Three-dimensional common-feature hypotheses for Toll-like receptor 7 agonists  

TLR7激动剂的三维药效团模型研究(英文)

作　　者：齐世光[1] 于慧[1] 金宏威[2] 王占黎[3] 

机构地区：[1]包头医学院第二附属医院,内蒙古包头014030 [2]北京大学医学部天然药物及仿生药物国家重点实验室,北京100191 [3]包头医学院第一附属医院,内蒙古包头014010

出　　处：《Journal of Chinese Pharmaceutical Sciences》2013年第2期148-153,共6页中国药学（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.20902068);Natural Science Foundation of Inner Mongolia Autonomous Region,China(Grant No.2011BS1201);Program for Young Talents of Science;Technology in Universities of Inner Mongolia Autonomous Region,China

摘　　要：Toll-like receptor 7 （TLR7）, the best known TLRs, has been demonstrated to be useful in fighting against infectious disease. In our study, three-dimensional （3D） pharmacophore models were constructed from a set of 5 TLR7 agonists. Among the 10 common-featured models generated by program Discovery Studio/HipHop, a hypothesis （Hypo2） including one hydrogen-bond donor （D）, one hydrogen-bond acceptor （A）, and two hydrophobic （H） features was considered to be important in evaluating the ligands with TLR7 agonistic activity. The obtained pharmacophore model was further validated using a set of test molecules and the Catalyst TLR7-agonist-subset database. Hypo2 has been shown to identify a range of highly potent TLR7 agonists. Finally, the obtained pharmacophore was further validated using docking studies. Taken together, this model can be utilized as a guide for future studies to design the structurally novel TLR7 agonists.本研究选择了5个TLR7激动剂作为训练集,使用Discovery Studio软件包构建了TLR7激动剂的药效团模型。最终获得的最优药效团模型Hypo2由一个氢键受体、一个氢键给体和两个疏水中心组成,对训练集和测试集具有较好的预测能力。此外,将Hypo2作为提问结构搜索由79个不同活性的TLR7激动剂(0.2–5000nM)组成的化合物库,该模型能有效将数据库中高活性的TLR7激动剂识别为目标化合物。分子对接研究进一步验证了该药效团模型的合理性。本研究获得的TLR7激动剂药效团模型有助于发现新型TLR7激动剂。

关 键 词：Toll-like receptor 7 Agonist Common-feature hypothesis Molecular docking 

分 类 号：R96[医药卫生—药理学]