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 / Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert. - In: JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN. - ISSN 0920-654X. - STAMPA. - 29:8(2015), pp. 757-776. [10.1007/s10822-015-9859-y]

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

RAGNO, Rino
;
PIROLLI, ADELE;Patsilinakos, Alexandros;
2015

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/788336
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