title: Systematic mining of analog series with related core structures in multi-target activity space.
abstract: We have aimed to systematically extract analog series with related core structures from multi-target activity space to explore target promiscuity of closely related analogous. Therefore, a previously introduced SAR matrix structure was adapted and further extended for large-scale data mining. These matrices organize analog series with related yet distinct core structures in a consistent manner. High-confidence compound activity data yielded more than 2,300 non-redundant matrices capturing 5,821 analog series that included 4,288 series with multi-target and 735 series with multi-family activities. Many matrices captured more than three analog series with activity against more than five targets. The matrices revealed a variety of promiscuity patterns. Compound series matrices also contain virtual compounds, which provide suggestions for compound design focusing on desired activity profiles.
authors: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, 53113, Bonn, Germany.
authors: Disha
authors: D
authors: Gupta-Ostermann
authors: Ye
authors: Y
authors: Hu
authors: Jürgen
authors: J
authors: Bajorath
mesh_terms: D057225:Data Mining; D062313:Databases, Pharmaceutical; D015195:Drug Design; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D013329:Structure-Activity Relationship
chemical_list: D004364:Pharmaceutical Preparations
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