title: Protein complex forming ability is favored over the features of interacting partners in determining the evolutionary rates of proteins in the yeast protein-protein interaction networks.
abstract: BACKGROUND
  Evolutionary rates of proteins in a protein-protein interaction network are primarily governed by the protein connectivity and/or expression level. A recent study revealed the importance of the features of the interacting protein partners, viz., the coefficient of functionality and clustering coefficient in controlling the protein evolutionary rates in a protein-protein interaction (PPI) network.
  
  
  RESULTS
  By multivariate regression analysis we found that the three parameters: probability of complex formation, expression level and degree of a protein independently guide the evolutionary rates of proteins in the PPI network. The contribution of the complex forming property of a protein and its expression level led to nearly 43% of the total variation as observed from the first principal component. We also found that for complex forming proteins in the network, those which have partners sharing the same functional class evolve faster than those having partners belonging to different functional classes. The proteins in the dense parts of the network evolve faster than their counterparts which are present in the sparse regions of the network. Taking into account the complex forming ability, we found that all the complex forming proteins considered in this study evolve slower than the non-complex forming proteins irrespective of their localization in the network or the affiliation of their partners to same/different functional classes.
  
  
  CONCLUSIONS
  We have shown here that the functionality and clustering coefficient correlated with the degree of the protein in the protein-protein interaction network. We have identified the significant relationship of the complex-forming property of proteins and their evolutionary rates even when they are classified according to the features of their interacting partners. Our study implies that the evolutionarily constrained proteins are actually members of a larger number of protein complexes and this justifies why they have enhanced expression levels.
authors.affiliation: Bioinformatics Centre, Bose Institute, P 1/12, C,I,T, Scheme VII M, Kolkata 700 054, India.
authors.forename: Sandip
authors.initials: S
authors.lastname: Chakraborty
authors.forename: Bratati
authors.initials: B
authors.lastname: Kahali
authors.forename: Tapash C
authors.initials: TC
authors.lastname: Ghosh
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D019143:Evolution, Molecular; D005656:Fungal Proteins / Q000235:genetics* / Q000378:metabolism*; D011485:Protein Binding; D012044:Regression Analysis; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism*
chemical_list: D005656:Fungal Proteins