ER/AR Multi-Conformational Docking Server: A Tool for Discovering and Studying Estrogen and Androgen Receptor...

Area of Science:

• Endocrinology
• Computational Chemistry
• Toxicology

Background:

• Endocrine-disrupting chemicals (EDCs) pose environmental risks.
• Predicting estrogen receptor (ER) and androgen receptor (AR) activity is crucial for EDC identification.
• Existing databases lack comprehensive structural and modulator data for ER and AR.

Purpose of the Study:

• To develop a predictive tool for ER and AR activity using molecular docking and similarity searches.
• To provide a centralized resource (EARDB) of ER, ERβ, and AR protein structures and modulators.
• To facilitate the identification of potential EDCs and novel ER/AR modulators.

Main Methods:

• Collected and curated ERα, ERβ, and AR protein structures and known small molecule modulators.
• Developed a web server integrating multi-conformation molecular docking for user-submitted molecules.
• Implemented a 2D similarity search function against known ER/AR modulators.

Main Results:

• The EARDB provides a unique collection of ER/AR data and predictive tools.
• Molecular docking predicts binding affinity, while similarity search identifies related compounds.
• Low binding energy or high similarity suggests potential EDC activity or novel modulator properties.

Conclusions:

• The EARDB serves as a valuable tool for predicting endocrine activity of compounds.
• It aids in drug design for ER and AR pathways.
• The platform supports the identification and assessment of endocrine-disrupting chemicals.