An integrated mass spectrometric and computational framework for the analysis of protein interaction networks

Nat Biotechnol. 2007 Mar;25(3):345-52. doi: 10.1038/nbt1289. Epub 2007 Feb 25.


Biological systems are controlled by protein complexes that associate into dynamic protein interaction networks. We describe a strategy that analyzes protein complexes through the integration of label-free, quantitative mass spectrometry and computational analysis. By evaluating peptide intensity profiles throughout the sequential dilution of samples, the MasterMap system identifies specific interaction partners, detects changes in the composition of protein complexes and reveals variations in the phosphorylation states of components of protein complexes. We use the complexes containing the human forkhead transcription factor FoxO3A to demonstrate the validity and performance of this technology. Our analysis identifies previously known and unknown interactions of FoxO3A with 14-3-3 proteins, in addition to identifying FoxO3A phosphorylation sites and detecting reduced 14-3-3 binding following inhibition of phosphoinositide-3 kinase. By improving specificity and sensitivity of interaction networks, assessing post-translational modifications and providing dynamic interaction profiles, the MasterMap system addresses several limitations of current approaches for protein complexes.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • 14-3-3 Proteins / metabolism*
  • Algorithms
  • Chromatography, Liquid / methods
  • Forkhead Box Protein O3
  • Forkhead Transcription Factors / metabolism*
  • Internet
  • Mass Spectrometry / methods
  • Phosphorylation
  • Protein Interaction Mapping / methods*
  • Protein Processing, Post-Translational
  • Proteome / chemistry*
  • Proteomics / methods*
  • Sensitivity and Specificity


  • 14-3-3 Proteins
  • FOXO3 protein, human
  • Forkhead Box Protein O3
  • Forkhead Transcription Factors
  • Proteome