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Related Experiment Video

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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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Kojak: efficient analysis of chemically cross-linked protein complexes.

Michael R Hoopmann1, Alex Zelter2, Richard S Johnson3

  • 1†Institute for Systems Biology, 401 Terry Avenue North, Seattle, Washington 98109, United States.

Journal of Proteome Research
|March 27, 2015
PubMed
Summary

Kojak software efficiently identifies cross-linked peptides from mass spectrometry data, improving protein-protein interaction analysis. This open-source tool offers more identifications in less time for researchers.

Keywords:
cross-linkingmass spectrometryprotein structureproteomics

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Area of Science:

  • Proteomics
  • Biochemistry
  • Computational Biology

Background:

  • Protein-protein interactions are crucial for cellular functions.
  • Analyzing these interactions often involves chemical cross-linking and mass spectrometry.
  • Identifying cross-linked peptides from complex spectra requires specialized algorithms.

Purpose of the Study:

  • To introduce Kojak, a novel software application for identifying cross-linked peptides.
  • To enable large-scale analysis of protein-protein interactions using chemical cross-linking.
  • To provide an efficient and accessible tool for cross-linking researchers.

Main Methods:

  • Kojak integrates spectral processing and scoring from traditional database search algorithms.
  • It supports various chemical cross-linkers, with or without heavy isotope labeling.
  • The algorithm was tested on novel and existing datasets and compared to existing software.

Main Results:

  • Kojak identified more cross-links compared to existing algorithms.
  • The software significantly reduced computational time for analysis.
  • It demonstrated effectiveness on both new and previously analyzed data.

Conclusions:

  • Kojak is an efficient, open-source, and cross-platform software for identifying cross-linked peptides.
  • It enhances the analysis of protein-protein interactions and protein topologies.
  • The tool provides researchers with an effective resource for increased cross-link identifications.