. The predicted highly active congeneric hits were then subjected to a comparative study between existing lead sparfloxacin with fluoroquinolone FQ hits as well as ACH-702 with predicted active isothiazoloquinolones, utilizing pharmacophore modelling to focus on the mechanism of drug binding against mycobacterial DNA gyrase. Finally, 68 compounds including 34 FQ and 34 isothiazoloquinolones were screened through high throughput screening comprising QSAR, the Lipinski rule of five and ligand-based pharmacophore modelling.