Bioinformatics Advance Access originally published online on October 27, 2004
Bioinformatics 2005 21(7):993-1001; doi:10.1093/bioinformatics/bti086
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Published by Oxford University Press 2004.
Statistical analysis of domains in interacting protein pairs
1Medical Research Council Biostatistics Unit Cambridge, UK
2Dipartimento di Informatica e Sistemistica, Università di Pavia Italy
3Medical Research Council Laboratory of Molecular Biology Cambridge, UK
*To whom correspondence should be addressed.
Motivation: Several methods have recently been developed to analyse large-scale sets of physical interactions between proteins in terms of physical contacts between the constituent domains, often with a view to predicting new pairwise interactions. Our aim is to combine genomic interaction data, in which domain–domain contacts are not explicitly reported, with the domain-level structure of individual proteins, in order to learn about the structure of interacting protein pairs. Our approach is driven by the need to assess the evidence for physical contacts between domains in a statistically rigorous way.
Results: We develop a statistical approach that assigns p-values to pairs of domain superfamilies, measuring the strength of evidence within a set of protein interactions that domains from these superfamilies form contacts. A set of p-values is calculated for SCOP superfamily pairs, based on a pooled data set of interactions from yeast. These p-values can be used to predict which domains come into contact in an interacting protein pair. This predictive scheme is tested against protein complexes in the Protein Quaternary Structure (PQS) database, and is used to predict domain–domain contacts within 705 interacting protein pairs taken from our pooled data set.
Contact: thomas.nye{at}mrc-bsu.cam.ac.uk
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