Cheetah-MS

Cheetah-MS integrates tandem cross-linking mass spectrometry (MS/MS or MS2) data with computational protein–protein docking to identify and model protein–protein interactions within complex, unfractionated mixtures.


Key Features:

  • Data input: Processes tandem cross-linking mass spectrometry (MS/MS or MS2) data from complex or unfractionated samples.
  • Cross-linking integration: Integrates chemical cross-linking information with MS/MS spectral evidence.
  • Docking: Applies computational protein–protein docking techniques to generate interaction models.
  • Mixture analysis: Analyzes intricate sample mixtures to predict protein–protein interactions with enhanced sensitivity and resolution.
  • Structural modeling: Produces detailed models of the quaternary structure of protein complexes.
  • Interaction interpretation: Combines cross-linking, MS, and docking data to aid interpretation of complex interaction datasets.

Scientific Applications:

  • Structural biology: Modeling quaternary structures of protein complexes using cross-linking and MS-derived evidence.
  • Molecular biology: Identifying and characterizing protein–protein interactions in complex biological samples.
  • Systems biology: Mapping interaction networks from unfractionated or heterogeneous mixtures to inform systems-level studies.

Methodology:

Integrates chemical cross-linking with tandem mass spectrometry (MS/MS or MS2) data processing and computational protein–protein docking to predict PPIs and generate quaternary structure models.

Topics

Details

Cost:
Free of charge
Tool Type:
api
Operating Systems:
Mac, Linux, Windows
Added:
10/27/2021
Last Updated:
11/24/2024

Operations

Publications

Khakzad H, Happonen L, Malmström J, Malmström L. Cheetah-MS: a web server to model protein complexes using tandem cross-linking mass spectrometry data. Bioinformatics. 2021;37(24):4871-4872. doi:10.1093/bioinformatics/btab449. PMID:34128979. PMCID:PMC8665757.

PMID: 34128979
PMCID: PMC8665757
Funding: - Foundation of Knut and Alice Wallenberg: 2016.0023, 2019.0353 - Vetenskapsrådet: 2020-02419 - Swiss National Science Foundation: P2ZHP3_191289