Literature DB >> 18937440

Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity.

Lívia B Salum1, Igor Polikarpov, Adriano D Andricopulo.   

Abstract

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpha (hERalpha) and beta (hERbeta). Because the levels and relative proportion of hERalpha and hERbeta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hERalpha and hERbeta. Significant statistical coefficients were obtained (hERalpha, q(2) = 0.76; hERbeta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hERalpha and hERbeta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design of novel hER modulators with improved selectivity.

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Year:  2008        PMID: 18937440     DOI: 10.1021/ci8002182

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


  6 in total

1.  Fragment-guided approach to incorporating structural information into a CoMFA study: BACE-1 as an example.

Authors:  Lívia Barros Salum; Napoleão Fonseca Valadares
Journal:  J Comput Aided Mol Des       Date:  2010-07-27       Impact factor: 3.686

2.  Computational estimation of rainbow trout estrogen receptor binding affinities for environmental estrogens.

Authors:  Conrad Shyu; Timothy D Cavileer; James J Nagler; F Marty Ytreberg
Journal:  Toxicol Appl Pharmacol       Date:  2010-11-12       Impact factor: 4.219

Review 3.  Fragment-based QSAR: perspectives in drug design.

Authors:  Lívia B Salum; Adriano D Andricopulo
Journal:  Mol Divers       Date:  2009-01-31       Impact factor: 2.943

4.  Multiple-targeting and conformational selection in the estrogen receptor: computation and experiment.

Authors:  Peng Yuan; Kaiwei Liang; Buyong Ma; Nan Zheng; Ruth Nussinov; Jian Huang
Journal:  Chem Biol Drug Des       Date:  2011-04-27       Impact factor: 2.817

5.  In silico prediction of estrogen receptor subtype binding affinity and selectivity using statistical methods and molecular docking with 2-arylnaphthalenes and 2-arylquinolines.

Authors:  Zhizhong Wang; Yan Li; Chunzhi Ai; Yonghua Wang
Journal:  Int J Mol Sci       Date:  2010-09-20       Impact factor: 5.923

6.  Computational study of estrogen receptor-alpha antagonist with three-dimensional quantitative structure-activity relationship, support vector regression, and linear regression methods.

Authors:  Ying-Hsin Chang; Jun-Yan Chen; Chiou-Yi Hor; Yu-Chung Chuang; Chang-Biau Yang; Chia-Ning Yang
Journal:  Int J Med Chem       Date:  2013-05-14
  6 in total

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