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Combining Chemical Cross-linking and Mass Spectrometry of Intact Protein Complexes to Study the Architecture of Multi-subunit Protein Assemblies
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Protein structure dynamics by crosslinking mass spectrometry.

Zhuo Angel Chen1, Juri Rappsilber2

  • 1Technische Universität Berlin, Chair of Bioanalytics, 10623 Berlin, Germany.

Current Opinion in Structural Biology
|April 27, 2023
PubMed
Summary

Crosslinking mass spectrometry (MS) maps protein structures. New methods enhance this technique to reveal specific protein conformations and dynamics, paving the way for advanced protein modeling.

Keywords:
Crosslinking mass spectrometryPhotoactivatable crosslinkingProtein conformational dynamicsProtein structure modelling and predictionQuantitative analysis

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Area of Science:

  • Biochemistry and Structural Biology
  • Proteomics
  • Computational Biology

Background:

  • Crosslinking mass spectrometry (MS) provides spatial proximity data for proteins in solution.
  • Interpreting crosslinks to identify specific protein conformations remains challenging due to data superposition.
  • Existing methods struggle to resolve conformational heterogeneity in dynamic protein systems.

Purpose of the Study:

  • To improve the ability of crosslinking MS to identify conformation-specific crosslinks.
  • To enhance the resolution and scale of studying protein dynamics using crosslinking data.
  • To integrate crosslinking MS with deep learning for advanced protein modeling.

Main Methods:

  • Utilizing photo-crosslinking to reduce crosslink superposition.
  • Integrating protein structure models with crosslinking data.
  • Employing quantitative crosslinking strategies.
  • Exploring advances like photoactivatable and in-situ crosslinking.

Main Results:

  • Developed strategies to differentiate conformation-specific crosslinks from superimposed data.
  • Demonstrated the utility of crosslinking MS in analyzing dynamic protein systems.
  • Showcased the potential of combining crosslinking data with computational modeling.

Conclusions:

  • Advances in crosslinking MS, including photoactivatable and in-situ techniques, are crucial for studying protein dynamics.
  • Integrating crosslinking data with deep learning-based modeling promises a breakthrough in understanding protein conformation dynamics.
  • Future applications may enable pseudo-atomic resolution and time-resolved studies of protein dynamics within the cellular context.