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Issue 67, 2018, Issue in Progress
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Chemical space, diversity and activity landscape analysis of estrogen receptor binders

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Abstract

Understanding the structure–activity relationships (SAR) of endocrine-disrupting chemicals has a major importance in toxicology. Despite the fact that classifiers and predictive models have been developed for estrogens for the past 20 years, to the best of our knowledge, there are no studies of their activity landscape or the identification of activity cliffs. Herein, we report the first SAR of a public dataset of 121 chemicals with reported estrogen receptor binding affinities using activity landscape modeling. To this end, we conducted a systematic quantitative and visual analysis of the chemical space of the 121 chemicals. The global diversity of the dataset was characterized by means of Consensus Diversity Plot, a recently developed method. Adding pairwise activity difference information to the chemical space gave rise to the activity landscape of the data set uncovering a heterogeneous SAR, in particular for some structural classes. At least eight compounds were identified with high propensity to form activity cliffs. The findings of this work further expand the current knowledge of the underlying SAR of estrogenic compounds and can be the starting point to develop novel and potentially improved predictive models.

Graphical abstract: Chemical space, diversity and activity landscape analysis of estrogen receptor binders

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Publication details

The article was received on 12 Sep 2018, accepted on 05 Nov 2018 and first published on 14 Nov 2018


Article type: Paper
DOI: 10.1039/C8RA07604A
Citation: RSC Adv., 2018,8, 38229-38237
  • Open access: Creative Commons BY-NC license
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    Chemical space, diversity and activity landscape analysis of estrogen receptor binders

    J. J. Naveja, U. Norinder, D. Mucs, E. López-López and J. L. Medina-Franco, RSC Adv., 2018, 8, 38229
    DOI: 10.1039/C8RA07604A

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