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Updated: May 25, 2026

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry
Published on: October 2, 2016
Physicochemical Characterization and Metabolites Identification of the Synthetic Cannabinoid MDMB-5'Br-PINACA Using
Alexandre B Godoi1,2, Natalícia J Antunes3, Júlio C C da Silva4
1Campinas Poison Control Center, Universidade Estadual de Campinas (UNICAMP), Campinas, SP 13083-859, Brazil.
Abstract:
MDMB-5'Br-PINACA is a recently identified brominated synthetic cannabinoid that was detected in herbal materials seized in Brazil in 2025, raising concerns regarding further potential intoxication cases. In this sense, the evaluation of physicochemical properties and metabolic fate may improve its analytical detectability. Therefore, an integrated in silico and in vitro approach was employed to investigate the physicochemical properties and phase I metabolism of MDMB-5'Br-PINACA. Physicochemical parameters and predicted metabolic pathways were first evaluated using BioTransformer 3.0 and XenoSite, providing complementary insights into likely sites of metabolism. In vitro metabolism was subsequently assessed using pooled human liver microsomes associated with liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) analysis. MS2-based molecular networking (MN) was applied as an exploratory and confirmatory strategy to guide metabolite annotation by clustering structurally related features and prioritizing candidates linked to MDMB-5'Br-PINACA. A total of twenty-seven metabolites were level 2 annotated, encompassing aliphatic and aromatic hydroxylation, sequential alcohol oxidation to ketone, aldehyde, and carboxylic acid derivatives, ester hydrolysis, intramolecular lactone formation, and N-dealkylation with loss of the pentyl side chain. Hydroxylations of the pentyl chain and tert-butyl moiety and secondary oxidative reactions emerged as the predominant pathways under the experimental conditions, in agreement with in silico predictions. However, lactone formation was exclusively revealed by in vitro experiments, demonstrating limitations of current in silico prediction approaches. The integration of computational prediction, LC-HRMS, and MN substantially enhanced metabolite coverage and confidence of structural assignment. These findings provide a detailed metabolic map of MDMB-5'Br-PINACA and underscore the value of combining in silico and in vitro approaches to improve metabolite identification, supporting forensic and clinical investigations of intoxication involving this synthetic cannabinoid.
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