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Open Access Methodology article

Improved homology-driven computational validation of protein-protein interactions motivated by the evolutionary gene duplication and divergence hypothesis

Christian Frech1*, Michael Kommenda1, Viktoria Dorfer1, Thomas Kern1, Helmut Hintner2, Johann W Bauer2 and Kamil Önder2,3

Author Affiliations

1 Upper Austria University of Applied Sciences, Softwarepark 11, 4232 Hagenberg, Austria

2 Paracelsus Medical Private University, Department of Dermatology, Müllner Hauptstraße 48, 5020 Salzburg, Austria

3 Department of Cell Biology, University of Salzburg, Salzburg, Austria

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BMC Bioinformatics 2009, 10:21 doi:10.1186/1471-2105-10-21

Published: 19 January 2009

Abstract

Background

Protein-protein interaction (PPI) data sets generated by high-throughput experiments are contaminated by large numbers of erroneous PPIs. Therefore, computational methods for PPI validation are necessary to improve the quality of such data sets. Against the background of the theory that most extant PPIs arose as a consequence of gene duplication, the sensitive search for homologous PPIs, i.e. for PPIs descending from a common ancestral PPI, should be a successful strategy for PPI validation.

Results

To validate an experimentally observed PPI, we combine FASTA and PSI-BLAST to perform a sensitive sequence-based search for pairs of interacting homologous proteins within a large, integrated PPI database. A novel scoring scheme that incorporates both quality and quantity of all observed matches allows us (1) to consider also tentative paralogs and orthologs in this analysis and (2) to combine search results from more than one homology detection method. ROC curves illustrate the high efficacy of this approach and its improvement over other homology-based validation methods.

Conclusion

New PPIs are primarily derived from preexisting PPIs and not invented de novo. Thus, the hallmark of true PPIs is the existence of homologous PPIs. The sensitive search for homologous PPIs within a large body of known PPIs is an efficient strategy to separate biologically relevant PPIs from the many spurious PPIs reported by high-throughput experiments.