Literature DB >> 22248436

Directed R-group combination graph: a methodology to uncover structure-activity relationship patterns in a series of analogues.

Anne Mai Wassermann1, Jürgen Bajorath.   

Abstract

A graphical method is introduced to study details of structure-activity relationships (SARs) in analogue series that further extends conventional analysis of analogues using R-group tables or related approaches and that provides additional and more differentiated SAR information. The newly designed graph structure represents entire series of analogues in a consistent manner, regardless of their size and complexity of substitution patterns. The approach is specifically tailored toward a systematic exploration and intuitive interpretation of SAR features involving different R-groups and their combinations. Analogues and their potency information are systematically organized on the basis of R-group combinations that are present in a series. This organization scheme results in graph components that represent well-defined SAR patterns. Analysis of these patterns provides an immediate access to critical substitution sites and R-group combinations, favorable and unfavorable R-groups, or nonadditive potency effects of multisite substitutions. Furthermore, the data structure makes it possible to design new analogues by combining favorable R-group combinations derived from different compounds.

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Year:  2012        PMID: 22248436     DOI: 10.1021/jm201362h

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  4 in total

1.  Visualization of multi-property landscapes for compound selection and optimization.

Authors:  Antonio de la Vega de León; Shilva Kayastha; Dilyana Dimova; Thomas Schultz; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2015-08-02       Impact factor: 3.686

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

Authors:  Disha Gupta-Ostermann; Ye Hu; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2013-08-24       Impact factor: 3.686

3.  Bigger data, collaborative tools and the future of predictive drug discovery.

Authors:  Sean Ekins; Alex M Clark; S Joshua Swamidass; Nadia Litterman; Antony J Williams
Journal:  J Comput Aided Mol Des       Date:  2014-06-19       Impact factor: 3.686

4.  AnalogExplorer2 - Stereochemistry sensitive graphical analysis of large analog series.

Authors:  Ye Hu; Bijun Zhang; Martin Vogt; Jürgen Bajorath
Journal:  F1000Res       Date:  2015-10-09
  4 in total

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