Abstract
CD38 is regarded as a potential target. Inhibitors against CD38 can regulate calcium metabolism in human body to impede the occurrence of disease, including diabetes and myeloma. In this work, 47 thiazoloquin(az)olin(on)es analogues with high pIC50 values in the micromolar ranges are studied by three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking. The comparative molecule field analysis (i.e., CoMFA q2 = 0.790; r2 = 0.967; rpred 2 = 0.872) and comparative molecular similarity indices analysis (i.e., CoMSIA q2 = 0.723; r2 = 0.969; rpred 2 = 0.815) are applied. Then, the Topomer CoMFA method is performed to validate these models, and the results show that this model has q2 = 0.662, r2 = 0.915 and rpred 2 = 0.704. These results indicate that the three models have good predictive abilities. Subsequently, molecular docking highlights the important interactions between the ligand and the CD38 receptor protein.
Keywords: 3D-QDAR, docking, CD38 inhibitor, Topomer CoMFA, CoMFA, CoMSIA
Letters in Drug Design & Discovery
Title:Identification of Thiazoloquin(az)olin(on)es Derivatives as CD38 Inhibitors Through 3D-QSAR and Molecular Docking Simulations
Volume: 14 Issue: 2
Author(s): Xiaodong Gao and Yujie Ren
Affiliation:
Keywords: 3D-QDAR, docking, CD38 inhibitor, Topomer CoMFA, CoMFA, CoMSIA
Abstract: CD38 is regarded as a potential target. Inhibitors against CD38 can regulate calcium metabolism in human body to impede the occurrence of disease, including diabetes and myeloma. In this work, 47 thiazoloquin(az)olin(on)es analogues with high pIC50 values in the micromolar ranges are studied by three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking. The comparative molecule field analysis (i.e., CoMFA q2 = 0.790; r2 = 0.967; rpred 2 = 0.872) and comparative molecular similarity indices analysis (i.e., CoMSIA q2 = 0.723; r2 = 0.969; rpred 2 = 0.815) are applied. Then, the Topomer CoMFA method is performed to validate these models, and the results show that this model has q2 = 0.662, r2 = 0.915 and rpred 2 = 0.704. These results indicate that the three models have good predictive abilities. Subsequently, molecular docking highlights the important interactions between the ligand and the CD38 receptor protein.
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Cite this article as:
Gao Xiaodong and Ren Yujie, Identification of Thiazoloquin(az)olin(on)es Derivatives as CD38 Inhibitors Through 3D-QSAR and Molecular Docking Simulations, Letters in Drug Design & Discovery 2017; 14 (2) . https://dx.doi.org/10.2174/1570180813666160919121104
DOI https://dx.doi.org/10.2174/1570180813666160919121104 |
Print ISSN 1570-1808 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-628X |
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