Comparative QSAR studies of nitrofuranyl amide derivatives using theoretical structural properties

The global increase in multidrug-resistant Mycobacterium tuberculosis strains and intolerance of first-line anti-tuberculosis drugs may cause major health problems and necessitate modification of the structural therapy regimen. In an ongoing effort to develop new and potent anti-tuberculosis agents, a series of nitrofuranyl amides were subjected to quantitative structure activity relationship (QSAR) analysis using various feature selection methods. Nitrofuranyl amide derivatives with good therapeutic indices are known to inhibit an enzyme responsible for bacterial cell-wall synthesis and act as novel mycobacterial inhibitors. Successful implementation of a predictive QSAR model largely depends on the selection of a preferred set of molecular descriptors that can signify the chemical-biological interaction. Genetic algorithm (GA), simulated annealing and stepwise regression are applied as variable selection methods for an effective comparison and model development. The results of two-dimensional QSAR showed that a combination of topological indices, hydrophobic properties and autocorrelation descriptors of different atomic properties could be explored to design potent anti-tubercular inhibitors. Further analysis using three-dimensional QSAR technique identifies a suitable model obtained by GA-partial least square method leading to anti-tubercular activity prediction. The influences of steric and electrostatic field effects generated by the contribution plot are analysed and discussed. Both two- and three-dimensional QSAR analyses of such derivatives provide important structural insights for designing potent anti-tuberculosis drugs.