Literature DB >> 21504183

Single R-Group Polymorphisms (SRPs) and R-cliffs: an intuitive framework for analyzing and visualizing activity cliffs in a single analog series.

Dimitris K Agrafiotis1, John J M Wiener, Andrew Skalkin, Jeremy Kolpak.   

Abstract

We introduce Single R-Group Polymorphisms (SRPs, pronounced 'sharps'), an intuitive framework for analyzing substituent effects and activity cliffs in a single congeneric series. A SRP is a pair of compounds that differ only in a single R-group position. Because the same substituent pair may occur in multiple SRPs in the series (i.e., with different combinations of substituents at the other R-group positions), SRP analysis makes it easy to identify systematic substituent effects and activity cliffs at each point of variation (R-cliffs). SRPs can be visualized as a symmetric heatmap where each cell represents a particular pair of substituents color-coded by the average difference in activity between the compounds that contain that particular SRP. SRP maps offer several advantages over existing techniques for visualizing activity cliffs: 1) the chemical structures of all the substituents are displayed simultaneously on a single map, thus directly engaging the pattern recognition abilities of the medicinal chemist; 2) it is based on R-group decomposition, a natural paradigm for generating and rationalizing SAR; 3) it uses a heatmap representation that makes it easy to identify systematic trends in the data; 4) it generalizes the concept of activity cliffs beyond similarity by allowing the analyst to sort the substituents according to any property of interest or place them manually in any desired order.

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Year:  2011        PMID: 21504183     DOI: 10.1021/ci200054u

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  5 in total

Review 1.  An Overview of the Challenges in Designing, Integrating, and Delivering BARD: A Public Chemical-Biology Resource and Query Portal for Multiple Organizations, Locations, and Disciplines.

Authors:  Andrea de Souza; Joshua A Bittker; David L Lahr; Steve Brudz; Simon Chatwin; Tudor I Oprea; Anna Waller; Jeremy J Yang; Noel Southall; Rajarshi Guha; Stephan C Schürer; Uma D Vempati; Mark R Southern; Eric S Dawson; Paul A Clemons; Thomas D Y Chung
Journal:  J Biomol Screen       Date:  2014-01-17

2.  Rapid scanning structure-activity relationships in combinatorial data sets: identification of activity switches.

Authors:  José L Medina-Franco; Bruce S Edwards; Clemencia Pinilla; Jon R Appel; Marc A Giulianotti; Radleigh G Santos; Austin B Yongye; Larry A Sklar; Richard A Houghten
Journal:  J Chem Inf Model       Date:  2013-06-07       Impact factor: 4.956

Review 3.  On exploring structure-activity relationships.

Authors:  Rajarshi Guha
Journal:  Methods Mol Biol       Date:  2013

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

5.  Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method.

Authors:  Emili Besalú
Journal:  Int J Mol Sci       Date:  2016-05-26       Impact factor: 5.923

  5 in total

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