Back

Analysis of Large Peptide Collisional Cross Section Dataset Reveals Structural Origin of Bimodal Behavior

Xu, A. M.; Szoelloesi, D.; Grubmuller, H.; Regev, O.

2025-09-16 bioinformatics
10.1101/2025.09.10.675470 bioRxiv
Show abstract

Recent advances in ion mobility spectrometry have enabled the measurement of rotationally averaged collisional cross-sectional area (CCS) for millions of peptides, as part of routine proteomic mass spectrometry workflows. One of the most striking finding in recent large ion mobility datasets is that CCS exhibits two distinct modes, most notably for charge 3+ peptides. Here, using classical machine learning approaches, we identify that basic site positioning is a key sequence feature determining if a peptide belongs to the high or low CCS mode. Molecular dynamics simulations suggest that peptides in the high CCS mode tend to adopt more extended conformations and form charge-stabilized helical structures, whereas those in the low CCS mode adopt more compact, globular conformations. Further supporting this structural hypothesis, we provide evidence for preferential protonation near the C-terminus, and uncover multiple position-dependent sequence determinants that all suggest the predominance of helix formation in the high mode. Together, these findings will enable better integration of CCS measurements into protein identification and quantification pipelines, improving the performance of ion mobility-based proteomics.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.