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

基于计算的识别雌激素受体 α/β 异二聚体选择性配体的方法

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作者:Carlos G Coriano, Fabao Liu, Chelsie K Sievers, Muxuan Liang, Yidan Wang, Yoongho Lim, Menggang Yu, Wei Xu

Abstract

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.

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