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Activity Landscapes, Information Theory, and Structure – Activity Relationships
Author(s) -
Iyer Preeti,
Stumpfe Dagmar,
Vogt Martin,
Bajorath J.,
Maggiora G. M.
Publication year - 2013
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201200120
Subject(s) - similarity (geometry) , feature (linguistics) , computer science , quantitative structure–activity relationship , cheminformatics , structural similarity , contrast (vision) , drug discovery , artificial intelligence , machine learning , bioinformatics , biology , image (mathematics) , philosophy , linguistics
Activity landscapes provide a comprehensive description of structure‐activity relationships (SARs). An information theoretic assessment of their features, namely, activity cliffs, similarity cliffs, smooth‐SAR, and featureless regions, is presented based on the probability of occurrence of these features. It is shown that activity cliffs provide highly informative SARs compared to smooth‐SAR regions, although the latter are the basis for most QSAR studies. This follows since small structural changes in the former are coupled with relatively large changes in activity, thus pinpointing specific structural features associated with the changes in activity. In contrast, Smooth‐SAR regions are typically associated with relatively small changes in both structure and activity. Surprisingly, similarity cliffs, which occur when both compounds in a compound‐pair have approximately equal activities but significantly different structures, are the most prevalent feature of activity landscapes. Hence, from an information theoretic point of view, they are the least informative landscape feature. Nevertheless, similarity cliffs do provide SAR information on potentially new active compound classes, and in that sense they are quite useful in drug discovery programs since they provide alternative possibilities should ADMET or other issues arise during the discovery and earlier preclinical development phases of drug research.

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