高等学校化学学报

高等学校化学学报 ›› 2013, Vol. 34 ›› Issue (5): 1240.doi: 10.7503/cjcu20120792

• 物理化学 • 上一篇    下一篇

大麻素Ⅰ型受体拮抗剂的结构特征

林克江1, 黄振桂1, 李婷2, 王南溪2, 程瑶2, 沈玲玲2, 王宇彤2, 李卉2, 叶波平3   

  1. 1. 中国药科大学药学院, 南京 210009;
    2. 中国药科大学基础药学理科基地班, 南京 210009;
    3. 中国药科大学生命科学与技术学院, 南京 210009
  • 收稿日期:2012-08-29 出版日期:2013-05-10 发布日期:2013-05-10
  • 通讯作者: 林克江, 男, 博士, 副教授, 主要从事新药物的设计与合成研究. E-mail: link@cpu.edu.cn E-mail:link@cpu.edu.cn
  • 基金资助:

    国家"重大新药创制"科技重大专项基金(批准号: 2012ZX09103301 -018)资助.

Structural Characteristics of Cannabinoid Type Ⅰ Receptor Antagonists

LIN Ke-Jiang1, HUANG Zhen-Gui1, LI Ting2, WANG Nan-Xi2, CHENG Yao2, SHEN Ling-Ling2, WANG Yu-Tong2, LI Hui2, YE Bo-Ping3   

  1. 1. School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China;
    2. Class of National Base of Pharmaceutical Education, China Pharmaceutical University, Nanjing 210009, China;
    3. School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
  • Received:2012-08-29 Online:2013-05-10 Published:2013-05-10

PDF (PC)

被引次数

5

摘要：

以92个具有大麻素受体Ⅰ(CB1)拮抗活性的化合物为训练集, 39个化合物为测试集, 采用Discovery Studio V2.5(DS)软件中的3D构效关系药效团产生(QSAR Pharmacophore Generation)模块建立药效团模型. 获得的最佳药效团模型的构成为一个氢键受体(HBA)、 一个疏水基团(HY)和二个芳环中心(RA), 采用费用函数(Cost function)评价药效团模型, 该模型的Δcost为119.32, 相关性为0.921, 均方根偏差为0.730, Configuration cost为16.1229, 表明模型能较好地预测化合物的活性. 同时针对目前已知的近450个化合物的12种结构类型进行了探讨, 所得结果为进一步设计CB1拮抗剂提供了理论依据.

关键词: 大麻素Ⅰ型受体拮抗剂, 药效团, 定量构效关系

Abstract:

Cannabinoid type Ⅰ receptor(CB1) antagonists offer a new approach to treat obesity and problems related to obesity such as diabetes and cardiometabolic risks. Pharmacophore models were developed via Discovery Studio V2.5 with a training set of 92 CB1 agonists and a test set of 39 compounds. The best hypothesis consisting of five features, namely, a hydrogen bond acceptors, a hydrophobic and two ring aromatic features, has a correlation coefficient of 0.921, a cost difference of 119.132, the root mean square(RMS) of 0.730, and a configuration cost of 16.1229, suggesting that a highly predictive pharmacophore model was successfully obtained. The application of the model shows great success in predicting the activities of the near 450 known CB1 agonists in 12 structural types and provides a guide to design new CB1 antagonists.

Key words: Cannabinoid type Ⅰ receptor antagonist, Pharmacophore, Quantitative structure activity relationship

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