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

Feng Wang,Shuai Hu,Shan Chang,Hong-Cheng Li,Qiuye Li,Ren Kong,De-Qing Ma,Jia-Yi Liang

doi:10.3389/fphar.2022.800885

Feng Wang, Shuai Hu + Show 6 more

Open Access

https://doi.org/10.3389/fphar.2022.800885

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Abstract

The prediction of the estrogen receptor (ER) and androgen receptor (AR) activity of a compound is quite important to avoid the environmental exposures of endocrine-disrupting chemicals. The Estrogen and Androgen Receptor Database (EARDB, http://eardb.schanglab.org.cn/) provides a unique collection of reported ERα, ERβ, or AR protein structures and known small molecule modulators. With the user-uploaded query molecules, molecular docking based on multi-conformations of a single target will be performed. Moreover, the 2D similarity search against known modulators is also provided. Molecules predicted with a low binding energy or high similarity to known ERα, ERβ, or AR modulators may be potential endocrine-disrupting chemicals or new modulators. The server provides a tool to predict the endocrine activity for compounds of interests, benefiting for the ER and AR drug design and endocrine-disrupting chemical identification.

Highlights

With the development of chemistry technology, numerous natural or non-natural compounds are synthesized and used in the daily life of human beings such as medicines, perfumes, food additives, automobiles, electronics, pesticides, textiles, plastics, and so on (Barr Dana et al, 2005; Judson et al, 2011)
It is noted that a number of the compounds act as endocrine-disrupting chemicals (EDCs) with the potential to interfere the hormone systems in human or wild lives (Schug et al, 2011; Dionisio et al, 2015)
The receptor files which possess docking poses less than 2 Å rmsd with the native binding ligand are incorporated to the web server to evaluate the user-submitted small molecules

Summary

INTRODUCTION

With the development of chemistry technology, numerous natural or non-natural compounds are synthesized and used in the daily life of human beings such as medicines, perfumes, food additives, automobiles, electronics, pesticides, textiles, plastics, and so on (Barr Dana et al, 2005; Judson et al, 2011). The in silico methods, especially the ligand-based QSAR (quantitative structure–activity relationships) approaches and structural base docking methods, are widely used in the computer-aided drug design field (Mao et al, 2021; Sabe et al, 2021). These methods are applied to predict the compound’s activities against endocrine-related proteins, such as the estrogen receptor (ER) and androgen receptor (AR) (Schneider et al, 2019). The aim is to provide a tool to predict any possible ER or AR effectors with multi-conformational docking models and ligand-based similarity

MATERIAL AND METHODS

RESULTS AND DISCUSSION

DATA AVAILABILITY STATEMENT