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Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
Published on: November 15, 2013
Genetic Polymorphisms in Nuclear Receptors Drive Variations in Responses to Environmental Exposures
Shaoqi Zuo1, Kun Zhang1, Jiayin Dai1
1State Environmental Protection Key Laboratory of Environmental Health Impact Assessment of Emerging Contaminants, School of Environmental Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China.
Abstract:
Single nucleotide polymorphisms (SNPs) are well-known for shaping human drug responses and disease susceptibility, yet their role in mediating environmental responses remains largely unexplored. Here, we systematically investigated SNPs within the ligand-binding domains (LBDs) of 48 nuclear receptors (NRs), focusing on their influence on receptor-ligand interactions. Through the integration of genomic databases, we identified 27 missense SNPs with global minor allele frequencies (MAFs) of >0.001 and mapped their distribution across NR LBDs. Structure-based molecular docking revealed significant differences in the ligand-binding affinities between wild-type and variant receptors, with differential docking index (DDI) scores ranging from 0.7 to 30.5. Functional validation demonstrated altered transcriptional activity for estrogen-related receptor alpha (ERRα, Leu388Phe) and retinoid X receptor alpha (RXRα, Met254Ile) in response to diverse environmental chemicals. Notably, the ERRα variant exhibited divergent responses to different classes of modulators, whereas the RXRα variant showed attenuated activation to multiple agonists, particularly organotin compounds at environmentally relevant concentrations. Population-level analysis further showed geographic variations in allele frequencies, suggesting potential variability in environmental susceptibility among populations. Collectively, these findings emphasize the critical role of SNPs in shaping individual and population-level responses to environmental exposures, highlighting the need to incorporate SNP data into toxicological risk assessment frameworks.
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