Table of Contents
Journal of Computational Medicine
Volume 2014, Article ID 563080, 12 pages
Research Article

Combined 3D QSAR Based Virtual Screening and Molecular Docking Study of Some Selected PDK-1 Kinase Inhibitors

School of Biochemical Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi 221005, India

Received 30 September 2013; Revised 21 December 2013; Accepted 6 January 2014; Published 1 June 2014

Academic Editor: Jeon-Hor Chen

Copyright © 2014 Shalini Singh and Pradeep Srivastava. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Phosphoinositide-dependent kinase-1 (PDK-1) is an important therapeutic target for the treatment of cancer. In order to identify the important chemical features of PDK-1 inhibitors, a 3D QSAR pharmacophore model was developed based on 21 available PDK-1 inhibitors. The best pharmacophore model (Hypo1) exhibits all the important chemical features required for PDK-1 inhibitors. The correlation coefficient, root mean square deviation (RMSD), and cost difference were 0.96906, 1.0719, and 168.13, respectively, suggesting a good predictive ability of the model (Hypo1) among all the ten pharmacophore models that were analyzed. The best pharmacophore model (Hypo1) was further validated by Fisher’s randomization method (95%), test set method , and the decoy set with the goodness of fit (0.73). Further, this validated pharmacophore model Hypo1 was used as a 3D query to screen the molecules from databases like NCI database and Maybridge. The resultant hit compounds were subsequently subjected to filtration by Lipinski’s rule of five as well as the ADMET study. Docking study was done to refine the retrieved hits and as a result to reduce the rate of false positive. Best hits will further be subjected to in vitro study in future.