中文摘要：

全新结构药物的研发存在周期长、耗资大、风险高的问题．通过各种技术预测已有药物的新适应症，即药物重定位，可以缩短药物研发时间、降低研发成本和风险．由于疾病种类和已知药物的数量繁多，完全通过实验筛选已知药物的新用途仍然具有很高的成本．随着组学和药物信息学数据的积累，药物重定位进入到了理性设计和实验筛选相结合的阶段，药物重定位的计算预测已经成为计算生物学和系统生物学的重要研究方向．本文将目前药物重定位计算分析的策略归纳为药物-靶标关系分析、药物-药物关系分析和药物-疾病关系分析，对已报道的技术方法及其成功应用实例进行了综述．

英文摘要：

Research and development of novel drugs cost too much time and money at high risk. Drug repositioning, which is to predict different therapeutic indications for approved drugs based on various technologies would help to reduce time, costs and risks of drug development. Experimental approaches alone are not sufficient to find new indications for approved drugs due to the huge amount of diseases and existing drugs. The integration of theoretical designs and experimental approaches along with published data of omics and drug informatics could lead to a new stage of drug development. Theoretical prediction of drug repositioning has provided a crucial direction to the research community of computational biology and systems biology. The current strategies of drug repositioning based on computing technology are underlined in this paper, namely drag-target relationship, drug-drug relationship and drug-disease relationship. Here we review the reported technologies and methods in this field with success cases at present.