Abstract
BackgroundThe rapid growth of protein-protein interaction (PPI) data has led to the emergence of PPI network analysis. Despite advances in high-throughput techniques, the interactomes of several model organisms are still far from complete. Therefore, it is desirable to expand these interactomes with ortholog-based and other methods.ResultsOrthologous pairs of 18 eukaryotic species were expanded and merged with experimental PPI datasets. The contributions of interologs from each species were evaluated. The expanded orthologous pairs enable the inference of interologs for various species. For example, more than 32,000 human interactions can be predicted. The same dataset has also been applied to the prediction of host-pathogen interactions. PPIs between P. falciparum calmodulin and several H. sapiens proteins are predicted, and these interactions may contribute to the maintenance of host cell Ca2+ concentration. Using comparisons with Bayesian and structure-based approaches, interactions between putative HSP40 homologs of P. falciparum and the H. sapiens TNF receptor associated factor family are revealed, suggesting a role for these interactions in the interference of the human immune response to P. falciparum.ConclusionThe PPI datasets are available from POINT and POINeT . Further development of methods to predict host-pathogen interactions should incorporate multiple approaches in order to improve sensitivity, and should facilitate the identification of targets for drug discovery and design.
Highlights
The rapid growth of protein-protein interaction (PPI) data has led to the emergence of PPI network analysis
Orthologs shared by H. sapiens and other model organisms The complete ortholog matrix from 18 eukaryotic species is shown in Additional File 1: Table S1
Interologs were determined from the model organisms M. musculus, R. norvegicus, D. melanogaster, C. elegans and S. cerevisiae
Summary
The rapid growth of protein-protein interaction (PPI) data has led to the emergence of PPI network analysis. Despite advances in high-throughput techniques, the interactomes of several model organisms are still far from complete. Many genome-wide high throughput yeast two-hybrid analyses have generated PPI datasets for various model organisms. Using our knowledge of conserved interactions in other organisms (or interologs) [8] to elucidate the interacting networks of a particular target protein, we have previously established a publicly accessible and functional database, POINT (the Prediction Of INTeractome database) http:// point.bioinformatics.tw/[9]. Additional highthroughput yeast two-hybrid experiments have generated an enormous number of human PPIs [13,14], which require assessments of their accuracy [15] and further evaluations using the concept of interologs. Interologs may be used to estimate the reliability of high throughput observations
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