Monthly Archives: February 2006

This article caught my attention for a couple of reasons (1) It proposes a physical model for protein-protein interaction networks, and (2) It comes from Eugene Shaknovich, not someone I traditionally associate with protein-protein interactions, but more with folding and drug design. "Scale-free" toplogies have been shown to exist in a number of networks, ranging from chemical reactions in a cell to the WWW. In general many biological systems seem to exhibit scale-free topologies. Deeds, et al. take a look at the network of protein-protein interactions (PPIs), specifically the results of two Y2H studies (Uetz et al., Nature, 2000 and Ito et al., PNAS, 2001) that suggest that the interactome of protein-protein interations of S. cerevisiae constitute scale-free networks. The first thing that they observe is that there is little correlation between the two interactomes, which is not entirely suriprising given the noisy nature of Y2H experiments and the known false positive rates. This paper uses the hypothesis that Y2H experiments result in interactions that are dominated by non-specific interactions. They then proceed to propose a physical model (certainly something that interests me greatly) to explain how two uncorrelated networks might have such similar topologies. The core of the model proposed in this paper is that the surfaces get exposed randomly between experiments, exposing different sets of hydrophonic residues, which is sufficient to explain the lack of correlation. The significance of this model is that PPIs as identified by Y2H are not necessarily driven by evolutionary dynamics, but rather by non-specific interactions (a factor supported by a correlation between the hydrophobicity of a protein and the number of interacting partners). It should be noted that this paper does not suggest that there is no biologically relevant and evolutionary information in the reported interactomes. The approach in this paper is interesting from a protein modeling point of view, since it uses extrapolated homology modeling results as the basis for looking at surface hydrophobic residues. I find it interesting that the body of literature that tries to explain protein-protein interaction networks physically is relatively small. Perhaps I am biased, but the first thing that jumped out at me upon learning that the interactions between the same proteins in uncorrelated networks could not be random (due to the scale-free nature) was the question "what physical interactions are driving the interaction networks?". In this case the authors propse that a simple hydrophobicity and de-solvation model (routinely used in protein-protein docking programs) + an element of noise can explain the differences in the results. Is the model the explanation? I am not sure. Certainly it makes sense that protein-protein interactions are driven by hydrophobic interactions. It also would make logical sense that evolutionary pressure would drive proteins to interact via a specific set of residues, likely to be driven by desolvation and optimization of binding energies. The real picture is probably a little more complicated and has to balance a number of criteria. The model that the authors propose seems just a little too simple. It might just be an indictment of Y2H. If two experiments could identify highly correlated interactomes, I would not be surprised if they were driven by physical interactions, maybe evolutionarily conserved sets of surface patches that drive PPIs. Further Reading: Review at the bioinformatics blog Technorati Tags: Systems Biology, Protein Interaction Networks, Science, Review