Detection and identification of isotope-labeled glutathionetrapped reactive drug metabolites

Significance of the topic

Rapid and confident identification of drug-derived reactive metabolites is fundamental to ensuring safety and efficacy during drug development. Glutathione trapping assays are a standard approach to detect electrophilic species that can bind macromolecules and cause toxicity. However, traditional neutral loss methods lack sensitivity and selectivity, motivating the adoption of high-resolution accurate mass (HRAM) analysis combined with stable isotope labeling and advanced data processing to improve detection and structural elucidation in complex matrices.

Objectives and overview of the study

This study aimed to demonstrate an integrated workflow for high-throughput profiling and structural characterization of stable isotope–labeled glutathione (GSH) conjugates formed with clozapine in rat liver microsomal incubations. The approach combines liquid chromatography–HRAM mass spectrometry using the Orbitrap Exploris 240 with targeted and untargeted data mining in Thermo Fisher’s Compound Discoverer software to achieve comprehensive and unbiased metabolite identification.

Methodology and instrumentation

Rat liver microsomes were incubated with clozapine, NADPH, and a 1:1 mixture of unlabeled and [13C2,15N]–labeled GSH. Samples underwent protein precipitation and were analyzed by reversed-phase UHPLC on a Vanquish Flex system coupled to an Orbitrap Exploris 240 operated in positive ion mode with full-scan (m/z 100–1000, 120 000 resolution) and data-dependent HCD-MS2 (30 000 resolution) acquisitions. AcquireX data acquisition enhanced MS2 coverage. Data processing employed a custom node-based workflow in Compound Discoverer 3.3 SP3, integrating Generate Expected Compounds, Pattern Scoring, Search Neutral Losses, FISh Scoring, Compound Class Scoring, and Differential Analysis nodes to detect both predicted and unknown metabolites.

Applied instrumentaion

• Thermo Scientific Orbitrap Exploris 240 mass spectrometer with HESI source
• Vanquish Flex UHPLC system with C18 column (2.5 µm, 100 × 2.1 mm)
• Thermo Scientific Compound Discoverer 3.3 SP3 software
• AcquireX intelligent data acquisition workflow

Main results and discussion

The targeted workflow detected eight expected clozapine–GSH conjugates, each observed as unlabeled/labeled ion pairs (Δ3.0037 Da) at identical retention times with sub-ppm mass accuracy. The untargeted workflow revealed one additional GSH conjugate not present in the predicted list. Pattern Scoring flagged isotope doublets, while the Search Neutral Losses node identified characteristic pyroglutamic acid losses (m/z 129.0425). FISh Scoring provided automated in silico fragmentation annotation, distinguishing positional isomers and confirming modification sites on the clozapine scaffold.

Benefits and practical applications

• Enhanced selectivity and sensitivity for reactive metabolite screening through stable isotope labeling and HRAM detection
• Integrated targeted/untargeted data mining reduces false positives and captures unexpected metabolites
• Automated FISh-based fragment annotation accelerates structure elucidation
• Streamlined workflow increases throughput and confidence in metabolite profiling during lead optimization

Future trends and potential uses

Advances may include expanded isotope labeling strategies, deeper AI-driven data processing, real-time spectral interpretation, and integration with multi-omics platforms. Further development of fragmentation libraries and adaptive acquisition methods will support broader applications in drug metabolism, environmental toxicology, and biomarker discovery.

Conclusion

This work established a robust, high-throughput workflow combining Orbitrap Exploris 240 HRAM analysis and Compound Discoverer software for confident identification and structural characterization of isotope-labeled GSH–trapped drug metabolites. The method delivers comprehensive coverage, high selectivity, and automated annotation, making it valuable for early safety assessment and lead optimization in pharmaceutical research.

Reference

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