A Combined Experimental and Computational Strategy to Define Protein Interaction Networks for Peptide Recognition Modules
University of Toronto · University of Washington · +5 more institutions
Abstract
Peptide recognition modules mediate many protein-protein interactions critical for the assembly of macromolecular complexes. Complete genome sequences have revealed thousands of these domains, requiring improved methods for identifying their physiologically relevant binding partners. We have developed a strategy combining computational prediction of interactions from phage-display ligand consensus sequences with large-scale two-hybrid physical interaction tests. Application to yeast SH3 domains generated a phage-display network containing 394 interactions among 206 proteins and a two-hybrid network containing 233 interactions among 145 proteins. Graph theoretic analysis identified 59 highly likely interactions…
Citation impact
- FWCI
- 23.00
- Percentile
- 100%
- References
- 21
Authors
16- AHAmy H.Y. TongCorresponding
University of Toronto
- BDBecky DreesCorresponding
University of Washington
- GNGiuliano NardelliCorresponding
University of Rome Tor Vergata
- GDGary D. BaderCorresponding
Mount Sinai Hospital, University of Toronto, Lunenfeld-Tanenbaum Research Institute
- BBBarbara Brannetti
University of Rome Tor Vergata
Topics & keywords
- Protein–protein interaction
- Computational biology
- Phage display
- Two-hybrid screening
- Biology
- Immunoprecipitation
- Peptide
- Interaction network