ArticleBMC bioinformatics2008
Prediction of enzyme function by combining sequence similarity and protein interactions.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Characterization of a GDS(L)-like hydrolase from Pleurotus sapidus with an unusual SGNH motif.AMB Express · 2024Article
- Salvaging high-quality genomes of microbial species from a meromictic lake using a hybrid sequencing approach.Communications biology · 2021Article
- Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism.BMC genomics · 2015Article
- Bioinformatics and Moonlighting Proteins.Frontiers in bioengineering and biotechnology · 2015Article
- Computational Approaches for Automated Classification of Enzyme Sequences.Journal of proteomics & bioinformatics · 2011Article
- DockAnalyse: an application for the analysis of protein-protein interactions.BMC structural biology · 2010Article
- Enrichment of homologs in insignificant BLAST hits by co-complex network alignment.BMC bioinformatics · 2010Article
- Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: I. Method development.Journal of computer-aided molecular design · 2009Article
- Bioinformatics annotation of the hypothetical proteins found by omics techniques can help to disclose additional virulence factors.Current microbiology · 2009Review
- ModLink+: improving fold recognition by using protein-protein interactions.Bioinformatics (Oxford, England) · 2009Article
- EFICAz2: enzyme function inference by a combined approach enhanced by machine learning.BMC bioinformatics · 2009Article
- Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources.BMC genomics · 2008Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundA number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners.
resultsThe method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST.
conclusionOur method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.
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