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Related Experiment Video

Updated: Nov 2, 2025

T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis
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Sequence-Specific Model for Predicting Peptide Collision Cross Section Values in Proteomic Ion Mobility Spectrometry.

Chih-Hsiang Chang1, Darien Yeung2,3,4, Victor Spicer3

  • 1Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan.

Journal of Proteome Research
|June 16, 2021
PubMed
Summary

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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We developed a new model to predict peptide collision cross section (CCS) values based on amino acid sequence and position. This method improves CCS prediction accuracy by considering how residue position affects peptide structure and charge solvation.

Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Biophysical Chemistry

Background:

  • Collision cross section (CCS) is a key parameter in ion mobility mass spectrometry (IM-MS) for characterizing peptides.
  • Predicting CCS from peptide sequence is crucial for large-scale proteomic analyses and structural elucidation.
  • Existing methods often lack the precision to capture sequence-specific and position-dependent effects on CCS.

Purpose of the Study:

  • To investigate the contribution of peptide amino acid sequence and residue position to collision cross section (CCS) values.
  • To develop an extended prediction model for CCS incorporating position-dependent intrinsic size parameters (ISP).
  • To analyze the impact of residue type, position, charge, hydrophobicity, and helical propensity on peptide ion mobility.

Main Methods:

Keywords:
collision cross section (CCS)ion mobility predictionpeptide ion mobilityposition-dependent intrinsic size parametersequence-specific ion mobility calculator (SSICalc)trapped ion mobility spectrometry

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  • Utilized a large dataset of ~134,000 peptides across four charge states (1+ to 4+).
  • Acquired migration data using 2D LC/trapped ion mobility spectrometry/quadrupole/time-of-flight mass spectrometry (MS).
  • Developed a generalized prediction model by optimizing position-dependent ISPs for eight peptide subsets (tryptic/nontryptic, four charges).

Main Results:

  • Achieved high prediction accuracy of ~0.981 for CCS across the entire peptide population.
  • Demonstrated that charge solvation is strongly influenced by the peptide's ability to solvate positive charges, affected by residue positioning.
  • Found that increased helical propensity and hydrophobicity favor extended structures, leading to higher CCS values.

Conclusions:

  • Peptide sequence and residue position significantly impact CCS values, necessitating position-aware prediction models.
  • Charge solvation and electrostatic interactions play critical roles in determining peptide ion mobility.
  • The developed model provides a more accurate framework for CCS prediction in proteomics and structural studies.