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Systematic mining of analog series with related core structures in multi-target activity space

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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.

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Authors and Affiliations

  1. Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, 53113, Bonn, Germany

    Disha Gupta-Ostermann, Ye Hu & Jürgen Bajorath

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  1. Disha Gupta-Ostermann
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  2. Ye Hu
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  3. Jürgen Bajorath
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Correspondence to Jürgen Bajorath.

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Gupta-Ostermann, D., Hu, Y. & Bajorath, J. Systematic mining of analog series with related core structures in multi-target activity space. J Comput Aided Mol Des 27, 665–674 (2013). https://doi.org/10.1007/s10822-013-9671-5

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  • DOI: https://doi.org/10.1007/s10822-013-9671-5

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