Confident transformation site localization of PROTAC drug metabolites facilitated by multi-stage fragmentation LC-MS

Significance of the topic

Proteolysis targeting chimeras (PROTACs) represent an emerging drug modality that harnesses the cell’s degradation machinery to selectively down-regulate disease-related proteins. Their bifunctional structure, however, complicates metabolic characterization because metabolites can arise at multiple sites across large, flexible linkers and protein-binding ligands. Confident localization of transformation sites on low-abundance drug metabolites is essential for lead optimization, safety assessment and regulatory filings in pharmaceutical research.

Study objectives and overview

This work illustrates the application of multi-stage fragmentation mass spectrometry (MSn) and intelligent data acquisition workflows to profile in vitro metabolites of two model PROTACs (MZ1 and dBET1). The goal was to demonstrate how high-resolution accurate mass (HRAM) MS2 and MS3 data acquired on a Tribrid mass spectrometer can be automatically processed to localize biotransformation sites and identify soft spots along linkers and ligands.

Methodology and instrumentation

Chemical incubations were performed by reacting 5 µM of each PROTAC with human liver S9 fraction (1 mg/mL) in phosphate buffer (pH 7.4) at 37 °C for 0 to 4 h. Reactions were quenched with ice-cold acetonitrile and centrifuged before UHPLC–MS analysis. Key instrumentation and software included:

• Vanquish Horizon UHPLC system with Accucore C18 column (2.1×100 mm, 2.6 µm)
• Orbitrap Ascend Biopharma Tribrid mass spectrometer equipped with OptaMax NG heated electrospray source
• EASY-IC internal calibration and AcquireX background exclusion for intelligent MSn acquisition
• Data-dependent MS2–HCD for precursors < 500 Da; MS2–CID plus stepped MS3 (CID/HCD) for > 500 Da
• Compound Discoverer 3.3 Expected Metabolite ID workflow with FISh scoring for automated fragment annotation

Main results and discussion

Using this workflow, 24 metabolites of MZ1 and 12 of dBET1 were detected and structurally annotated. MZ1 metabolism was dominated by linker cleavage (“dealkylation”) and site-specific oxidations, whereas dBET1 underwent phthalimide ring hydrolysis and oxidation. Multi-stage fragmentation spectra enabled clear localization of modifications: for example, MS3 fragmentation of the sodium adduct of an MZ1 “+O” metabolite (M18) revealed an oxidation on the BRD4-binding moiety, while a distinct MS3 pattern on a second “+O” isomer (M23) pinpointed oxidation to the linker. Similarly, two hydration isomers of dBET1 (“+H2O”) could be distinguished by their MS2 fingerprint.

Benefits and practical applications

This approach allows confident detection of low-abundance metabolites and precise assignment of transformation sites without the need for targeted re-acquisition. Automated fragment ion annotation accelerates data review, supporting lead optimization, ADME profiling and regulatory submissions in drug discovery and development.

Future trends and potential applications

Emerging opportunities include integration of machine-learning algorithms for automated spectral interpretation, coupling of MSn workflows with ion mobility separation to resolve isomers, and real-time decision tree optimization. These advances will further streamline PROTAC metabolism studies and can be extended to other large-molecule modalities.

Conclusion

High-quality MS2 and MS3 data acquired on the Orbitrap Ascend Biopharma Tribrid, combined with intelligent acquisition and automated data processing in Compound Discoverer, provide a robust platform for PROTAC metabolite profiling. The study underscores the impact of linker chemistry on metabolic soft spots and demonstrates how MSn workflows enhance structural elucidation of complex drug candidates.

Reference

1. Hu Z. et al. Recent Developments in PROTAC-mediated Protein Degradation: From Bench to Clinic. Chembiochem 2022;23:e202100270.
2. Goracci L. et al. Understanding the Metabolism of Proteolysis Targeting Chimeras (PROTACs): The Next Step toward Pharmaceutical Applications. J. Med. Chem. 2020;63:11615.
3. Comstock K., Du M., Jiang M. Confident drug metabolite identification using an intelligent data acquisition and processing workflow. Thermo Fisher Scientific Application Note 65953, 2021.