ArticleArchives of toxicology2024
In silico and in vitro metabolism studies of the new synthetic opiate AP-237 (bucinnazine) using bioinformatics tools.
Article in Archives of toxicology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- N-Ethylpentedrone: first hair detection and human metabolic profiling across multiple biological matrices using UHPLC-HRMS, molecular networking and in silico prediction.Archives of toxicology · 2026Article
- Predicting xenobiotic metabolism: a computational approach mining LC-MS/MS data with SIRIUS and BioTransformer.Archives of toxicology · 2026Article
- Identifying metabolites of new psychoactive substances using in silico prediction tools.Archives of toxicology · 2025Article
- Metabolism study of two phenethylamine - derived new psychoactive substances using in silico, in vivo, and in vitro approaches.Archives of toxicology · 2025Article
- Non-Targeted Screening and Identification of the Transformation Pathway of Carbamazepine in the Saemangeum Watershed, Republic of Korea.International journal of molecular sciences · 2024Article
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Authors and funding
7 authors.
Funding
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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