Department of Bioinformatics, School of Life Sciences and Technology, Tongji University , Shanghai 200092, People's Repubic of China.
Center of Excellence in Bioinformatics and Life Sciences, the State University of New York at Buffalo , Buffalo, New York 14203, United States.
J Chem Inf Model. 2016 Sep 26;56(9):1615-21. doi: 10.1021/acs.jcim.6b00397. Epub 2016 Aug 19.
Drug discovery and development is a costly and time-consuming process with a high risk for failure resulting primarily from a drug's associated clinical safety and efficacy potential. Identifying and eliminating inapt candidate drugs as early as possible is an effective way for reducing unnecessary costs, but limited analytical tools are currently available for this purpose. Recent growth in the area of toxicogenomics and pharmacogenomics has provided with a vast amount of drug expression microarray data. Web servers such as CMap and LTMap have used this information to evaluate drug toxicity and mechanisms of action independently; however, their wider applicability has been limited by the lack of a combinatorial drug-safety type of analysis. Using available genome-wide drug transcriptional expression profiles, we developed the first web server for combinatorial evaluation of toxicity and efficacy of candidate drugs named "Connection Map for Compounds" (CMC). Using CMC, researchers can initially compare their query drug gene signatures with prebuilt gene profiles generated from two large-scale toxicogenomics databases, and subsequently perform a drug efficacy analysis for identification of known mechanisms of drug action or generation of new predictions. CMC provides a novel approach for drug repositioning and early evaluation in drug discovery with its unique combination of toxicity and efficacy analyses, expansibility of data and algorithms, and customization of reference gene profiles. CMC can be freely accessed at http://cadd.tongji.edu.cn/webserver/CMCbp.jsp .
药物发现和开发是一个昂贵且耗时的过程，失败的风险很高，主要原因是药物的临床安全性和疗效潜力。尽早识别和消除不合适的候选药物是降低不必要成本的有效方法，但目前为此目的提供的分析工具有限。毒理基因组学和药物基因组学领域的最近发展为药物表达微阵列数据提供了大量信息。CMap 和 LTMap 等网络服务器已使用这些信息来独立评估药物毒性和作用机制；但是，由于缺乏组合药物安全性分析，它们的适用性受到限制。我们使用现有的全基因组药物转录表达谱，开发了第一个名为“化合物连接图”（CMC）的组合评估候选药物毒性和疗效的网络服务器。使用 CMC，研究人员可以最初将他们的查询药物基因特征与从两个大型毒理基因组学数据库生成的预构建基因特征进行比较，然后进行药物疗效分析，以识别已知的药物作用机制或产生新的预测。CMC 通过其独特的毒性和疗效分析、数据和算法的可扩展性以及参考基因特征的定制，为药物重新定位和药物发现的早期评估提供了一种新方法。CMC 可在 http://cadd.tongji.edu.cn/webserver/CMCbp.jsp 免费访问。
