Disorder and sequence repeats in hub proteins and their implications for network evolution

Zsuzsanna Dosztányi, Jake Chen, A. Keith Dunker, István Simon, Peter Tompa

Research output: Contribution to journalArticle

241 Scopus citations


Protein interaction networks display approximate scale-free topology, in which hub proteins that interact with a large number of other proteins determine the overall organization of the network. In this study, we aim to determine whether hubs are distinguishable from other networked proteins by specific sequence features. Proteins of different connectednesses were compared in the interaction networks of Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, and Homo sapiens with respect to the distribution of predicted structural disorder, sequence repeats, low complexity regions, and chain length. Highly connected proteins ("hub proteins") contained significantly more of, and greater proportion of, these sequence features and tended to be longer overall as compared to less connected proteins. These sequence features provide two different functional means for realizing multiple interactions: (1) extended interaction surface and (2) flexibility and adaptability, providing a mechanism for the same region to bind distinct partners. Our view contradicts the prevailing view that scaling in protein interactomes arose from gene duplication and preferential attachment of equivalent proteins. We propose an alternative evolutionary network specialization process, in which certain components of the protein interactome improved their fitness for binding by becoming longer or accruing regions of disorder and/or internal repeats and have therefore become specialized in network organization.

Original languageEnglish (US)
Pages (from-to)2985-2995
Number of pages11
JournalJournal of Proteome Research
Issue number11
StatePublished - Nov 1 2006


  • Disordered protein
  • Hub protein
  • Interaction network
  • Protein-protein interaction
  • Unstructured protein

ASJC Scopus subject areas

  • Genetics
  • Biotechnology
  • Biochemistry

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