Pharmacophore-based 3D-QSAR as a predictive method for the QSAR analysis on a series of potent and selective inhibitors for three kinases of RTK family

Combined comparative molecular field analysis, comparative molecular similarity indices analysis, molecular docking and molecular dynamics studies of histone deacetylase 6 inhibitors

Human histone deacetylase isoform 6 (HDAC6) has been shown to have an immense role in cell motility and aggresome formation and is being an attractive selective target for the treatment of multiple tumour types and neurodegenerative conditions. The discovery of selective HDAC6 inhibitors with new chemical functionalities is therefore of utmost interest to researchers. In order to examine the structural requirements for HDAC6-specific inhibitors and to derive predictive model which can be used for designing new selective HDAC6 inhibitors, a three-dimensional quantitative structure-activity relationship study was carried out on a diverse set of ligands using common feature-based pharmacophore alignment followed by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The models displayed high correlation of 0.978 and 0.991 for best CoMFA and CoMSIA models, respectively, and a good statistical significance. The model could be used for predicting activities of the test set compounds as well as for deriving useful information regarding steric, electrostatic, hydrophobic properties of the molecules used in this study. Further, the training and test set molecules were docked into the HDAC6 binding site and molecular dynamics was carried out to suggest structural requirements for design of new inhibitors.

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.