Lethality and entropy of protein interaction networks.
We characterize protein interaction networks in terms of network entropy. This approach suggests a ranking principle, which strongly correlates with elements of functional importance, such as lethal proteins. Our combined analysis of protein interaction networks and functional profiles in single cellular yeast and multi-cellular worm shows that proteins with large contribution to network entropy are preferentially lethal. While entropy is inherently a dynamical concept, the present analysis incorporates only structural information. Our result therefore highlights the importance of topological features, which appear as correlates of an underlying dynamical property, and which in turn determine functional traits. We argue that network entropy is a natural extension of previously studied observables, such as pathway multiplicity and centrality. It is also applicable to networks in which the processes can be quantified and therefore serves as a link to study questions of structural and dynamical robustness in a unified way.
Manke
Thomas
T
Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. manke@molgen.mpg.de
Demetrius
Lloyd
L
Vingron
Martin
M
D000818:Animals; D017173:Caenorhabditis elegans / Q000737:chemistry; D029742:Caenorhabditis elegans Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology; D019277:Entropy; D017353:Gene Deletion; D011336:Probability; D011506:Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism*; D034622:RNA Interference; D012441:Saccharomyces cerevisiae / Q000737:chemistry; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D020798:Two-Hybrid System Techniques
D029742:Caenorhabditis elegans Proteins; D011506:Proteins; D029701:Saccharomyces cerevisiae Proteins