ROUTINE METABOLITE IDENTIFICATION FOR COMPLEX PEPTIDES BASED ON IMS ENABLED QTOF DIA DATA ACQUISITION AND MASS-METASITE DATA PROCESSING

Importance of the Topic

Accurate and rapid characterization of peptide drug metabolites is critical for assessing ADME profiles and ensuring safety and efficacy, especially for complex peptides with non-natural modifications.

Objectives and Study Overview

This study demonstrates a streamlined workflow combining ion mobility-enabled DIA acquisition on a Vion IMS QToF with Mass-MetaSite and WebMetabase software processing to profile metabolites of five FDA-approved cyclic peptides after simulated intestinal digestion.

Methodology and Instrumentation

• Peptide Incubation: Daptomycin, Dalbavancin, Oritavancin, Anidulafungin, and Lanreotide at 10 μM in simulated intestinal fluid with 1000 μg/mL chymotrypsin, sampled over 0–300 minutes.
• Chromatography: ACQUITY H-Class UPLC with Peptide BEH C18 column, 5–40% B over 8 minutes, flow 0.4 mL/min, 60°C.
• Mass Spectrometry: Vion IMS QToF using HDMSE with Intelligent Data Capture for real-time denoising and data compression.
• Data Processing: Mass-MetaSite and WebMetabase for macromolecule metabolite identification and visualization.

Main Results and Discussion

Turnover rates varied from very low for Anidulafungin to medium for Daptomycin and Lanreotide. CCS-filtered extracted ion chromatograms revealed clear metabolite peaks and reduced background noise. Daptomycin metabolites included mono- and dihydrolysis and demethylation products with CCS ranges of 404.5–407.7 Å2. Dalbavancin demethylated forms displayed CCS values between 454.9 and 458.5 Å2. WebMetabase generated cluster plots of response over time and ranked proposed structures based on mass error and MS area criteria.

Practical Benefits and Applications of the Method

• Enhanced separation of isobaric metabolites through ion mobility filtering.
• Over 70% reduction in data file size via intelligent data capture.
• Automated, comprehensive identification of cyclic peptide metabolites.
• Scalable workflow suitable for early ADME screening and QA/QC laboratories.

Future Trends and Potential Applications

Advances in real-time noise reduction and integrated HRMS-IMS algorithms are expected to further improve identification confidence and throughput. Expansion of the workflow to small molecule analyses and adoption of cloud-based processing will enhance accessibility and scalability.

Conclusion

The combination of ion mobility-enabled DIA acquisition with Mass-MetaSite and WebMetabase software offers a robust and efficient platform for routine metabolite profiling of complex peptides, delivering high data quality, reduced processing time, and comprehensive structural insights.

References

• Wrona W. et al. Somatostatin Analogue Catabolite Screening and Identification Using Vion IMS QTof with WebMetabase. Waters Corp., 720006586EN.
• Radchenko A. et al. Software-aided approach to investigate peptide structure and metabolic susceptibility of amide bonds in peptide drugs. PLOS One, 2017.
• Mortishire-Smith R. et al. Intelligent Data Capture: Real-Time Noise Reduction for High Resolution Mass Spectrometry. Waters White Paper LITR135023115.