Receptor based 3D-QSAR to identify putative binders of Mycobacterium tuberculosis Enoyl acyl carrier protein reductase.
In the current study, the applicability and scope of 3D-QSAR models (CoMFA and CoMSIA) to complement virtual screening using 3D pharmacophore and molecular docking is examined and applied to identify potential hits against Mycobacterium tuberculosis Enoyl acyl carrier protein reductase (MtENR). Initially CoMFA and CoMSIA models were developed using series of structurally related arylamides as MtENR inhibitors. Docking studies were employed to position the inhibitors into MtENR active site to derive receptor based 3D-QSAR models. Both CoMFA and CoMSIA yielded significant cross validated q(2) values of 0.663 and 0.639 and r(2) values of 0.989 and 0.963, respectively. The statistically significant models were validated by a test set of eight compounds with predictive r(2) value of 0.882 and 0.875 for CoMFA and CoMSIA. The contour maps from 3D-QSAR models in combination with docked binding structures help to better interpret the structure activity relationship. Integrated with CoMFA and CoMSIA predictive models structure based (3D-pharmacophore and molecular docking) virtual screening have been employed to explore potential hits against MtENR. A representative set of 20 compounds with high predicted IC(50) values were sorted out in the present study.
Kumar
Ashutosh
A
Molecular and Structural Biology Division, Central Drug Research Institute, Lucknow, 226 001, India.
Siddiqi
Mohammad Imran
MI
D000213:Acyl Carrier Protein / Q000737:chemistry* / Q000378:metabolism; D009169:Mycobacterium tuberculosis / Q000201:enzymology* / Q000378:metabolism; D010088:Oxidoreductases / Q000737:chemistry* / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship
D000213:Acyl Carrier Protein; D010088:Oxidoreductases