Hu Huabin, Stumpfe Dagmar, Bajorath Jürgen
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53113 Bonn, Germany.
Future Sci OA. 2019 Jan 18;5(2):FSO363. doi: 10.4155/fsoa-2018-0089. eCollection 2019 Feb.
Generating a knowledge base of new activity cliffs (ACs) defined on the basis of compound set-dependent potency distributions, also taking confirmed inactive compounds into account.
Different AC definitions, representations and search criteria were rationalized and applied.
For nearly 100 different target proteins, for which medicinal chemistry and biological screening data were available, target set-dependent ACs were identified. More than 20,000 target set-dependent ACs and associated information are made freely available.
LIMITATIONS & NEXT STEPS: As more compound data become available for new targets, the search for target set-dependent ACs, including confirmed inactive compounds will continue. Second-generation ACs will be subjected to systematic structure-activity relationship analysis.
基于化合物集依赖性效价分布生成新的活性悬崖（ACs）知识库，同时考虑已确认的非活性化合物。
对不同的AC定义、表示方法和搜索标准进行了合理化处理并加以应用。
对于近100种有药物化学和生物筛选数据的不同靶蛋白，确定了靶标集依赖性ACs。超过20000个靶标集依赖性ACs及相关信息可免费获取。
随着更多新靶标的化合物数据可用，将继续搜索包括已确认非活性化合物在内的靶标集依赖性ACs。第二代ACs将进行系统的构效关系分析。
