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In silico and in vitro metabolism studies of the new synthetic opiate AP-237 (bucinnazine) using bioinformatics tools

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Abstract

The recent emergence of new synthetic opioids (NSOs) compounds in the illicit market is increasingly related to fatal cases. Identification and medical care of NSO intoxication cases are challenging, particularly due to high frequency of new products and extensive metabolism. As the study of NSO metabolism is crucial for the identification of these drugs in cases of intoxication, we aimed to investigate the metabolism of the piperazine NSO AP-237 (= bucinnazine). Two complementary approaches (in silico and in vitro) were used to identify putative AP-237 metabolites which could be used as consumption markers. In silico metabolism studies were realized by combining four open access softwares (MetaTrans, SyGMa, Glory X, Biotransformer 3.0). In vitro experiments were performed by incubating AP-237 (20 µM) in differentiated HepaRG cells during 0 h, 8 h, 24 h or 48 h. Cell supernatant were extracted and analyzed by liquid chromatography coupled to high-resolution mass spectrometry and data were reprocessed using three strategies (MetGem, GNPS or Compound Discoverer®). A total of 28 phase I and six phase II metabolites was predicted in silico. Molecular networking identified seven putative phase I metabolites (m/z 203.154, m/z 247.180, m/z 271.180, two m/z 289.191 isomers, m/z 305.186, m/z 329.222), including four previously unknown metabolites. Overall, this cross-disciplinary approach with molecular networking on data acquired in vitro and in silico prediction enabled to propose relevant candidate as AP-237 consumption markers that could be added to mass spectrometry libraries to help diagnose intoxication.

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Funding

This work was funded by Rennes University to Thomas Gicquel with "Défi Scientifique" grant.

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Correspondence to Romain Pelletier.

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Pelletier, R., Bourdais, A., Fabresse, N. et al. In silico and in vitro metabolism studies of the new synthetic opiate AP-237 (bucinnazine) using bioinformatics tools. Arch Toxicol 98, 165–179 (2024). https://doi.org/10.1007/s00204-023-03617-x

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