Software-Assisted Automated Detection and Identification of "Unknown" Analogues: Implementation on V-Type Nerve Agents

Software-assisted automated detection and identification of "unknown" 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 "unknown" 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.

Software-assisted automated detection and identification of "unknown" fentanyl analogues

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.

Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS

Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.

Integrating Effect-Directed Analysis and Chemically Indicative Mass Spectral Fragmentation to Screen for Toxic Organophosphorus Compounds

Analytical chemists are often challenged to screen for bioactive compounds in complex matrices, sometimes without a priori knowledge of the exact compound of interest. Therefore, "flagging" techniques, highlighting common characteristics of bioactive compounds, are highly sought after. In this work, we demonstrate a double flagging method, where unknown organophosphorus acetylcholinesterase inhibitors are "flagged" out of a complex matrix by the presence of organophosphorus-indicative ions as well as their acetylcholinesterase inhibition. This is accomplished by flagging the LC chromatographic retention time of phosphorus-indicative ions using accurate mass high-energy in-source CID products, and the retention time of acetylcholinesterase inhibiting compounds using a parallel microfractionation-based bioassay. We successfully apply this method to screen VX, VM, and RVX nerve agents as well as methomyl, a carbamate pesticide, out of soil and whole blood samples at low μM to sub-μM concentrations. This methodology can be easily extended to diverse chemical families and biological activities of interest.