Literature DB >> 20608746

Chemical substitutions that introduce activity cliffs across different compound classes and biological targets.

Anne Mai Wassermann1, Jürgen Bajorath.   

Abstract

Applying the concept of matched molecular pairs, we have systematically analyzed the ability of defined chemical changes to introduce activity cliffs. Public domain compound data were systematically screened for matched molecular pairs that were then organized according to chemical transformations they represent and associated potency changes. From vast available chemical transformation space, including both R-group and core substructure changes, approximately 250 nonredundant substitutions were identified that displayed a general tendency to form activity cliffs. These substitutions introduced activity cliffs in the structural context of diverse scaffolds and in compounds active against many different targets. Activity cliff-forming transformations were often rather simple, including replacements of small functional groups. Moreover, in many instances, chemically very similar transformations were identified that had a much lower propensity to form activity cliffs or no detectable cliff potential. Thus, clear preferences emerged for specific transformations. A compendium of substitutions with general activity cliff-forming potential is provided to aid in compound optimization efforts.

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Year:  2010        PMID: 20608746     DOI: 10.1021/ci1001845

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


  14 in total

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Journal:  J Chem Inf Model       Date:  2015-05-11       Impact factor: 4.956

7.  Exploring Structure-Activity Data Using the Landscape Paradigm.

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Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2012-11

8.  PubChem3D: Biologically relevant 3-D similarity.

Authors:  Sunghwan Kim; Evan E Bolton; Stephen H Bryant
Journal:  J Cheminform       Date:  2011-07-22       Impact factor: 5.514

9.  Freely available compound data sets and software tools for chemoinformatics and computational medicinal chemistry applications.

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Journal:  F1000Res       Date:  2012-08-14

10.  Structure-activity relationship analysis on the basis of matched molecular pairs.

Authors:  Anne Mai Wassermann
Journal:  J Cheminform       Date:  2014-03-11       Impact factor: 5.514

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