Anti-tubercular drug designing by structure based screening of combinatorial libraries
In the current study, the applicability and scope of descriptor based QSAR models to complement virtual screening using molecular docking approach have been applied to identify potential virtual screening hits targeting DNA gyrase A from Mycobacterium tuberculosis, an effective and validated anti-mycobacterial target. Initially QSAR models were developed against M. fortuitum and M. smegmatis using a series of structurally related fluoroquinolone derivatives as DNA gyrase inhibitors. Both the QSAR models yielded significant cross validated Q(2) values of 0.6715 and 0.6944 and R(2) values of 0.7250 and 0.7420, respectively. The statistically significant models were validated by a test set of 22 compounds with predictive R(2) value of 0.7562 and 0.7087 for M. fortuitum and M. smegmatis respectively. To aid the creation of novel antituberculosis compounds, combinatorial library was developed on fluoroquinolone template to derive a data set of 5280 compounds whose activity values have been measured by the above models. Highly active compounds predicted from the models were subjected to molecular docking study to investigate the mechanism of drug binding with the DNA gyrase A protein of M. tuberculosis and the compounds showing similar type of binding patterns with that of the existing drug molecules, like sparfloxacin, were finally reported. It is seen that hydrophobic characteristics of molecular structure together with few hydrogen bond interactions are playing an essential role in antimicrobial activity for the fluoroquinolone derivatives. A representative set of seven compounds with high predicted MIC values were sorted out in the present study.
virtual screening molecular docking fluoroquinolone compounds genetic algorithm (ga) quantitative structure activity relationship (qsar)