Journal Article

An in silico to in vivo approach identifies retinoid-X receptor activating tert-butylphenols used in food contact materials

Ettayapuram Ramaprasad, Azhagiya Singam, Durkin, Kathleen A., La Merrill, Michele A., Mengeling, Brenda J., Smith, Martyn T., Mansouri, Kamel, Furlow, J. David, Kleinstreuer, Nicole C., Turkieh, Dania

2025

Overview

The potential for food contact chemicals to disrupt genetic programs in development and metabolism raises concerns. Nuclear receptors (NRs) control many of these programs, and the retinoid-X receptor (RXR) is a DNA-binding partner for one-third of the NRs. RXR disruption could generate adverse outcomes in several NR pathways. We used machine learning and other in silico methods to identify RXR-interacting candidates from a list of over 57,000 chemicals. Butylphenols comprised the largest, high-probability, structural group (58 compounds); several are food contact chemicals with widespread commercial use. In vitro ToxCast data suggested that bulky, aliphatic substitution at C4 of 2,6-di-tert-butylphenol facilitated RXR activation. We tested six butylphenols with increasing bulk at C4 in vivo for their ability to disrupt thyroid hormone receptor (TR) signaling, using an integrated luciferase reporter driven by TR-RXR binding and quantifiable morphological changes in a Xenopus laevis precocious metamorphosis assay. Three tert-butylphenols potentiated TH action at nanomolar concentrations. Molecular modeling showed the three positives formed more frequent, stable interactions with RXRα, and bulkiness at C4 increased steric complementarity with the RXR ligand-binding pocket. Our findings establish a paradigm for machine learning coupled with a convenient, in vivo validation approach to identify chemicals interacting with RXR-NR-controlled genetic pathways.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 631/114 / 631/136 / 631/1647 / 631/443 / Agonists / Animals / Artificial intelligence / Chemicals / Complementarity / Computer Simulation / Energy / Environmental exposure / Food / Food contact chemicals / Humanities and Social Sciences / Humans / Learning algorithms / Ligands / Machine Learning / Metamorphosis / Models, Molecular / Molecular docking / Molecular modelling / multidisciplinary / Nuclear receptors / Phenols / Phenols - chemistry / Phenols - pharmacology / Principal components analysis / Protein Binding / Receptors, Thyroid Hormone - metabolism / Retinoid X receptors / Retinoid X Receptors - chemistry / Retinoid X Receptors - metabolism / Retinoid-X receptor / Science / Science (multidisciplinary) / Signal Transduction - drug effects / Thyroid / Thyroid gland / Xenopus laevis