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Large Data Set Analysis Reveals Structural Origin of Peptide Collisional Cross Section Bimodal Behavior
Allyn M Xu1, Dániel Szöllősi2, Helmut Grubmüller2
1Computer Science Department, Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, United States.
Journal of the American Society for Mass Spectrometry
|December 21, 2025
Summary
Collisional cross-sectional area (CCS) in proteomics reveals two distinct peptide modes. Basic site positioning in peptide sequences dictates these modes, influencing protein identification and quantification in mass spectrometry.
Area of Science:
- Proteomics
- Analytical Chemistry
- Computational Biology
Background:
- Ion mobility spectrometry (IMS) now routinely measures collisional cross-sectional area (CCS) for peptides.
- Large IMS datasets reveal peptides often fall into distinct high or low CCS modes, especially for charge 3+ peptides.
Purpose of the Study:
- To identify sequence features governing peptide CCS modes.
- To elucidate the structural basis for distinct CCS modes in peptides.
Main Methods:
- Machine learning analysis of large IMS datasets.
- Molecular dynamics simulations of peptide conformations.
- Analysis of protonation sites and sequence determinants.
Main Results:
- Basic site positioning is a key determinant of peptide CCS mode.
- High CCS mode peptides adopt extended, helical structures.
- Low CCS mode peptides adopt compact, globular conformations.
- Protonation near the C-terminus and position-dependent determinants favor helix formation in the high CCS mode.
Conclusions:
- Peptide sequence, specifically basic site positioning, dictates CCS mode through conformational preferences.
- Understanding these CCS modes enhances peptide identification and quantification in proteomics.
- This work facilitates improved integration of IMS data into proteomic workflows.
