Abstract
BackgroundThe existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI) network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs.ResultsFor each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks.ConclusionConsiderable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree correlations, biological PPI networks do not actually seem to make use of this possibility.
Highlights
The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI) network of Ito et al More recent studies observed no such negative correlations for high-confidence interaction sets
Our results suggest that the mostly uncorrelated network structure of PPI networks might be a consequence of different selective disadvantages of both negatively and positively correlated networks
Protein-Protein interaction networks For this article, the following protein-protein interaction networks were analyzed: (i) networks from yeast twohybrid (Y2H) experiments, (ii) networks extracted from the Database of Interacting Proteins (DIP) [22] and (iii) the yeast high-confidence interaction set compiled by Batada et al [20]
Summary
The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI) network of Ito et al More recent studies observed no such negative correlations for high-confidence interaction sets. All biological processes of a cell such as proliferation, signal transduction or apoptosis are shaped by proteins interacting with each other and building more or less transient complexes. To understand these processes, determining the underlying protein interactions is of vital importance. The advent of high-throughput methods such as yeast two-hybrid (Y2H) has made it possible to determine protein interactions on a large scale. Protein-protein interaction networks belong to the class of so-called scale-free networks [8] This means that the number of interactions of a protein, i.e. its degree, follows approximately a power-law distribution with many proteins forming only very few interactions and a few promiscuous proteins (hubs) forming many. A correlation between the lethality of a protein knockout and the corresponding protein degree has been shown [8]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
