A Computational-Based Approach to Identify Estrogen Receptor α/β Heterodimer Selective Ligands

Autor: Menggang Yu, Fabao Liu, Chelsie K. Sievers, Muxuan Liang, Wei Xu, Yidan Wang, Yoongho Lim, Carlos G. Coriano
Rok vydání: 2018
Předmět:
Zdroj: Molecular Pharmacology. 93:197-207
ISSN: 1521-0111
0026-895X
DOI: 10.1124/mol.117.108696
Popis: The biologic effects of estrogens are transduced by two estrogen receptors (ERs), ERα and ERβ, which function in dimer forms. The ERα/α homodimer promotes and the ERβ/β inhibits estrogen-dependent growth of mammary epithelial cells; the functions of ERα/β heterodimers remain elusive. Using compounds that promote ERα/β heterodimerization, we have previously shown that ERα/β heterodimers appeared to inhibit tumor cell growth and migration in vitro. Further dissection of ERα/β heterodimer functions was hampered by the lack of ERα/β heterodimer-specific ligands. Herein, we report a multistep workflow to identify the selective ERα/β heterodimer-inducing compound. Phytoestrogenic compounds were first screened for ER transcriptional activity using reporter assays and ER dimerization preference using a bioluminescence resonance energy transfer assay. The top hits were subjected to in silico modeling to identify the pharmacophore that confers ERα/β heterodimer specificity. The pharmacophore encompassing seven features that are potentially important for the formation of the ERα/β heterodimer was retrieved and subsequently used for virtual screening of large chemical libraries. Four chemical compounds were identified that selectively induce ERα/β heterodimers over their respective homodimers. Such ligands will become unique tools to reveal the functional insights of ERα/β heterodimers.
Databáze: OpenAIRE