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Journal Article

Citation

Drug E, Marder D, Binyamin I, Yeffet D, Gershonov E, Dagan S. J. Mass Spectrom. 2024; 59(1): e4994.

Copyright

(Copyright © 2024, John Wiley and Sons)

DOI

10.1002/jms.4994

PMID

38108525

Abstract

Fentanyl and its non-pharmaceutical analogues (NPFs) are potent synthetic opioids, traditionally used for pain management, with ever-increasing illicit uses. Tightening the regulation for known fentanyls leads to new synthetic analogues in the opioid market. Furthermore, the Organization for the Prohibition of Chemical Weapons (OPCW) has recently issued a decision regarding aerosolized use of central nervous system (CNS)-acting agents, such as fentanyl and its analogues, under the concern that these materials could be misused for terror or war purposes. The ever-increasing development of new fentanyl analogues makes the task of detection and identification of these new, unknown analogues crucial. In this work, we introduce an automated tool for the detection and putative identification of "unknown" fentanyl analogues, using liquid chromatography-mass spectrometry (LC-MS) (high-resolution mass spectrometry [HRMS]) analysis, subsequently followed by data processing using the "Compound Discoverer" software. This software, in our modified use, enabled the automatic detection of various fentanyl analogues, by "digging" out components and comparing them to pre-calculated theoretical molecular ions of possible modifications or transformations on the fentanyl backbone structure (no library or database used). Subsequently, structural elucidation for the proposed component of interest is carried out by automated MS/MS data interpretation, as performed by the software. This method was explored on 12 fentanyl-based "unknown" analogues used as model examples, including chemical modifications such as fluorination and methylation. In all tested compounds, automatic detection and identification were achieved, even at concentrations as low as 1 ng/mL in an environmental soil matrix extract.


Language: en

Keywords

Software; Databases, Factual; *Fentanyl; *Tandem Mass Spectrometry; Analgesics, Opioid; analogues; Compound Discoverer; detection; fentanyl; identification; unknown

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