In vivo and in silico analyses of estrogenic potential of equine estrogens in medaka (Oryzias latipes).

ABSTRACT

Equine estrogens (EEs) are widely used in hormone replacement therapy pharmaceuticals for postmenopausal women. Previous studies have shown that EEs occur in the aquatic environment; however, the potential estrogenicity and risk of EEs in aquatic organisms, including fish, have yet to be studied in detail. Therefore, we evaluated the estrogenic potential of major EEs, namely equilin (Eq), 17α-dihydroequilin (17α-Eq), 17ß-dihydroequilin (17ß-Eq), equilenin (Eqn), 17α-dihydroequilenin (17α-Eqn), and 17ß-dihydroequilenin (17ß-Eqn), on medaka (Oryzias latipes) using in vivo and in silico assays. Quantitative real-time RT-PCR analyses revealed that expression levels of choriogenin L (ChgL) and choriogenin H (ChgH) in medaka embryos responded to various types and concentrations of EEs in a concentration-dependent manner, whereas transcription levels of vitellogenin 1 were not significantly affected by any of the EEs in the concentration range tested. The order of the in vivo estrogenic potencies of EEs was as follows 17ß-Eq > Eq > 17ß-Eqn > Eqn > 17α-Eqn > 17α-Eq. Additionally, the 50% effective concentrations (EC50) of 17ß-Eq was lower than that of 17ß-estradiol. We also investigated the interaction potential of EEs with medaka estrogen receptor (ER) subtypes in silico using a three-dimensional model of the ligand-binding domain (LBD) for each ER and docking simulations. All six EEs were found to interact with the LBDs of ERα, ERß1, and ERß2. The order of the in silico interaction potentials of EEs with each ER LBD was as follows 17ß-Eq > 17α-Eq > Eq > 17ß-Eqn > 17α-Eqn > Eqn. Furthermore, we identified the key amino acids that interact with EEs in each ER LBD; our findings suggest that amino acids and/or their hydrogen bonding may be responsible for the ligand-specific interactions with each ER. This study is the first to comprehensively analyze the estrogenic potential of EEs in medaka both in vivo and in silico.