Abstract
Pharmacophore models of G protein-coupled receptor40 (GPR40) agonists were developed using Discovery Studio V2.1. One hydrogen bond acceptor and three hydrophobic features, Hypo 1 which was the best hypothesis, had a correlation co-efficient of 0.971, cost difference of 73.041, and RMSD 0.680. This model was validated by test set, Fischer randomization test and decoy set. Subsequently, Hypo 1 was employed as a 3D query to identify potent molecules from chembridge database. 21 compounds were identified with estimated EC50 less than 500 nM. Seven top-scored hit compounds were chosen for further evaluation in FLIPR assay and two compounds were discovered as potent GPR40 agonists.
Keywords: 3D-QSAR-pharmacophore, discovery studio, GPR40 agonists, HypoGen, virtual screening.
Current Computer-Aided Drug Design
Title:3D-QSAR Based Pharmacophore Modeling and Virtual Screening for Identification of Novel G Protein-Coupled Receptor40 Agonists
Volume: 11 Issue: 1
Author(s): Peng Lu, Yubin Wang, Ping Kai Ouyang, Jinxiong She and Mingfang He
Affiliation:
Keywords: 3D-QSAR-pharmacophore, discovery studio, GPR40 agonists, HypoGen, virtual screening.
Abstract: Pharmacophore models of G protein-coupled receptor40 (GPR40) agonists were developed using Discovery Studio V2.1. One hydrogen bond acceptor and three hydrophobic features, Hypo 1 which was the best hypothesis, had a correlation co-efficient of 0.971, cost difference of 73.041, and RMSD 0.680. This model was validated by test set, Fischer randomization test and decoy set. Subsequently, Hypo 1 was employed as a 3D query to identify potent molecules from chembridge database. 21 compounds were identified with estimated EC50 less than 500 nM. Seven top-scored hit compounds were chosen for further evaluation in FLIPR assay and two compounds were discovered as potent GPR40 agonists.
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Cite this article as:
Lu Peng, Wang Yubin, Ouyang Kai Ping, She Jinxiong and He Mingfang, 3D-QSAR Based Pharmacophore Modeling and Virtual Screening for Identification of Novel G Protein-Coupled Receptor40 Agonists, Current Computer-Aided Drug Design 2015; 11 (1) . https://dx.doi.org/10.2174/1573409911666150529125814
DOI https://dx.doi.org/10.2174/1573409911666150529125814 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |
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