Sardari S, Dezfulian M
Department of Biotechnology, Pasteur Institute, #69 Pasteur Avenue, Tehran, Iran 13164.
Mini Rev Med Chem. 2007 Feb;7(2):181-9. doi: 10.2174/138955707779802633.
The existing chemical data such as those created by high throughput screening (HTS), structure-activity relationship (SAR) studies are converted into information as a result of storage and registration. Accessibility, manipulation, and data mining of such information make up the knowledge for drug development. Cheminformatics, exploiting the combination of chemical structural knowledge, biological screening, and data mining approaches is used to guide drug discovery and development and would assist by integrating complex series of rational selection of designed compounds with drug-like properties, building smarter focused libraries. This paper presents cheminformatics approaches and tools for designing and data mining of chemical databases and information. Many examples of success in lead identification and optimization in the area of anti-infective therapy have been discussed.
现有的化学数据,如高通量筛选(HTS)、构效关系(SAR)研究产生的数据,通过存储和注册被转化为信息。这些信息的可获取性、操作和数据挖掘构成了药物开发的知识。化学信息学利用化学结构知识、生物筛选和数据挖掘方法的结合,用于指导药物发现和开发,并通过将具有类药性质的设计化合物的复杂系列合理选择与构建更智能的聚焦库相结合来提供帮助。本文介绍了用于化学数据库和信息设计及数据挖掘的化学信息学方法和工具。文中讨论了抗感染治疗领域在先导化合物识别和优化方面的许多成功实例。