Characterization and prediction of protein-protein interactions within and between complexes

Einat Sprinzak, Yael Altuvia, Hanah Margalit*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

65 Scopus citations


Databases of experimentally determined protein interactions provide information on binary interactions and on involvement in multiprotein complexes. These data are valuable for understanding the general properties of the interaction between proteins as well as for the development of prediction schemes for unknown interactions. Here we analyze experimentally determined protein interactions by measuring various sequence, genomic, transcriptomic, and proteomic attributes of each interacting pair in the yeast Saccharomyces cerevisiae. We find that dividing the data into two groups, one that includes binary interactions within protein complexes (stable) and another that includes binary interactions that are not within complexes (transient), enables better characterization of the interactions by the different attributes and improves the prediction of new interactions. This analysis revealed that most attributes were more indicative in the set of intracomplex interactions. Using this data set for training, we integrated the different attributes by logistic regression and developed a predictive scheme that distinguishes between interacting and noninteracting protein pairs. Analysis of the logistic-regression model showed that one of the strongest contributors to the discrimination between interacting and noninteracting pairs is the presence of distinct pairs of domain signatures that were suggested previously to characterize interacting proteins. The predictive algorithm succeeds in identifying both intracomplex and other interactions (possibly the more stable ones), and its correct identification rate is 2-fold higher than that of large-scale yeast two-hybrid experiments.

Original languageAmerican English
Pages (from-to)14718-14723
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number40
StatePublished - 3 Oct 2006


  • Domain signature
  • Genomewide analysis
  • Logistic regression
  • Stable interaction
  • Transient interaction


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