title: Evolutionary and physiological importance of hub proteins.
abstract: It has been claimed that proteins with more interaction partners (hubs) are both physiologically more important (i.e., less dispensable) and, owing to an assumed high density of binding sites, slow evolving. Not all analyses, however, support these results, probably because of biased and less-than reliable global protein interaction data. Here we provide the first examination of these issues using a comprehensive literature-curated dataset of well-substantiated protein interactions in Saccharomyces cerevisiae. Whereas use of less reliable yeast two-hybrid data alone can reject the possibility that local connectivity correlates with measures of dispensability, in higher quality datasets a relatively robust correlation is observed. In contrast, local connectivity does not correlate with the rate of protein evolution even in reliable datasets. This perhaps surprising lack of correlation with evolutionary rate appears in part to arise from the fact that hub proteins do not have a higher density of residues associated with binding. However, hub proteins do have at least one other set of unusual features, namely rapid turnover and regulation, as manifest in high mRNA decay rates and a large number of phosphorylation sites. This, we suggest, is an adaptation to minimize unwanted activation of pathways that might be mediated by adventitious binding to hubs, were they to actively persist longer than required at any given time point. We conclude that hub proteins are more important for cellular growth rate and under tight regulation but are not slow evolving.
authors.affiliation: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada. nizar.batada@gmail.com
authors.forename: Nizar N
authors.initials: NN
authors.lastname: Batada
authors.forename: Laurence D
authors.initials: LD
authors.lastname: Hurst
authors.forename: Mike
authors.initials: M
authors.lastname: Tyers
mesh_terms: D005075:Biological Evolution; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D019143:Evolution, Molecular; D005786:Gene Expression Regulation; D015233:Models, Statistical; D025941:Protein Interaction Mapping / Q000379:methods; D012333:RNA, Messenger / Q000378:metabolism; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry
chemical_list: D012333:RNA, Messenger; D029701:Saccharomyces cerevisiae Proteins