On the origin and implications of scaling in biological networks

17 June 2005

Eric Deeds
Shakhnovich Lab
Department of Chemistry and Chemical Biology
Harvard University


It has recently been demonstrated that many biological networks exhibit a "scale-free" topology where the probability of observing a node with a certain number of edges (k) follows a power law: i.e. p(k) ~ k^{-gamma}. This observation has been explained in terms of dynamical evolutionary models of duplication and divergence broadly based on the principle of "preferential attachment". In this talk I will discuss recent work exploring alternative, non-dynamic, physical models for these networks. I will specifically consider the protein-protein interaction (PPI) network. I will demonstrate that the two published independent measurements of these interactions using the yeast-2-hybrid (Y2H) methodology produce graphs that are only weakly correlated with one another despite their strikingly similar scale-free topology. I will then discuss a physical model that can explain the observation of scale-free networks of such interactions based on the fundamental principle that (de)solvation is a major physical factor in protein-protein interactions. This simple physical model reproduces not only the scale-free nature of such graphs but also their "modular" and "hierarchical" organization as empirically observed in higher-order features of these networks. A key support for this model is provided by the discovery of significant correlation between number of interactions made by a protein (its node degree k in the network) and fraction of hydrophobic residues on its surface. These results have profound implications not only for protein-protein interaction networks but also for scale-free networks in other systems.


E Deeds and E I Shakhnovich, "The emergence of scaling in sequence-based physical models of protein evolution", Biophysical Journal 88:3905-3911 2005. Abstract

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