Activity Cliff Networks for Medicinal Chemistry. Issue 5 (27th August 2014)

• Record Type: Journal Article
• Authors: Stumpfe, Dagmar; Bajorath, Jürgen; Gurwitz, David
• Is Part Of: Drug development research. Volume 75:Issue 5(2014)
• Page Start: 291
• Page End: 298
• Publication Date: 2014-08-27
• Subjects: Drug development -- Periodicals; Drugs -- Research -- Periodicals; 615.19
• DOI: 10.1002/ddr.21208
• Languages: English
• ISSNs: 0272-4391

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p> <table-wrap position="anchor" orientation="portrait"> <table border="1"> <colgroup span="1"> <col align="left" span="1" /> </colgroup> <tbody> <tr> <td align="left" rowspan="1" colspan="1">Preclinical Research</td> </tr> </tbody> </table> </table-wrap> </p> <p>Network 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.</p> </abstract>