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噻唑类Fascin蛋白抑制剂的3D-QSAR研究

3D-QSAR studies on thiazole derivatives as Fascin protein inhibitors

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【作者】 文晓荣王娟安春红舒茂林治华

【Author】 Wen Xiaorong;Wang Juan;An Chunhong;Shu Mao;Lin Zhihua;School of Pharmacy & Bioengineering, Chongqing University of Technology;School of Chemistry and Chemical Engineering, Chongqing University;

【机构】 重庆理工大学药学与生物工程学院重庆大学化学化工学院

【摘要】 本文针对43个噻唑衍生物Fascin蛋白抑制剂,运用CoMFA(比较分子力场分析)以及CoMSIA(比较分子相似性指数分析)这两种经典的3D-QSAR方法,建立了CoMFA模型和CoMSIA模型,分别对其进行三维定量构效关系研究。CoMFA模型和CoMSIA模型的交叉验证系数q~2分别为0.731和0.846,相关系数r~2分别为0.969和0.926。这两种模型都显示出了比较好的预测性和稳定性。它们的三维等势图以及对接结果也证实了抑制剂活性和结构特征之间的关系,可以为今后设计研究新型Fascin抑制剂而提供了理论基础。

【Abstract】 In this paper, two typical 3D-QSAR methods of CoMFA(comparative molecular field analysis) and CoMSIA(comparative molecular similarity index analysis) models were applied to systematic investigate 43 thiazole derivatives as Fascin protein inhibitors, and the CoMFA and CoMSIA model were builted to carries on the three-dimensional quantitative structure-activity relationship studies. The coefficients of cross-validation q~2 and non cross-validation r~2 for CoMFA model were 0.731 and 0.846, for CoMSIA model were 0.969 and 0.926 respectively. Both model had good predictive capability and stability. The contour maps provided useful guidance for more potent Fascin inhibitors discovery.

【基金】 国家自然科学基金项目(81171508,31170747);重庆市自然科学基金重点项目CSTC 2013 JJB10004;重庆市教委科技项目(KJ130809,KJ1400946)
  • 【文献出处】 计算机与应用化学 ,Computers and Applied Chemistry , 编辑部邮箱 ,2016年08期
  • 【分类号】R91
  • 【被引频次】4
  • 【下载频次】141
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