Molecular modeling studies of vascular endothelial growth factor receptor tyrosine kinase inhibitors using QSAR and docking

Molecular structure, pKa, lipophilicity, solubility, absorption, polar surface area, and blood brain barrier penetration of some antiangiogenic agents

“…There is no single experimental study concerned with the systematic comparative experimental investigation of the physicochemical and pharmacokinetic parameters of these medicinally useful new antiangiogenic agents. Quantitative structure activity relationships and docking of factor VEGFR inhibitors were discussed quite recently [9], and the X-ray crystal structures of sorafenib [10], chlorine derivative of sunitinib [11], motesanib [12], vandetanib [13], and AEE 788 [14] in complexes with protein kinases deposited in the Protein Data Bank [15] were used to clarify the binding mode of these ligands. The absence of experimental structural data of highly potent synthetic angiogenesis inhibitors targeting a number of VEGF, as well as platelet-derived growth factor (PDGF) receptors presents a challenge to the application of the molecular modeling methods in order to enhance our understanding of the biological activity of these compounds.…”

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

“…VEGFR-2 is a likely target for computational drug design as small molecule inhibitors have been derived from many molecular scaffolds, including quinazolines [14,15], naphtamides [16], furo [2,3-d]pyrimidines [17], pyridinyltriazines [18], pyrimidinyllindazoles [19], and most recently thieno [3,2-d]pyrimidinones and thieno [1][2][3] triazines [20], offering an expansive data set for design and optimization. Using SciFinder Ò as a representative search tool for the literature, 17 publications were identified which used 3-D QSAR methods to study inhibitors of VEGFR-2 [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. Most of these studies built CoMFA/CoMSIA models using SYBYL software [21,22,[28][29][30][31][35][36][37], and all but one simply used these models for pharmacophore modeling and analysis; one study used the 3-D QSAR models as a virtual screening tool to identify novel N-(pyridin-4-ylmethyl)aniline derivates as potential VEGFR-2 inhibitors [37].…”

“…Using SciFinder Ò as a representative search tool for the literature, 17 publications were identified which used 3-D QSAR methods to study inhibitors of VEGFR-2 [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. Most of these studies built CoMFA/CoMSIA models using SYBYL software [21,22,[28][29][30][31][35][36][37], and all but one simply used these models for pharmacophore modeling and analysis; one study used the 3-D QSAR models as a virtual screening tool to identify novel N-(pyridin-4-ylmethyl)aniline derivates as potential VEGFR-2 inhibitors [37]. Many of the studies performed docking studies on the training and test set molecules using a variety of docking software (AutoDock [36], Sybyl [21,37], Surflex-Dock [35], MacroModel [31], GOLD [28] ), but each study made use of only one available crystal structure of VEGFR-2.…”

“…Most of these studies built CoMFA/CoMSIA models using SYBYL software [21,22,[28][29][30][31][35][36][37], and all but one simply used these models for pharmacophore modeling and analysis; one study used the 3-D QSAR models as a virtual screening tool to identify novel N-(pyridin-4-ylmethyl)aniline derivates as potential VEGFR-2 inhibitors [37]. Many of the studies performed docking studies on the training and test set molecules using a variety of docking software (AutoDock [36], Sybyl [21,37], Surflex-Dock [35], MacroModel [31], GOLD [28] ), but each study made use of only one available crystal structure of VEGFR-2. Herein, by means of the 3-D QSAutogrid/R procedure [38], the very first general structure-based 3-D QSAR (SB 3-D QSAR) models has been developed using all the available experimental data for VEGFR-2 as training set, and externally validated with 262 molecules with unknown binding modes, composing ten different external test sets.…”

Pharmacophore Guided 3D‐QSAR CoMFA Analysis of Amino Substituted Nitrogen Heterocycle Ureas as KDR Inhibitors

“…Yu et al developed three-dimensional pharmacophore hypotheses on the basis of a set of known KDR kinase inhibitors and employed the best one as 3D search query to screen the Traditional Chinese Medicine Database (TCMD) for other potential inhibitors [27]. More recently, Du et al employed two conformer-based alignment strategies to construct reliable 3D-QSAR models on naphthamide analogues with the aim of optimizing and enhancing selectivity toward KDR [28].…”