Exploring novel KDR inhibitors based on pharmaco-informatics methodology

Abstract

Kinase-insert domain-containing receptor (KDR) is one of the important mediators of Vascular endothelial growth factor (VEGF) function in endothelial cells. Inhibition of KDR can be therapeutically advantageous for treatment of a number of diseases. The present study focuses on exploring novel KDR inhibitors by means of pharmaco-informatics methodologies. Three-dimensional quantitative structure–activity relationship (3D-QSAR) analysis by atom-based pharmacophore mapping over a set of 85 molecules provides a proposition regarding the molecular fingerprint that can be optimized for designing more active inhibitors. The model was statistically validated with Q ² = 0.865 for training and r ² = 0.789, Pearson-r = 0.903 for test set molecules; r ²(0.925) by external validation suggests model robustness and indicates it as a strong query for screening any compound library. Virtual screening shows the importance of active site and hinge region residue for interaction with KDR inhibitors. Remarkably the retrieved hits contain a urea backbone, implicating urea derivatives as promising candidate for designing KDR inhibitors. The hydrophobicity of active site, which has until now been overlooked, has been raised into the picture by this study. This can impact on KDR drug development. The study thus quantifies crucial structural requirements necessary for a favourable interaction with the receptor binding site while the cooperative pattern provides important structural clues to chemists for framing potent medicinal agents in future.