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We model the evolution of eukaryotic protein-protein interaction (PPI)networks. In our model, PPI networks evolve by two known biological mechanisms:(1) Gene duplication, which is followed by rapid diversification of duplicateinteractions. (2) Neofunctionalization, in which a mutation leads to a newinteraction with some other protein. Since many interactions are due to simplesurface compatibility, we hypothesize there is an increased likelihood ofinteracting with other proteins in the target protein's neighborhood. We findgood agreement of the model on 10 different network properties compared tohigh-confidence experimental PPI networks in yeast, fruit flies, and humans.Key findings are: (1) PPI networks evolve modular structures, with no need toinvoke particular selection pressures. (2) Proteins in cells have on averageabout 6 degrees of separation, similar to some social networks, such ashuman-communication and actor networks. (3) Unlike social networks, which havea shrinking diameter (degree of maximum separation) over time, PPI networks arepredicted to grow in diameter. (4) The model indicates that evolutionarily oldproteins should have higher connectivities and be more centrally embedded intheir networks. This suggests a way in which present-day proteomics data couldprovide insights into biological evolution.

Simulated evolution of protein-protein interaction networks with realistic topology