Software-assisted automated detection and identification of "Нет данных" analogues of benzodiazepines in liquid chromatography mass spectrometry analysis.

RATIONALE: Benzodiazepines (BZDs) construct a large group of psychoactive drugs acting as depressants of the central nervous system (CNS) and used in medicine as sedatives and anxiolytic and antiepileptic agents. The illicit use of these materials is a worldwide problem, and for many years, part of the benzodiazepines have been abused as rape drugs. For example, flunitrazepam (Rohypnol) is most commonly linked by media reports to drug-facilitated sexual assaults, more commonly referred to as "date rape." Furthermore, there are growing concerns for other misuses of these drugs. Over the last few years, there was an increase in the number, type, and availability of new psychoactive substances (NPS) belonging to the benzodiazepine group, challenging standard forensic labs to fully identify the chemical structure of new, unknown benzodiazepines.

METHODS: This work demonstrates a new application of the automated tool for the detection and identification of benzodiazepine analogues using high-resolution-accurate-mass LC-MS analysis, followed by "Compound Discoverer" (CD) software data processing, to automatically detect various benzodiazepine analogues by picking peaks and compare them to in silico calculated modifications made on a predefined basic backbone. Subsequently, a complete structural elucidation for the proposed molecular formula is obtained by MS/MS data analysis of the suspected component.

RESULTS: This method was found to be useful for the automated detection and putative identification of a series of nine "Нет данных" benzodiazepine analogues, at concentrations in the low ng/mL range.

CONCLUSIONS: We hereby present a general demonstration of this powerful tool for the forensic community in the detection and identification of hazardous unknown compounds.