Stumpfe Dagmar, Lounkine Eugen, Bajorath Jürgen
Department of Life Science Informatics, B-IT, Rheinische Friedrich-Wilhelms-Universität, Bonn, Germany.
Methods Mol Biol. 2011;672:503-15. doi: 10.1007/978-1-60761-839-3_20.
For chemical genetics and chemical biology, an important task is the identification of small molecules that are selective against individual targets and can be used as molecular probes for specific biological functions. To aid in the development of computational methods for selectivity analysis, molecular benchmark systems have been developed that capture compound selectivity data for pairs of targets. These molecular test systems are utilized for "selectivity searching" and the analysis of structure-selectivity relationships. Going beyond binary selectivity sets focusing on target pairs, a methodological framework, Molecular Formal Concept Analysis (MolFCA), is described for the definition and systematic mining of compound selectivity profiles.
对于化学生物学和化学遗传学而言,一项重要任务是鉴定对单个靶点具有选择性且可用作特定生物学功能分子探针的小分子。为助力选择性分析计算方法的开发,已构建了分子基准系统,用于获取针对成对靶点的化合物选择性数据。这些分子测试系统用于“选择性搜索”以及结构-选择性关系分析。除了关注靶点对的二元选择性集之外,还描述了一种方法框架——分子形式概念分析(MolFCA),用于定义和系统挖掘化合物选择性概况。