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Bioinformatics Advance Access published online on June 30, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti564
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received April 23, 2005
Revised June 23, 2005
Accepted June 28, 2005

Article

The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships

Tetsuya Sato 1*, Yoshihiro Yamanishi 2, Minoru Kanehisa 1, and Hiroyuki Toh 3

1 Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan
2 Centre de Géostatistique, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77305 Fontainebleau cedex, France
3 Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan

* To whom correspondence should be addressed.
Tetsuya Sato, E-mail: sato{at}kuicr.kyoto-u.ac.jp


  Abstract

Motivation: The prediction of protein-protein interactions is currently an important issue of bioinformatics. The mirror tree method uses evolutionary information to predict protein-protein interactions. However, it has been recognized that predictions by the mirror tree method lead to many false positives. The incentive of our study was to solve this problem by improving the method of extracting the co-evolutionary information about the protein pairs.

Results: We developed a novel method to predict protein-protein interactions from co-evolutionary information in the framework of the mirror tree method. The originality is the use of the projection operator to exclude the information about the phylogenetic relationships among the source organisms from the distance matrix. Each distance matrix was transformed into a vector for the operation. The vector is referred to as a ‘phylogenetic vector’. We have proposed three ways to extract the phylogenetic information: (1) using the 16S rRNA from the same source organisms as the proteins under consideration, (2) averaging the phylogenetic vectors, and (3) analyzing the principal components of the phylogenetic vectors. We examined the performance of the proposed methods to predict interacting protein pairs from Escherichia coli, using experimentally verified data. Our method was successful, and drastically reduced the number of false positives in the prediction.

Availability: The R script for the prediction of protein-protein interactions reported in this manuscript is available at http://timpani.genome.ad.jp/~proj/.

Supplementary information: The information is also available at the same site as the R script.


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