Confident drug metabolite identification using an intelligent data acquisition and processing workflow

Significance of Topic

High-resolution accurate mass spectrometry (HRAM MS) has become indispensable in drug discovery for characterizing biotransformation products. Its combination of sub-ppm mass accuracy, isotope fine structure analysis, and detailed MS/MS fragmentation enables unequivocal identification of drug metabolites, which is critical for safety assessment and pharmacokinetic studies.

Study Objectives and Overview

This work evaluates an integrated workflow comprising a Thermo Scientific™ Orbitrap Exploris™ 240 mass spectrometer with AcquireX™ intelligent data acquisition, a Vanquish™ Horizon UHPLC system, and Compound Discoverer™ software. The aim is to enhance confidence and coverage in identifying low-level metabolites of model compounds (nefazodone, montelukast, timolol) in complex biological matrices.

Methodology and Instrumentation

Sample Preparation

• Incubation of 10 µM compounds with human/rat liver microsomes and cofactors (NADPH, UDPGA, GSH).
• Quenching with acetonitrile, protein precipitation, concentration, and spiking into plasma.

Chromatography

• Vanquish Horizon UHPLC with Hypersil GOLD™ C18 column (2.1 × 50 mm, 1.9 µm) at 50 °C, 0.5 mL/min.
• Gradient from 5 % to 95 % organic (acetonitrile/ammonium formate/formic acid).

Mass Spectrometry

• Orbitrap Exploris 240 with OptaMax™ NG source, EASY-IC™ internal calibration.
• Full MS (60 000 resolution) followed by Top-N ddMS2 (15 000 resolution) with fast polarity switching.
• AcquireX workflows for automated background exclusion and targeted inclusion list generation.

Data Processing

• Compound Discoverer™ 3.2 with MetID workflow for expected and unknown metabolites.
• Nodes for background subtraction, expected compound finding, fragment ion search (FISh), pattern and class scoring.

Key Results and Discussion

The high scan speed and AcquireX background exclusion workflow increased MS/MS coverage of drug-related ions by 30–50 % over conventional DDA. For nefazodone, the number of metabolites triggering MS/MS rose from 10 to 21. Montelukast metabolites increased from 4 to 11, and timolol from 5 to 7. Sub-ppm mass accuracy and isotope fine structure confirmed elemental compositions (e.g., C13H24O5N4S for a timolol metabolite). Intelligent data processing automated fragment annotation and enabled discovery of unexpected biotransformations such as N-dealkylation.

Benefits and Practical Applications

• Comprehensive metabolite profiling in a single run without repeated injections.
• Enhanced detection of low-abundance metabolites masked by matrix interferences.
• Streamlined workflow with automated list generation and data processing.
• Improved confidence in structural assignments through automated fragment matching.

Future Trends and Opportunities

Integration of machine learning models for predicting biotransformations, real-time adaptive acquisition strategies, and deeper scanning of challenging matrices will further advance metabolite profiling. The coupling of advanced data analytics with HRAM MS instrumentation will accelerate drug candidate evaluation and safety assessments.

Conclusion

The combined Orbitrap Exploris 240, Vanquish Horizon UHPLC, AcquireX workflows, and Compound Discoverer software deliver a robust and efficient platform for confident drug metabolite identification. The intelligent acquisition and processing significantly improve MS/MS coverage and streamline the discovery of both expected and unexpected metabolites in complex biological samples.

References

• Zhu M. et al. Drug Metabolite Profiling and Identification by High-Resolution Mass Spectrometry. Journal of Biological Chemistry 2011;286(29):25419–25425.
• Thermo Fisher Scientific. Smart Note: AcquireX Intelligent Data Acquisition Technology for Orbitrap Tribrid Mass Spectrometers. SN65392-EN 0720M.
• Thermo Fisher Scientific. White Paper: Compound Discoverer Software – Compounding Insights for Small Molecule Research. WP65210-EN 0518S.