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Updated: May 12, 2026

Combining Chemical Cross-linking and Mass Spectrometry of Intact Protein Complexes to Study the Architecture of Multi-subunit Protein Assemblies
Published on: November 28, 2017
Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers
Lutz Fischer1, Zhuo Angel Chen, Juri Rappsilber
1Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, United Kingdom.
Quantitative cross-linking/mass spectrometry (CLMS) is now feasible for studying dynamic protein complexes. We developed a new strategy and open-source software (XiQ) to overcome limitations in quantifying cross-linked proteins.
Area of Science:
- Biochemistry
- Proteomics
- Structural Biology
Background:
- Dynamic proteins and multi-protein complexes are crucial for biological processes.
- Cross-linking/mass spectrometry (CLMS) provides residue-level structural data for static protein assemblies.
- Quantifying dynamic changes in protein complexes remains a challenge.
Purpose of the Study:
- To investigate the technical feasibility of quantitative CLMS using isotope labeling.
- To develop and validate a method for quantifying cross-linked protein interactions.
- To create an open-source software solution for analyzing quantitative CLMS data.
Main Methods:
- Cross-linking of human serum albumin (HSA) with BS3-d0/4 at different isotope ratios.
- Analysis of cross-linked peptides using mass spectrometry.
- Development of the open-source software XiQ for quantitative CLMS data analysis.
Main Results:
- Isotope labeling slightly reduced the number of identified cross-links.
- Standard quantitative proteomics software was unsuitable for CLMS data.
- The developed XiQ software enabled the quantification of cross-linking data, demonstrating technical feasibility.
Conclusions:
- Quantitative CLMS is technically feasible for studying dynamic protein interactions.
- The developed strategy and XiQ software facilitate the analysis of dynamic biological processes.
- This work lays the foundation for easier study of molecular details in biological systems.
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