4.6 Article

Bioactivation of Isoxazole-Containing Bromodomain and Extra-Terminal Domain (BET) Inhibitors

Journal

METABOLITES
Volume 11, Issue 6, Pages -

Publisher

MDPI
DOI: 10.3390/metabo11060390

Keywords

bromodomain; inhibitor; isoxazole; model; deep neural network; pathway; bioactivation; reactive metabolite; quinone; glutathione

Funding

  1. National Library of Medicine of the National Institutes of Health [R01LM012222, R01LM012482, R01GM140635]
  2. National Institutes of Health [1S10RR022984-01A1, 1S10OD018091-01]
  3. National Institute of General Medical Sciences [T32GM106999]
  4. Winthrop P Rockefeller Cancer Institute at the University of Arkansas for Medical Sciences
  5. BBSRC
  6. GSK [BB/M015157/1]
  7. St Hugh's College, Oxford

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The 3,5-dimethylisoxazole motif is widely used in BET inhibitors but may lead to the formation of toxic reactive metabolites. A study combining deep neural models and experimental validation predicted the bioactivation pathways of these inhibitors, with a focus on novel extended quinone-methides. The results highlighted the need to improve overall bioactivation scaling and potential concerns for toxicity in the development of new drug leads.
The 3,5-dimethylisoxazole motif has become a useful and popular acetyl-lysine mimic employed in isoxazole-containing bromodomain and extra-terminal (BET) inhibitors but may introduce the potential for bioactivations into toxic reactive metabolites. As a test, we coupled deep neural models for quinone formation, metabolite structures, and biomolecule reactivity to predict bioactivation pathways for 32 BET inhibitors and validate the bioactivation of select inhibitors experimentally. Based on model predictions, inhibitors were more likely to undergo bioactivation than reported non-bioactivated molecules containing isoxazoles. The model outputs varied with substituents indicating the ability to scale their impact on bioactivation. We selected OXFBD02, OXFBD04, and I-BET151 for more in-depth analysis. OXFBD's bioactivations were evenly split between traditional quinones and novel extended quinone-methides involving the isoxazole yet strongly favored the latter quinones. Subsequent experimental studies confirmed the formation of both types of quinones for OXFBD molecules, yet traditional quinones were the dominant reactive metabolites. Modeled I-BET151 bioactivations led to extended quinone-methides, which were not verified experimentally. The differences in observed and predicted bioactivations reflected the need to improve overall bioactivation scaling. Nevertheless, our coupled modeling approach predicted BET inhibitor bioactivations including novel extended quinone methides, and we experimentally verified those pathways highlighting potential concerns for toxicity in the development of these new drug leads.

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