Systematic discovery of new recognition peptides mediating protein interaction networks

Research output: Contribution to journalJournal articleResearchpeer-review

  • Victor Neduva
  • Rune Linding
  • Isabelle Su-Angrand
  • Alexander Stark
  • Federico de Masi
  • Toby J Gibson
  • Joe Lewis
  • Luis Serrano
  • Robert B Russell

Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP). Many domains are known, though comparatively few linear motifs have been discovered. Their short length (three to eight residues), and the fact that they often reside in disordered regions in proteins makes them difficult to detect through sequence comparison or experiment. Nevertheless, each new motif provides critical molecular details of how interaction networks are constructed, and can explain how one protein is able to bind to very different partners. Here we show that binding motifs can be detected using data from genome-scale interaction studies, and thus avoid the normally slow discovery process. Our approach based on motif over-representation in non-homologous sequences, rediscovers known motifs and predicts dozens of others. Direct binding experiments reveal that two predicted motifs are indeed protein-binding modules: a DxxDxxxD protein phosphatase 1 binding motif with a KD of 22 microM and a VxxxRxYS motif that binds Translin with a KD of 43 microM. We estimate that there are dozens or even hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes.

Original languageEnglish
JournalP L o S Biology (Online)
Volume3
Issue number12
Pages (from-to)e405 (2090-2099)
Number of pages10
ISSN1545-7885
DOIs
Publication statusPublished - Dec 2005
Externally publishedYes

    Research areas

  • Amino Acid Sequence, Animals, Genome, Humans, Models, Molecular, Molecular Sequence Data, Peptides, Protein Binding, Protein Structure, Tertiary, Proteins

ID: 122677841