药学学报, 2014, 49(10): 1357-1364
引用本文:
方坚松, 刘艾林, 杜冠华. 基于化学信息学方法预测药物靶点的研究进展[J]. 药学学报, 2014, 49(10): 1357-1364.
FANG Jian-song, LIU Ai-lin, DU Guan-hua. Research advance in the drug target prediction based on chemoinformatics[J]. Acta Pharmaceutica Sinica, 2014, 49(10): 1357-1364.

基于化学信息学方法预测药物靶点的研究进展
方坚松1, 刘艾林1,2,3, 杜冠华1,2,3
1. 中国医学科学院、北京协和医学院药物研究所, 北京 100050;
2. "药物靶点研究与新药筛选"北京市重点实验室, 北京 100050;
3. "天然药物活性物质与功能"国家重点实验室, 北京 100050
摘要:
网络药理学与多向药理学等新兴学科的出现迫使科学家们重新认识与探索已有药物新的作用机制。药物靶点的预测对阐释药物分子作用机制和老药新用等领域都具有重大意义。本文结合近年来国内外多个课题组的研究成果,主要综述了当前几种基于化学信息学方法预测小分子潜在靶点的方法,包括基于配体结构特征的预测方法、基于蛋白结构特征的预测方法以及基于数据挖掘技术的预测方法,通过应用实例,说明这些方法的优势,并提出今后的发展方向。
关键词:    化学信息学      靶点预测      数据挖掘      相似性搜索     
Research advance in the drug target prediction based on chemoinformatics
FANG Jian-song1, LIU Ai-lin1,2,3, DU Guan-hua1,2,3
1. Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China;
2. Beijing Key Laboratory of Drug Target and Screening Research, Beijing 100050, China;
3. State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China
Abstract:
The emerging of network pharmacology and polypharmacology forces the scientists to recognize and explore new mechanisms of existing drugs. The drug target prediction can play a key significance on the elucidation of the molecular mechanism of drugs and drug reposition. In this paper, we systematically review the existing approaches to the prediction of biological targets of small molecule based on chemoinformatics, including ligand-based prediction, receptor-based prediction and data mining-based prediction. We also depict the strength of these methods as well as their applications, and put forward their developing direction.
Key words:    chemoinformatics    target prediction    data mining    similarity search   
收稿日期: 2014-04-14
基金项目: 重大新药创制项目(2014ZX09507003-002);卫生行业科研专项(200802041);国际合作项目(2011DFR31240)
通讯作者: 刘艾林,Tel:86-10-83150885,Fax:86-10-63165184,E-mail:liuailin@imm.ac.cn;杜冠华,Tel/Fax:86-10-63165184,E-mail:dugh@imm.ac.cn
Email: liuailin@imm.ac.cn;dugh@imm.ac.cn
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