Ecotoxicology and Environmental Safety (Oct 2023)

In silico simulations and molecular descriptors to predict in vitro transactivation potencies of Baikal seal estrogen receptors by environmental contaminants

  • Hoa Thanh Nguyen,
  • Yuka Yoshinouchi,
  • Masashi Hirano,
  • Kei Nomiyama,
  • Haruhiko Nakata,
  • Eun-Young Kim,
  • Hisato Iwata

Journal volume & issue
Vol. 265
p. 115495

Abstract

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Baikal seals (Pusa sibirica) are vulnerable to high levels of organic pollutants. Here, we evaluated the transactivation potencies of bisphenols (BPs) and hydroxylated polychlorinated biphenyls (OH-PCBs) via the Baikal seal estrogen receptor α and β (bsERα and bsERβ) using in vitro and in silico approaches. In vitro reporter gene assays showed that most BPs and OH-PCBs exhibited estrogenic activity with bsER sub-type-specific potency. Among the BPs tested, bisphenol AF showed the lowest EC50 for both bsERs. 4′-OH-CB50 and 4′-OH-CB30 showed the lowest EC50 among OH-PCBs tested for bsERα and bsERβ, respectively. 4-((4-Isopropoxyphenyl)-sulfonyl)phenol, 4′-OH-CB72, and 4′-OH-CB121 showed weak bsERα-specific transactivation. Only 4-OH-CB107 did not affect both bsERs. In silico docking simulations revealed the binding affinities of these chemicals to bsERs and partially explained the in vitro results. Using the in silico simulations and molecular descriptors as explanatory variables and the in vitro results as objective variables, the quantitative structure-activity relationship (QSAR) models constructed for classification and regression accurately separated bsER-active compounds from non-active compounds and predicted the in vitro bsERα- and bsERβ-transactivation potencies, respectively. The QSAR models also suggested that chemical polarity, van der Waals surface area, bridging atom structure, position of the phenolic-OH group, and ligand interactions with key residues of the ligand binding pocket are critical variables to account for the bsER transactivation potency of the test compounds. We also succeeded in constructing computational models for predicting in vitro transactivation potencies of mouse ERs in the same manner, demonstrating the applicability of our approach independent of species-specific responses.

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