Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.
J Chem Inf Model. 2010 Dec 27;50(12):2112-8. doi: 10.1021/ci1003637. Epub 2010 Nov 12.
Increasing evidence that many pharmaceutically relevant compounds elicit their effects through binding to multiple targets, so-called polypharmacology, is beginning to change conventional drug discovery and design strategies. In light of this paradigm shift, we have mined publicly available compound and bioactivity data for promiscuous chemotypes. For this purpose, a hierarchy of active compounds, atomic property based scaffolds, and unique molecular topologies were generated, and activity annotations were analyzed using this framework. Starting from ∼35 000 compounds active against human targets with at least 1 μM potency, 33 chemotypes with distinct topology were identified that represented molecules active against at least 3 different target families. Network representations were utilized to study scaffold-target family relationships and activity profiles of scaffolds corresponding to promiscuous chemotypes. A subset of promiscuous chemotypes displayed a significant enrichment in drugs over bioactive compounds. A total of 190 drugs were identified that had on average only 2 known target annotations but belonged to the 7 most promiscuous chemotypes that were active against 8-15 target families. These drugs should be attractive candidates for polypharmacological profiling.
越来越多的证据表明，许多具有药用价值的化合物通过与多个靶点结合来发挥作用，这种现象被称为多药理学，它正在开始改变传统的药物发现和设计策略。有鉴于此，我们已经从公开的化合物和生物活性数据中挖掘出了具有混杂化学结构的化合物。为此，生成了一个活性化合物层次结构、基于原子特性的支架和独特的分子拓扑结构，并使用该框架分析了活性注释。从对人类靶点具有至少 1μM 效力的约 35000 种活性化合物开始，确定了 33 种具有不同拓扑结构的化学型，这些化学型代表了对至少 3 种不同靶家族具有活性的分子。利用网络表示来研究支架-靶家族关系以及与混杂化学型相对应的支架的活性谱。混杂化学型的一个子集在药物中的富集程度明显高于生物活性化合物。共鉴定出 190 种药物，这些药物平均只有 2 个已知的靶标注释，但属于对 8-15 个靶家族具有活性的 7 种最混杂的化学型。这些药物应该是多药理学分析的有吸引力的候选药物。
