A Computational-Based Approach to Identify Estrogen Receptor alpha/beta Heterodimer Selective Ligands

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

来源：Molecular Pharmacology, 2018, 93(3): 197-207.

DOI：10.1124/mol.117.108696

The biologic effects of estrogens are transduced by two estrogen receptors (ERs), ER alpha and ER beta, which function in dimer forms. The ER alpha/alpha homodimer promotes and the ER beta/beta inhibits estrogen-dependent growth of mammary epithelial cells; the functions of ER alpha/beta heterodimers remain elusive. Using compounds that promote ER alpha/beta heterodimerization, we have previously shown that ER alpha/beta heterodimers appeared to inhibit tumor cell growth and migration in vitro. Further dissection of ERa/b heterodimer functions was hampered by the lack of ER alpha/beta heterodimer-specific ligands. Herein, we report a multistep workflow to identify the selective ER alpha/beta 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 ER alpha/beta heterodimer specificity. The pharmacophore encompassing seven features that are potentially important for the formation of the ER alpha/beta heterodimer was retrieved and subsequently used for virtual screening of large chemical libraries. Four chemical compounds were identified that selectively induce ER alpha/beta heterodimers over their respective homodimers. Such ligands will become unique tools to reveal the functional insights of ER alpha/beta heterodimers.

• 出版日期2018-3-1