Quantitative cross-linking/mass spectrometry to elucidate structural changes in proteins and their complexes
Zhuo A Chen1,2, Juri Rappsilber3,4
1Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany.
Nature Protocols
|December 19, 2018
Summary
Quantitative cross-linking/mass spectrometry (QCLMS/QXL-MS) reveals protein structural changes in solution. This method analyzes cross-linked residue pairs to identify conformational shifts and protein interactions with high resolution.
Area of Science:
- Biochemistry
- Structural Biology
- Proteomics
Background:
- Quantitative cross-linking/mass spectrometry (QCLMS/QXL-MS) is a powerful technique for probing protein structure in solution.
- It reveals induced conformational changes, shifts in conformational ensembles, and alterations in protein interactions.
- Cross-links provide unique insights into structural states and changes that may not be detectable by other methods.
Purpose of the Study:
- To present a detailed protocol for QCLMS/QXL-MS analysis.
- To demonstrate both label-free and isotope-labeled workflows for detecting protein structural dynamics.
- To highlight the utility of specific software tools for data analysis and quantitation.
Main Methods:
- Utilized bis(sulfosuccinimidyl)suberate (BS3) as the cross-linking agent.
- Employed both label-free and isotope-labeled cross-linking strategies.
- Used XiSearch software for cross-linked residue pair identification and Skyline for automated quantitation, with manual correction for enhanced accuracy.
Main Results:
- The protocol successfully identified cross-linked residue pairs, indicating structural changes.
- Demonstrated the ability to distinguish between minor local and major conformational changes based on cross-link abundance.
- Showcased the application to purified multi-protein complexes, with potential for broader use.
Conclusions:
- QCLMS/QXL-MS is effective for characterizing protein structural states and dynamics in solution.
- Optimizing cross-linker ratios and peptide fractionation enhances data density and resolution.
- The presented protocol provides a robust framework for structural analysis of proteins and complexes.
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