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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
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Analyzing Large Protein Complexes by Structural Mass Spectrometry
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Modeling Protein Complexes Using Restraints from Crosslinking Mass Spectrometry.

Joshua Matthew Allen Bullock1, Neeladri Sen2, Konstantinos Thalassinos3

  • 1Institute of Structural and Molecular Biology, Birkbeck College, University of London, Malet Street, London WC1E 7HX, UK.

Structure (London, England : 1993)
|May 29, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces cMNXL, a new scoring function for macromolecular modeling using crosslinking mass spectrometry (XL-MS). It improves accuracy by considering residue distance, crosslinker bounds, and solvent accessibility, outperforming traditional methods.

Keywords:
3D electron microscopycrosslinkingcrosslinking mass spectrometrycryo-EMintegrative modelingprotein structure modellingscoring function

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Area of Science:

  • Structural biology
  • Biochemistry
  • Computational biology

Background:

  • Macromolecular modeling often relies on crosslinking mass spectrometry (XL-MS) data.
  • Existing methods primarily focus on distance violations, potentially missing crucial information within XL-MS data.

Purpose of the Study:

  • To develop and evaluate a novel scoring function, cMNXL, that incorporates multiple features from XL-MS data for improved macromolecular modeling.
  • To compare the performance of Euclidean distance versus solvent-accessible surface distance in modeling.
  • To assess the benefits of integrating XL-MS data with 3D electron microscopy (3DEM) maps for integrative modeling.

Main Methods:

  • Implementation of a scoring function (cMNXL) considering expected residue distance, crosslinker bound violation, and solvent accessibility.
  • Comparison of Euclidean distance and solvent-accessible surface distance calculations for crosslinked residues.
  • Development of a combined score integrating XL-MS and low-resolution cryo-electron microscopy (cryo-EM) data.

Main Results:

  • The cMNXL scoring function demonstrated superior performance compared to methods relying solely on crosslink distance violation.
  • No significant performance difference was observed between Euclidean distance and solvent-accessible surface distance.
  • Integrative modeling combining XL-MS and 3DEM data yielded improved results over using either data type alone.

Conclusions:

  • The developed cMNXL scoring function enhances macromolecular modeling accuracy by leveraging multiple XL-MS data features.
  • Integrating XL-MS with low-resolution cryo-EM data offers a powerful approach for more precise structural determination of macromolecular assemblies.