BCTD:一个药物重定位研究用药物靶点数据库
BCTD: A Drug-Target Relation Database for Drug Repositioning
DOI: 10.12677/HJCB.2015.53005, PDF, HTML, XML,  被引量 下载: 3,187  浏览: 10,151 
作者: 王克强:复旦大学生命科学学院遗传学研究所遗传工程国家重点实验室,上海;吴宏宇, 黄青山*:复旦大学生命科学学院遗传学研究所遗传工程国家重点实验室,上海;上海高科联合生物技术研发有限公司,上海;李国栋:上海高科联合生物技术研发有限公司,上海
关键词: 靶点数据库药物重定位Target Database Drug Repositioning
摘要: 新药研发具有周期长、成本高、风险大等特点,往往是漫长而艰难的。药物重定位,即发现原有药物的新适应症,可有效缩短周期、降低成本、规避风险,正在成为药物研发的重要策略。近些年药物重定位发展迅速,其中联合药物靶点相互作用信息和组学数据进行药物重定位是一种可行的方法。但是现有的众多药物靶点数据库中的部分药物靶点信息缺乏实验证明,而且大多存在或遗漏或冗余的现象,各库中信息亦采用不同命名规则,难以直接用作药物重定位研究。因此我们综合整理多个数据库内容和大量文献,排除缺乏实验证明的信息,并标准化所得信息,建立了一个全新的在线药物靶点数据库。该数据库现含有766个化合物、746个靶点和2862条药物/化合物和靶点相互作用的信息。该库的建立大大简化了研究人员查询与寻找药物靶点信息的流程,能够为药物重定位提供方向和线索。
Abstract: Discovering and developing new drug is an arduous, costly and risky process. Drug repositioning, by discovering new indications of old drugs out of their original indications, is a time-saving, cost-efficient and low-risk manner. This made it more and more important in drug discovery and development. It has appeared numerous methods for drug repositioning in recent years. Combining the information of interactions between drugs and targets with omics data is a reasonable and effectively approach of drug repositioning. Dozens of databases including information of drug targets were constructed with varying scopes by different research groups in the past decade. However, it is inconvenient to researchers who need such information because of the lack of coordination in naming rules among these databases and the existed data omissions or redundancies. So we create a new database of drug-target interactions by manually inspecting and standardizing the data collected from these databases and scientific literatures. In the current version, there are 766 drug/compound entries, 746 target entries and 2862 items of drug-target interactions in the database. It will facilitate researchers to get the information of drug targets easily and quickly, providing clues for drug repositioning.
文章引用:王克强, 吴宏宇, 李国栋, 黄青山. BCTD:一个药物重定位研究用药物靶点数据库[J]. 计算生物学, 2015, 5(3): 41-47. http://dx.doi.org/10.12677/HJCB.2015.53005

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