Bioinformatics Advance Access originally published online on June 20, 2006
Bioinformatics 2006 22(16):2012-2019; doi:10.1093/bioinformatics/btl338
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
A lock-and-key model for protein–protein interactions
1 Bioinformatics Research Centre, Department of Computing Science, University of Glasgow G12 8QQ, UK
2 Department of Mathematics, University of Strathclyde G1 1XH, UK
3 Groningen Bioinformatics Centre, University of Groningen Kerklaan 30, 9751 NN Haren, Netherlands
*To whom correspondence should be addressed.
 |
Abstract |
|---|
Motivation: Protein–protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism's proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs, and also to identify potentially missing or spurious interactions.
Results: Our new graph model explains observed interactions between proteins by an underlying interaction of complementary binding domains (lock-and-key model). This leads to a novel graph-theoretical algorithm to identify bipartite subgraphs within protein–protein interaction networks where the underlying data are taken from yeast two-hybrid experimental results. By testing on synthetic data, we demonstrate that under certain modelling assumptions, the algorithm will return correct domain information about each protein in the network. Tests on data from various model organisms show that the local and global patterns predicted by the model are indeed found in experimental data. Using functional and protein structure annotations, we show that bipartite subnetworks can be identified that correspond to biologically relevant interaction motifs. Some of these are novel and we discuss an example involving SH3 domains from the Saccharomyces cerevisiae interactome.
Availability: The algorithm (in Matlab format) is available (see http://www.maths.strath.ac.uk/~aas96106/lock_key.html)
Contact: jmorriso{at}dcs.gla.ac.uk
Supplementary information: Supplementary data are available at http://www.maths.strath.ac.uk/~aas96106/lock_key.html.
Associate Editor: Charlie Hodgman
Received on February 20, 2006; revised on April 26, 2006; accepted on June 15, 2006
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  J. Li and Q. Liu 'Double water exclusion': a hypothesis refining the O-ring theory for the hot spots at protein interfaces Bioinformatics, March 15, 2009; 25(6): 743 - 750. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. J. Higham, M. Rasajski, and N. Przulj Fitting a geometric graph to a protein-protein interaction network Bioinformatics, April 15, 2008; 24(8): 1093 - 1099. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Andreopoulos, A. An, X. Wang, M. Faloutsos, and M. Schroeder Clustering by common friends finds locally significant proteins mediating modules Bioinformatics, May 1, 2007; 23(9): 1124 - 1131. [Abstract] [Full Text] [PDF]
|
|