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Inferring homologous protein-protein interactions through pair position specific scoring matrix.
Lin, Chun-Yu; Chen, Yung-Chiang; Lo, Yu-Shu; Yang, Jinn-Moon.
Afiliação
  • Lin CY; Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
BMC Bioinformatics ; 14 Suppl 2: S11, 2013.
Article em En | MEDLINE | ID: mdl-23367879
ABSTRACT

BACKGROUND:

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.

RESULTS:

In this study, we proposed "pair Position Specific Scoring Matrix (pairPSSM)" to identify homologous PPIs. The pairPSSM 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 pairPSSM were 0.42 and 0.31, respectively. Moreover, we applied pairPSSM to identify ~450,000 homologous PPIs with their interacting domains and residues in seven common organisms (e.g. Homo sapiens, Mus musculus, Saccharomyces cerevisiae and Escherichia coli).

CONCLUSIONS:

Our pairPSSM 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 pairPSSM 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 pairPSSM is able to provide valuable insights for the PPI evolution and networks across multiple species.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Mapeamento de Interação de Proteínas / Matrizes de Pontuação de Posição Específica Tipo de estudo: Prognostic_studies Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2013 Tipo de documento: Article País de afiliação: Taiwan

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Mapeamento de Interação de Proteínas / Matrizes de Pontuação de Posição Específica Tipo de estudo: Prognostic_studies Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2013 Tipo de documento: Article País de afiliação: Taiwan