Inferring homologous protein-protein interactions through pair position specific scoring matrix

• Published in: BMC Bioinformatics
• Main Authors: Lin Chun-Yu, Chen Yung-Chiang, Lo Yu-Shu, Yang Jinn-Moon
• Format: Article
• Language: English
• Published: BMC 2013-01-01

<p>Abstract</p> <p>Background</p> <p>The protein-protein interaction (PPI) is one of the most important features to understand biological processes. For a PPI, the physical domain-domain interaction (DDI) plays the key role for biology functions. In the post-genomic era, to rapidly identify homologous PPIs for analyzing the contact residue pairs of their interfaces within DDIs on a genomic scale is essential to determine PPI networks and the PPI interface evolution across multiple species.</p> <p>Results</p> <p>In this study, we proposed "pair Position Specific Scoring Matrix (<it>pair</it>PSSM)" to identify homologous PPIs. The <it>pair</it>PSSM can successfully distinguish the true protein complexes from unreasonable protein pairs with about 90% accuracy. For the test set including 1,122 representative heterodimers and 2,708,746 non-interacting protein pairs, the mean average precision and mean false positive rate of <it>pair</it>PSSM were 0.42 and 0.31, respectively. Moreover, we applied <it>pair</it>PSSM to identify ~450,000 homologous PPIs with their interacting domains and residues in seven common organisms (e.g. <it>Homo sapiens</it>, <it>Mus musculus</it>, <it>Saccharomyces cerevisiae </it>and <it>Escherichia coli</it>).</p> <p>Conclusions</p> <p>Our <it>pair</it>PSSM is able to provide statistical significance of residue pairs using evolutionary profiles and a scoring system for inferring homologous PPIs. According to our best knowledge, the <it>pair</it>PSSM is the first method for searching homologous PPIs across multiple species using pair position specific scoring matrix and a 3D dimer as the template to map interacting domain pairs of these PPIs. We believe that <it>pair</it>PSSM is able to provide valuable insights for the PPI evolution and networks across multiple species.</p>