Title | ||
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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 |
Abstract | ||
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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. |
Year | DOI | Venue |
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2015 | 10.1007/s10822-015-9859-y | Journal of Computer-Aided Molecular Design |
Keywords | Field | DocType |
Vascular endothelial growth factor receptor-2 (VEGFR-2),Structure-based drug design (SBDD),Ligand-based drug design (LBDD),3-D QSAR,Molecular docking,3-D QSAutogrid/R | Docking (molecular),Quantitative structure–activity relationship,Pharmacophore,Experimental data,Kinase insert domain receptor,Chemistry,Vascular endothelial growth factor,Angiogenesis,Bioinformatics,Test set | Journal |
Volume | Issue | ISSN |
29 | 8 | 0920-654X |
Citations | PageRank | References |
2 | 0.38 | 12 |
Authors | ||
8 |
Name | Order | Citations | PageRank |
---|---|---|---|
Rino Ragno | 1 | 39 | 8.76 |
Flavio Ballante | 2 | 26 | 3.98 |
Adele Pirolli | 3 | 2 | 0.72 |
Richard B Wickersham | 4 | 9 | 1.34 |
Alexandros Patsilinakos | 5 | 3 | 1.08 |
Stéphanie Hesse | 6 | 2 | 0.38 |
Enrico Perspicace | 7 | 2 | 0.38 |
Gilbert Kirsch | 8 | 2 | 0.38 |