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Related Experiment Video

Updated: Jun 28, 2026

Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay

Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay

Published on: December 19, 2018

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

Lívia B Salum¹, Igor Polikarpov, Adriano D Andricopulo

¹Laboratorio de Quimica Medicinal e Computacional, Centro de Biotecnologia Molecular Estrutural, Instituto de Fisica de Sao Carlos, Universidade de Sao Paulo, Av Trabalhador Sao-Carlense 400, 13560-970 Sao Carlos-SP, Brazil.

Journal of Chemical Information and Modeling

|October 22, 2008

Summary

Researchers developed computational models to understand how small molecules selectively bind to human estrogen receptor (hER) subtypes alpha and beta. This work aids in designing targeted therapies by differentiating between hERalpha and hERbeta pathways.

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Detecting the Ligand-binding Domain Dimerization Activity of Estrogen Receptor Alpha Using the Mammalian Two-Hybrid Assay

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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

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Published on: August 28, 2019

Area of Science:

Pharmacology
Structural Biology
Computational Chemistry

Background:

Estrogens modulate physiological processes via human estrogen receptor (hER) subtypes alpha (hERalpha) and beta (hERbeta).
Differential expression of hERalpha and hERbeta in target cells necessitates selective ligands for tissue-specific targeting.
Understanding the structural basis of ligand selectivity is crucial for developing targeted therapeutics.

Purpose of the Study:

To elucidate the structural and chemical basis for small molecule discrimination between hERalpha and hERbeta.
To develop predictive computational models for designing selective hER modulators.

Main Methods:

Quantitative Structure-Activity Relationship (QSAR) studies using Comparative Molecular Field Analysis (CoMFA) on 81 hER modulators.
Three-dimensional (3D) target-based approaches, including GRID/Principal Component Analysis (PCA) investigations.
Analysis of five hER crystal structures to generate molecular interaction fields (MIF) maps.

Main Results:

CoMFA models demonstrated high internal consistency for both hERalpha (q(2) = 0.76) and hERbeta (q(2) = 0.70).
Models were validated using external test sets, showing good agreement between predicted and experimental binding affinities.
GRID/PCA successfully separated hERalpha and hERbeta, identifying key structural features influencing subtype selectivity.

Conclusions:

Developed QSAR and GRID/PCA models provide insights into hER subtype selectivity.
3D contour maps highlight critical structural determinants for selective ligand design.
Findings will facilitate the rational design of novel hER modulators with enhanced subtype selectivity for therapeutic applications.