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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
Investigation of a metabolism-dependent aryl hydrocarbon receptor off-target activation for a drug development
Amy G Aslamkhan1, Wen Kang1, Karin Otte2
1Nonclinical Drug Safety, Merck & Co., Inc., Rahway, NJ 07065, United States.
Abstract:
During lead optimization, off-target activation of the aryl hydrocarbon receptor (AhR) was identified for Compound 25. AhR is a xenobiotic-responsive transcription factor associated with adverse outcomes in rodents (and potentially humans) and modulation of drug metabolism. In rats, marked hepatic induction of AhR target genes, Cyp1a1 and Cyp1a2, was observed following repeat dosing and increased with study duration. Compound 25 was inactive in conventional AhR luciferase reporter assays but induced robust Cyp1a1 expression in metabolically competent rat and human HEPATOPAC cultures, suggesting a metabolism-dependent mechanism. Extensive metabolite profiling demonstrated that Compound 25 undergoes complex oxidative and conjugative metabolism; however, specific AhR-active metabolite(s) could not be identified. AhR involvement was confirmed in vivo using AhR knockout and wild-type rats, in which Cyp1a1/2 induction occurred exclusively in wild-type animals. Chromatin immunoprecipitation further demonstrated increased AhR binding at Cyp1a1/2 promoters following Compound 25 treatment. In rat HEPATOPAC cultures, siRNA-mediated knockdown of Por and Cyb5a attenuated Cyp1a1 induction, supporting a requirement for metabolic competence. Consistent with AhR pathway engagement, induction of CYP1A1 in human HEPATOPAC was reduced by the AhR antagonist CH223191. Collectively, these findings demonstrate that AhR activation associated with Compound 25 is dependent on metabolic transformation and may not be detected in conventional reporter assays lacking metabolic capacity. This work highlights the value of metabolically competent hepatocyte models, combined with short-duration in vivo studies, for identifying and mitigating metabolism-dependent AhR liabilities during drug discovery.
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