Abstract
Dipeptidyl peptidase IV (DPP-IV) is an attractive target, and its launched inhibitors have made great significance to clinical therapy of type 2 diabetes. For developing high potent DPP-IV inhibitors, ligand- and structure-based approaches were applied for the optimization of cyanopyrrolidine in this study. Two statistically significant 3D-QSAR models (CoMFA with q2, 0.585; r2, 0.963; CoMSIA with q2, 0.678; r2, 0.949) were developed. In combination with the structure-based pharmacophore model, fundamental structural requirements and pharmacophoric features for R groups were determined. Suitable fragments for different R groups were retrieved for the generation of novel molecules. After being evaluated by molecular docking, QuaSAR descriptors filter and 3D-QSAR activity prediction, active DPP-IV inhibitors were found. The reliability indicated this workflow can be applied to facilitate lead optimization for DPP-IV and even for other drug targets.
Keywords: DPP-IV, 3D-QSAR, pharmacophore, fragment, type 2 diabetes.
Letters in Drug Design & Discovery
Title:De Novo Design of High Potent DPP-IV Inhibitors Based on the Scaffold of Cyanopyrrolidine
Volume: 12 Issue: 6
Author(s): Yu-Lei Jiang, Hao-Liang Yuan, Wei-Wei Zhang, Hai-Chun Liu, Yan-Min Zhang, Xiao Xiong, Jin-Xing Xu, Shuai Lu, Tao Lu and Ya-Dong Chen
Affiliation:
Keywords: DPP-IV, 3D-QSAR, pharmacophore, fragment, type 2 diabetes.
Abstract: Dipeptidyl peptidase IV (DPP-IV) is an attractive target, and its launched inhibitors have made great significance to clinical therapy of type 2 diabetes. For developing high potent DPP-IV inhibitors, ligand- and structure-based approaches were applied for the optimization of cyanopyrrolidine in this study. Two statistically significant 3D-QSAR models (CoMFA with q2, 0.585; r2, 0.963; CoMSIA with q2, 0.678; r2, 0.949) were developed. In combination with the structure-based pharmacophore model, fundamental structural requirements and pharmacophoric features for R groups were determined. Suitable fragments for different R groups were retrieved for the generation of novel molecules. After being evaluated by molecular docking, QuaSAR descriptors filter and 3D-QSAR activity prediction, active DPP-IV inhibitors were found. The reliability indicated this workflow can be applied to facilitate lead optimization for DPP-IV and even for other drug targets.
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Jiang Yu-Lei, Yuan Hao-Liang, Zhang Wei-Wei, Liu Hai-Chun, Zhang Yan-Min, Xiong Xiao, Xu Jin-Xing, Lu Shuai, Lu Tao and Chen Ya-Dong, De Novo Design of High Potent DPP-IV Inhibitors Based on the Scaffold of Cyanopyrrolidine, Letters in Drug Design & Discovery 2015; 12 (6) . https://dx.doi.org/10.2174/1570180812666141201223016
DOI https://dx.doi.org/10.2174/1570180812666141201223016 |
Print ISSN 1570-1808 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-628X |
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