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Quantitative cross-linking/mass spectrometry reveals subtle protein conformational changes.

Zhuo Chen1, Lutz Fischer1, Salman Tahir1

  • 1Wellcome Trust Centre for Cell Biology, Institute of Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3BF, UK.

Wellcome Open Research
|December 16, 2016
PubMed
Summary

Quantitative cross-linking/mass spectrometry (QCLMS) reveals protein structural dynamics by analyzing cross-link yields. This method distinguishes minor from major conformational changes, crucial for understanding protein interactions.

Keywords:
automated data processconformational changecross-linking/mass spectrometryisotope labeled cross-linkersquantitative protein structure

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Proteomics

Background:

  • Quantitative cross-linking/mass spectrometry (QCLMS) is a technique used to study protein structural dynamics in solution.
  • Previous applications include understanding proteasome lid maturation and complement C3(H2O) structure.

Purpose of the Study:

  • To benchmark the QCLMS workflow using the well-characterized human complement protein C3 and its activated form, C3b.
  • To establish a framework for semi-automated data processing to enhance QCLMS utility.

Main Methods:

  • Benchmarking the QCLMS workflow with human complement C3 and C3b.
  • Utilizing replica analysis and a label-swapping procedure for robust data analysis.
  • Developing a workflow and code of practice for semi-automated data processing.

Main Results:

  • Local conformational changes impact cross-linking yields of spatially proximate residues.
  • Major conformational changes affect the overall detectability of cross-links.
  • The study provides a robust method for distinguishing between minor and major protein conformational changes.

Conclusions:

  • QCLMS is a valuable tool for probing protein structural dynamics and conformational changes in solution.
  • The developed workflow and data processing framework facilitate QCLMS application.
  • This approach lays the foundation for monitoring domain movements in protein-protein interaction networks.