Abstract
BackgroundProtein-protein interactions are at the basis of most cellular processes and crucial for many bio-technological applications. During the last few years the development of high-throughput technologies has produced several large-scale protein-protein interaction data sets for various organisms. It is important to develop tools for dissecting their content and analyse the information they embed by data-integration and computational methods.ResultsInteractions can be mediated by the presence of specific features, such as motifs, surface patches and domains. The co-occurrence of these features on proteins interacting with the same protein can indicate mutually exclusive interactions and, therefore, can be used for inferring the involvement of the proteins in common biological processes.We present here a publicly available server that allows the user to investigate protein interaction data in light of other biological information, such as their sequences, presence of specific domains, process and component ontologies. The server can be effectively used to construct a high-confidence set of mutually exclusive interactions by identifying similar features in groups of proteins sharing a common interaction partner. As an example, we describe here the identification of common motifs, function, cellular localization and domains in different datasets of yeast interactions.ConclusionsThe server can be used to analyse user-supplied datasets, it contains pre-processed data for four yeast Protein Protein interaction datasets and the results of their statistical analysis. These show that the presence of common motifs in proteins interacting with the same partner is a valuable source of information, it can be used to investigate the properties of the interacting proteins and provides information that can be effectively integrated with other sources. As more experimental interaction data become available, this tool will become more and more useful to gain a more detailed picture of the interactome.
Highlights
Protein-protein interactions are at the basis of most cellular processes and crucial for many bio-technological applications
The server can be used to analyse user-supplied datasets, it contains pre-processed data for four yeast Protein Protein interaction datasets and the results of their statistical analysis. These show that the presence of common motifs in proteins interacting with the same partner is a valuable source of information, it can be used to investigate the properties of the interacting proteins and provides information that can be effectively integrated with other sources
An example: function prediction using motif analysis The method that we described for the analysis of protein-protein interactions (PPIs) maps can almost naturally be extended to become a tool for protein functional assignment, on the basis of the hypothesis that two proteins interacting with the same partner and sharing a common motif are likely to have some functional similarity as well
Summary
Protein-protein interactions are at the basis of most cellular processes and crucial for many bio-technological applications. In many cases proteins physically bind to each other to absolve their role, and the interaction is often mediated by the physical binding of some of their subunits, such as domains, surface patches or small regions composed of a few residues called motifs [2,3,4]. The latter is rather frequent, there have been few attempts to systematically explore the information that they provide at the genomic level. The identification of shared motifs has proven to be very useful to characterize protein interactions (e.g. the binding of the SH3 domain to the PxxP local sequence), function (DNA binding), localization (nuclear localization signal) and domain fingerprints (PROSITE [4])
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