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

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.

The Targeted Pesticides as Acetylcholinesterase Inhibitors: Comprehensive Cross-Organism Molecular Modelling Studies Performed to Anticipate the Pharmacology of Harmfulness to Humans In Vitro

“…The SB alignment assessment for either Mus musculus or Homo sapiens AChE inhibitors was performed by means of the four step standard protocol [ 78 , 96 ], by means of either AutoDock [ 79 ], AutoDock Vina [ 80 ], and DOCK [ 81 ] docking algorithms/scoring functions.…”

Understanding the Molecular Determinant of Reversible Human Monoamine Oxidase B Inhibitors Containing 2H-Chromen-2-One Core: Structure-Based and Ligand-Based Derived Three-Dimensional Quantitative Structure–Activity Relationships Predictive Models

“…In the case of SB aligned 3-D QSAR, alignment of the test set molecules should be performed by means of molecular docking. Nevertheless, docking algorithms are not yet fully optimized and reliable, and, moreover, during the simulation the proteins are still mainly considered as rigid . Therefore, the SB alignment of the test set conformations could result in nonoptimal positioning and lead to a higher prediction error.…”

“…The alignment procedures were assessed for their ability to reproduce the known experimental binding modes (docking or alignment accuracies) of the sole reversible inhibitors and were performed utilizing AutoDock Vina (hereinafter: Vina), DOCK, PLANTS (with all its available scoring functions: chemplp, plp, and plp95), and Surflex-Dock programs for the SB (Tables and and Figures and S27), and Balloon/ShaEP , programs couple for the LB alignment assessment (Table and Figures and S28–S30). The protocol consisted of experimental (EC) or modeled (randomized, RC) ligand conformation redocking (RD)/realignment (RA) or cross-docking (CD)/cross-alignment (CA) assessments (see the Alignment Assessment section). The best 3-D QSAR models were utilized to predict the activity of either SB or LB aligned test set compounds (Tables , , and S43–S50 and Figures and S31–S33).…”

Identification of Inhibitors to Trypanosoma cruzi Sirtuins Based on Compounds Developed to Human Enzymes

“…Briefly, the most suitable docking software was selected using all the program/minimization/scoring function combinations with a total of 9 combinations. The selection of the program was done by means of root mean squared deviation (RMSD) on the basis of ability to reproduce the sirtuins experimental complexes with the least error calculated by the docking accuracy (DA) [52]…”