Detecting remotely related proteins by their interactions and sequence similarity

Jordi Espadaler, Narayanan Eswar, Francesc X. Avilés, Andrej Sali, Ramón Aragüés, Baldomero Oliva, Marc A. Marti-Renom, Enrique Querol

Producció científica: Contribució a revistaArticleRecercaAvaluat per experts

24 Cites (Scopus)

Resum

The function of an uncharacterized protein is usually inferred either from its homology to, or its interactions with, characterized proteins. Here, we use both sequence similarity and protein interactions to identify relationships between remotely related protein sequences. We rely on the fact that homologous sequences share similar interactions, and, therefore, the set of interacting partners of the partners of a given protein is enriched by its homologs. The approach was benchmarked by assigning the fold and functional family to test sequences of known structure. Specifically, we relied on 1,434 proteins with known folds, as defined in the Structural Classification of Proteins (SCOP) database, and with known interacting partners, as defined in the Database of Interacting Proteins (DIP). For this subset, the specificity of fold assignment was increased from 54% for position-specific iterative BLAST to 75% for our approach, with a concomitant increase in sensitivity for a few percentage points. Similarly, the specificity of family assignment at the e-value threshold of 10-8 was increased from 70% to 87%. The proposed method would be a useful tool for large-scale automated discovery of remote relationships between protein sequences, given its unique reliance on sequence similarity and protein-protein interactions. © 2005 by The National Academy of Sciences of the USA.
Idioma originalAnglès
Pàgines (de-a)7151-7156
RevistaProceedings of the National Academy of Sciences of the United States of America
Volum102
DOIs
Estat de la publicacióPublicada - 17 de maig 2005

Fingerprint

Navegar pels temes de recerca de 'Detecting remotely related proteins by their interactions and sequence similarity'. Junts formen un fingerprint únic.

Com citar-ho