• Dagmar Stumpfe and Jürgen Bajorath.
• Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, D-53113, Germany.
• Drug Dev. Res. 2014 Aug 1; 75 (5): 291-8.

AbstractNetwork representations are widely used in bioinformatics but have only been little explored in chemistry. Thus far, only a few attempts have been made to generate and analyze compound networks. Among these are the first activity cliff networks. In medicinal chemistry, activity cliffs are focal points of structure-activity relationships (SAR) analysis. Activity cliffs have generally been defined as pairs of structurally similar or analogous active compounds that have a large difference in potency against their target. However, most activity cliffs are not formed in isolation but in a coordinated manner involving multiple highly and weakly potent compounds. Recently, a comprehensive activity cliff network has been generated for current public domain bioactive compounds, hence providing a first global view of activity cliff formation. The design of activity cliff networks is discussed herein. From the global activity cliff network, local networks can be extracted for individual compound activity classes that provide graphical access to high-level SAR information for compound optimization efforts.© 2014 Wiley Periodicals, Inc.

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