Literature DB >> 17514577

QSAR and mechanistic interpretation of estrogen receptor binding.

R Serafimova1, M Todorov, D Nedelcheva, T Pavlov, Y Akahori, M Nakai, O Mekenyan.   

Abstract

A multi-dimensional formulation of the COmmon REactivity PAttern (COREPA) modeling approach has been used to investigate chemical binding to the human estrogen receptor (hER). A training set of 645 chemicals included 497 steroid and environmental chemicals (database of the Chemical Evaluation and Research Institute, Japan - CERI) and 148 chemicals to further explore hER-structure interactions (selected J. Katzenellenbogen references). Upgrades of modeling approaches were introduced for multivariate COREPA analysis, optimal conformational generation and description of the local hydrophobicity of chemicals. Analysis of reactivity patterns based on the distance between nucleophilic sites resulted in identification of distinct interaction types: a steroid-like A-B type described by frontier orbital energies and distance between nucleophilic sites with specific charge requirements; an A-C type where local hydrophobic effects are combined with electronic interactions to modulate binding; and mixed A-B-C (AD) type. Chemicals were grouped by type, then COREPA models were developed for within specific relative binding affinity ranges of >10%, 10 > RBA > or = 0.1%, and 0.1 > RBA > 0.0%. The derived models for each interaction type and affinity range combined specific prefiltering requirements (interatomic distances) and a COREPA classification node using no more than 2 discriminating parameters. The interaction types are becoming less distinct in the lowest activity range for each chemicals of each type; here, the modeling was performed within chemical classes (phenols, phthalates, etc.). The ultimate model was organized as a battery of local models associated to interaction type and mechanism.

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Year:  2007        PMID: 17514577     DOI: 10.1080/10629360601053992

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  4 in total

1.  A hierarchical testing strategy for micropollutants in drinking water regarding their potential endocrine-disrupting effects-towards health-related indicator values.

Authors:  Jochen Kuckelkorn; Regine Redelstein; Timon Heide; Jennifer Kunze; Sibylle Maletz; Petra Waldmann; Tamara Grummt; Thomas-Benjamin Seiler; Henner Hollert
Journal:  Environ Sci Pollut Res Int       Date:  2017-09-21       Impact factor: 4.223

2.  Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

Authors:  Kathryn Ribay; Marlene T Kim; Wenyi Wang; Daniel Pinolini; Hao Zhu
Journal:  Front Environ Sci       Date:  2016-03-08

3.  Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches.

Authors:  Liying Zhang; Alexander Sedykh; Ashutosh Tripathi; Hao Zhu; Antreas Afantitis; Varnavas D Mouchlis; Georgia Melagraki; Ivan Rusyn; Alexander Tropsha
Journal:  Toxicol Appl Pharmacol       Date:  2013-05-23       Impact factor: 4.219

4.  Evaluation of OASIS QSAR Models Using ToxCast™ in Vitro Estrogen and Androgen Receptor Binding Data and Application in an Integrated Endocrine Screening Approach.

Authors:  Barun Bhhatarai; Daniel M Wilson; Paul S Price; Sue Marty; Amanda K Parks; Edward Carney
Journal:  Environ Health Perspect       Date:  2016-05-06       Impact factor: 9.031

  4 in total

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