人类尼古丁型乙酰胆碱受体α7亚型激动剂的药效团模型构建及验证

doi:10.5246/jcps.2013.05.057

摘要/Abstract

摘要：

人类尼古丁型乙酰胆碱受体α7亚型是精神分裂认知障碍的治疗靶点, 开发具有选择性的激动剂对于该疾病的临床治疗具有重要意义。由于α7受体的三维结构尚未解析, 我们采取基于配体的药物设计策略, 用HypoGen方法构建了该受体激动剂的药效团模型, 并通过费用函数 (cost function)进行质量评价, 以测试集活性预测和基于Fisher随机化方法的交互检验进行药效团验证。通过富集因子 (EF)和ROC曲线下面积 (AU-ROC)等统计学参数挑选得到的最终药效团模型具有1个氢键受体 (HBA), 2个疏水中心 (Hydrophobic)和1个正电离子化基团(PosIonizable), 并且该药效团模型和α7受体同源模建蛋白的配体对接结果的吻合度较好。本研究所建立的药效团模型, 可用于后续α7受体选择性激动剂的筛选和优化, 对抗精神分裂疾病药物的开发具有一定的理论指导和应用价值。

关键词: 精神分裂, 人类尼古丁型乙酰胆碱受体α7亚型, 激动剂, 药效团模型, 分子对接

Abstract: Human nAChR α7 is the potential target for schizophrenia cognitive disorders, and it is meaningful to develop selective human nAChR α7 agonists for the clinical treatment of the disease. Because the crystal structure of α7 receptor has not been resolved, ligand-based drug design strategy was took in this work. A 3D QSAR pharmacophore model was built by HypoGen method, and its quality was evaluated by cost function. Furthermore, the pharmacophore model was validated with activity prediction of test set and was cross-validated based on Fisher’s Randomization Method. By Enrichment Factor and AU-ROC analysis, the final pharmacophore, which is consisted of one HBA, two Hydrophobic and one PosIonizable, was selected and it fitted well with the docking result of α7 homology model and the ligand. The pharmacophore is expected for the following virtual screening and lead optimization of human nAChR α7 agonists, which is important for the development and discovery of novel antipsychotics.

Key words: Schizophrenia, Human nAChR α7, Agonists, Pharmacophore modeling, Molecular docking

中图分类号:

R916.1

Supporting: Foundation item: National Natural Science Foundation of China (Grant No. 81373272).
^*Corresponding author. Tel.: 86-10-82805049; 86-10-82802567

于博, 金宏威, 张亮仁^*, 王超^*. 人类尼古丁型乙酰胆碱受体α7亚型激动剂的药效团模型构建及验证[J]. , DOI: 10.5246/jcps.2013.05.057.

Bo Yu, Hongwei Jin, Liangren Zhang^*, Chao Wang^* . Pharmacophore identification and validation for human nAChR α7 agonists[J]. , DOI: 10.5246/jcps.2013.05.057.

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