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Updated: Jul 18, 2025

Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
Published on: November 15, 2013
Nuclear receptor superfamily structural diversity in pacific oyster: In silico identification of estradiol binding
Tâmela Zamboni Madaloz1, Karin Dos Santos1, Flávia Lucena Zacchi2
1Programa de Pós-Graduação Em Bioquímica, Departamento de Bioquímica, Universidade Federal de Santa Catarina, Florianópolis, SC, 88040-900, Brazil; Laboratório de Biomarcadores de Contaminação Aquática e Imunoquímica, Universidade Federal de Santa Catarina, Florianópolis, SC, 88040-900, Brazil.
Abstract:
The increasing presence of anthropogenic contaminants in aquatic environments poses challenges for species inhabiting contaminated sites. Due to their structural binding characteristics to ligands that inhibit or activate gene transcription, these xenobiotic compounds frequently target the nuclear receptor superfamily. The present work aims to understand the potential interaction between the hormone 17-β-estradiol, an environmental contaminant, and the nuclear receptors of Crassostrea gigas, the Pacific oyster. This filter-feeding, sessile oyster species is subject to environmental changes and exposure to contaminants. In the Pacific oyster, the estrogen-binding nuclear receptor is not able to bind this hormone as it does in vertebrates. However, another receptor may exhibit responsiveness to estrogen-like molecules and derivatives. We employed high-performance in silico methodologies, including three-dimensional modeling, molecular docking and atomistic molecular dynamics to identify likely binding candidates with the target moecule. Our approach revealed that among the C. gigas nuclear receptor superfamily, candidates with the most favorable interaction with the molecule of interest belonged to the NR1D, NR1H, NR1P, NR2E, NHR42, and NR0B groups. Interestingly, NR1H and NR0B were associated with planktonic/larval life cycle stages, while NR1P, NR2E, and NR0B were associated with sessile/adult life stages. The application of this computational methodological strategy demonstrated high performance in the virtual screening of candidates for binding with the target xenobiotic molecule and can be employed in other studies in the field of ecotoxicology in non-model organisms.
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