高等学校化学学报

高等学校化学学报 ›› 2005, Vol. 26 ›› Issue (3): 546.

• 研究论文 • 上一篇    下一篇

家蝇与大鼠GABA受体抑制剂的药效团模型及其3D-QSAR研究

任天瑞1, 沈斌1,2, 裴剑锋2, 汪永生1, 向文胜1   

  1. 1. 国家生物化学工程技术研究中心,中国科学院过程工程研究所,北京 100080;
    2. 北京大学化学与分子工程学院分子动态与稳态结构国家重点实验室,北京大学理论生物学中心,北京 100871;
    3. 中国科学院计算机网络信息中心,北京 100080
  • 收稿日期:2004-01-21 出版日期:2005-03-10 发布日期:2005-03-10
  • 通讯作者: 任天瑞(1964年出生),男,教授,从事药物分子设计与合成研究.E-mail:trren@home.ipe.ac.cn E-mail:trren@home.ipe.ac.cn
  • 基金资助:

    国家“九七三”计划项目(批准号:2003CB114400);国家“八六三”计划项目(批准号:2003AA235010-05)资助.

Pharmacophore Models and 3D-QSAR Studies of Rat and Fly's GABA Receptor Inhibitors

REN Tian-Rui1, SHEN Bin1,2, PEI Jian-Feng2, WANG Yong-Sheng1, XIANG Wen-Sheng1   

  1. 1. National Engineering Research Center for Biotechnology, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100080, China;
    2. State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Center for Theoretical Biology, Peking University, Beijing 100871, China;
    3. Computer Network Information Center, Chinese Academy Sciences, Beijing 100080, China
  • Received:2004-01-21 Online:2005-03-10 Published:2005-03-10

PDF (PC)

被引次数

23

摘要： 采用DISCOtech方法,用7个大鼠γ-氨基丁酸(GABA)A受体抑制剂和11个家蝇GABAA受体抑制剂分别建立了其药效团模型;用CoMFA方法建立了22个大鼠GABAA受体抑制剂和29个家蝇GABAA受体抑制剂的3D-QSAR模型,模型的交叉验证相关系数分别为0.526和0.679,验证了药效团模型的合理性,为设计更高活性和更高选择性的化合物提供了参考

关键词: GABAA受体, 药效团模型, 三维定量构效关系(3D-QSAR), 比较分子力场分析(CoMFA)

Abstract: Aminobutyric acid(GABA) plays an important role as a major inhibitory neurotransmitter in both vertebrates and invertebrates, which have similar but pharmacologically distinct GABAA receptors, so insect's GABAA receptors are regarded as a promising target for insecticides. In this paper, two pharmacophore models of rat and fly's GABAA receptors for a series of reported inhibitors were studied by DISCOtech methodology, which laid a foundation for finding the leading compounds and designing new selective compounds. According to this study, the three-dimensional quantitative structure and activity relationships were studied, which gave two predictive CoMFA models with qrat2= 0.526 and qfly2=0.679. The CoMFA models verified the pharmacophore models, and gave insights to the design of better GABAA receptor inhibitors.

Key words: GABAA receptor, Pharmacophore model, 3D-QSAR, Comparative molecular field analysis(CoMFA)

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