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Detecting remotely related proteins by their interactions and sequence similarity
Jordi Espadaler1, Ramón Aragüés, Narayanan Eswar
1Laboratori de Bioinformàtica Estructural, Grup de Recerca en Informàtica Biomèdica-Institut Municipal d'Investigació Médica (GRIB-IMIM), Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain.
Summary
This study introduces a novel method combining protein sequence similarity and interaction data to discover remote protein relationships. This approach enhances the accuracy of identifying protein folds and functional families, aiding large-scale automated protein discovery.
Area of Science:
- * Bioinformatics
- * Computational Biology
- * Structural Biology
Background:
- * Protein function is typically inferred from homology or interactions with known proteins.
- * Identifying remote relationships between protein sequences remains a challenge in bioinformatics.
- * Existing methods like BLAST have limitations in specificity and sensitivity for distant homologs.
Purpose of the Study:
- * To develop and validate a novel computational approach for identifying remote protein sequence relationships.
- * To leverage both sequence similarity and protein-protein interaction networks for enhanced protein function prediction.
- * To improve the accuracy of assigning protein folds and functional families.
Main Methods:
- * Integration of sequence similarity searches with protein-protein interaction network analysis.
- * Utilizing the principle that homologous proteins often share similar interaction partners.
- * Benchmarking the approach using proteins with known structures (SCOP) and interactions (DIP).
Main Results:
- * The proposed method significantly increased the specificity of fold assignment from 54% (BLAST) to 75%.
- * Specificity of functional family assignment improved from 70% to 87% at an e-value threshold of 10(-8).
- * Achieved a slight increase in sensitivity for fold and family assignments.
Conclusions:
- * The combined approach of sequence similarity and interaction data effectively identifies remote protein relationships.
- * This method offers a valuable tool for large-scale, automated discovery of distant protein homologs.
- * Enhanced accuracy in fold and family assignment facilitates a deeper understanding of protein function and evolution.