Bajorath Jürgen
Department of Life Science Informatics, Bonn-Aachen International Center for Information Technology, Rheinische Friedrich-Wilhelms-Universität Bonn, Dahlmannstr. 2, D-53113, Bonn, Germany).
Mol Inform. 2016 Dec;35(11-12):583-587. doi: 10.1002/minf.201600030. Epub 2016 Apr 28.
In the context of polypharmacology, promiscuity is defined as the ability of small molecules to specifically interact with multiple targets. In addition, promiscuity can also be viewed as a characteristic feature of targets by considering their ability to recognize structurally diverse molecules as well as compounds with multi-target activities. Promiscuity estimates can be obtained through systematic mining of compound activity data. Currently available volumes of activity data are so large that it should be possible to derive statistically sound trends from their analysis. However, confidence criteria must be carefully considered when drawing conclusions from compound data mining. Herein, the results of recent promiscuity analyses are presented in context, including studies that view promiscuity from a target perspective.
在多药理学背景下，混杂性被定义为小分子与多个靶点特异性相互作用的能力。此外，通过考虑靶点识别结构多样分子以及具有多靶点活性化合物的能力，混杂性也可被视为靶点的一个特征。混杂性估计可通过系统挖掘化合物活性数据获得。目前可用的活性数据量非常大，以至于应该能够从对它们的分析中得出具有统计学意义的趋势。然而，从化合物数据挖掘得出结论时，必须仔细考虑置信标准。在此，将近期混杂性分析的结果放在背景中呈现，包括从靶点角度看待混杂性的研究。
