化学学报 ›› 2005, Vol. 63 ›› Issue (20): 1875-1883. 上一篇    下一篇

研究论文

拮抗状态下α1A, α1Bα1D-肾上腺素能受体的分子模拟研究

李敏勇1,2,卢景芬2,夏霖*,1   

  1. (1中国药科大学 药物化学教研室 南京 210009)
    (2北京大学 天然药物与仿生药物重点实验室 北京 100083)
  • 投稿日期:2005-12-16 修回日期:2005-06-29 发布日期:2010-12-10
  • 通讯作者: 夏霖

Receptor-based Molecular Modeling Study on Antagonist-Bound Human α1A, α1B and α1D-Adrenoceptors

LI Min-Yong1,2, LU Jing-Fen2, XIA Lin*,1   

  1. (1 Department of Medicinal Chemistry, China Pharmaceutical University, Nanjing 210009)
    (2 National Research Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100083)
  • Received:2005-12-16 Revised:2005-06-29 Published:2010-12-10
  • Contact: XIA Lin

采用同源建模法对α1A-, α1B-和α1D-AR的三维结构进行了模拟, 并采用分子力学、分子动力学方法对所得同源模型进行优化, 然后分别采用训练集拮抗剂对接的方法得到拮抗状态下的α1A-, α1B-和α1D-AR三维结构模型. 得到的模型再采用FRED对接软件对测试集中的18个化合物进行对接并打分, 再将所得打分结果与其活性进行线性回归, 其回归结果具有良好的拟合效果, 由此回归方程预测的活性与化合物实验值较吻合, 说明我们建立的拮抗状态下的α1A-, α1B-和α1D-AR的三维同源模型具有一定的合理性, 可作为化合物虚拟筛选模型, 对新化合物进行对接虚拟筛选.

关键词: 肾上腺素能受体, 拮抗剂, 同源模型, 分子模拟, 分子对接

This investigation was performed to present the construction of rough homology models, the refinement using molecular methanics and molecular dynamics, and the optimization of these models into “antagonist-bound” models using training set docking for α1A-, α1B- and α1D-AR models. A test set consisting of 18 molecules was then docked into to obtained “antagonist-bound” models using FRED program. The docking scores and experimental affinities were analyzed by linear regression to obtain a good correlation. Consequently, this work highlights the rational construction for “antagonist-bound”α1A-, α1B- and α1D-AR models. The knowledge of these models can be used for virtual screening to discover more novel potential molecules.

Key words: adrenoceptor, antagonist, homology model, molecular modeling, docking