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.

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.

The vascular endothelial growth factor receptor-2 kinases (VEGFR-2) are attractive targets for the development of anticancer agents. Self-organizing molecular field analysis (SOMFA) (a simple three-dimensional quantitative structure-activity relationship (3D-QSAR) method) is used to study the structure-activity correlation of 3-pyrrole substituted indolin-2-ones VEGFR-2 inhibitors. The statistical results, cross-validated <path id="x1D45F" d="M393 379q-9 -16 -28 -29q-15 -10 -23 -2q-19 19 -36 19q-21 0 -52 -38q-57 -72 -82 -126l-40 -197q-23 -3 -75 -18l-7 7q49 196 74 335q7 43 -2 43q-7 0 -30 -14.5t-47 -37.5l-16 23q37 42 82 73t67 31q41 0 15 -113l-11 -50h4q41 71 85 117t77 46q29 0 45 -26
q13 -21 0 -43z" /> <path id="x43" d="M614 175l29 -10q-33 -109 -57 -154q-121 -26 -184 -26q-90 0 -160.5 29t-112.5 77t-63.5 105.5t-21.5 119.5q0 157 108 253t277 96q36 0 71.5 -5t69 -13.5t36.5 -8.5q15 -102 20 -150l-29 -8q-20 79 -66.5 114t-128.5 35q-119 0 -187.5 -86t-68.5 -207
q0 -140 73.5 -227.5t188.5 -87.5q73 0 119.5 37.5t86.5 116.5z" /> (0.5267) and non-cross-validated (0.5623), show a reliable predictive ability. The contributions of shape and electrostatic fields are 42.7% and 57.3%, respectively. Analysis of SOMFA models through shape and electrostatic grids provide useful information for the design and optimization of new 3-pyrrole substituted indolin-2-one based VEGFR-2 inhibitors.

/pdf/3d-qsar-study-on-a-series-of-vegfr-2-kinase-inhibitors-3-3nhbjrbvci.pdf

Depeng Yan

Papers

3D-QSAR Studies of VEGFR-2 Kinase Inhibitors Based on Docking