Dataset Information

Dominant-negative proteins in herpesviruses - from assigning gene function to intracellular immunization.

ABSTRACT: Investigating and assigning gene functions of herpesviruses is a process, which profits from consistent technical innovation. Cloning of bacterial artificial chromosomes encoding herpesvirus genomes permits nearly unlimited possibilities in the construction of genetically modified viruses. Targeted or randomized screening approaches allow rapid identification of essential viral proteins. Nevertheless, mapping of essential genes reveals only limited insight into function. The usage of dominant-negative (DN) proteins has been the tool of choice to dissect functions of proteins during the viral life cycle. DN proteins also facilitate the analysis of host-virus interactions. Finally, DNs serve as starting-point for design of new antiviral strategies.

SUBMITTER: Muhlbach H

PROVIDER: S-EPMC3185506 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Dominant-negative proteins in herpesviruses - from assigning gene function to intracellular immunization.

Mühlbach Hermine H Mohr Christian A CA Ruzsics Zsolt Z Koszinowski Ulrich H UH

Viruses 20091019 3

Investigating and assigning gene functions of herpesviruses is a process, which profits from consistent technical innovation. Cloning of bacterial artificial chromosomes encoding herpesvirus genomes permits nearly unlimited possibilities in the construction of genetically modified viruses. Targeted or randomized screening approaches allow rapid identification of essential viral proteins. Nevertheless, mapping of essential genes reveals only limited insight into function. The usage of dominant-ne ...[more]

PMID: 21994555

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Project description:BackgroundProtein function prediction remains a key challenge. Domain composition affects protein function. Here we present DomFun, a Ruby gem that uses associations between protein domains and functions, calculated using multiple indices based on tripartite network analysis. These domain-function associations are combined at the protein level, to generate protein-function predictions.ResultsWe analysed 16 tripartite networks connecting homologous superfamily and FunFam domains from CATH-Gene3D with functional annotations from the three Gene Ontology (GO) sub-ontologies, KEGG, and Reactome. We validated the results using the CAFA 3 benchmark platform for GO annotation, finding that out of the multiple association metrics and domain datasets tested, Simpson index for FunFam domain-function associations combined with Stouffer's method leads to the best performance in almost all scenarios. We also found that using FunFams led to better performance than superfamilies, and better results were found for GO molecular function compared to GO biological process terms. DomFun performed as well as the highest-performing method in certain CAFA 3 evaluation procedures in terms of [Formula: see text] and [Formula: see text] We also implemented our own benchmark procedure, Pathway Prediction Performance (PPP), which can be used to validate function prediction for additional annotations sources, such as KEGG and Reactome. Using PPP, we found similar results to those found with CAFA 3 for GO, moreover we found good performance for the other annotation sources. As with CAFA 3, Simpson index with Stouffer's method led to the top performance in almost all scenarios.ConclusionsDomFun shows competitive performance with other methods evaluated in CAFA 3 when predicting proteins function with GO, although results vary depending on the evaluation procedure. Through our own benchmark procedure, PPP, we have shown it can also make accurate predictions for KEGG and Reactome. It performs best when using FunFams, combining Simpson index derived domain-function associations using Stouffer's method. The tool has been implemented so that it can be easily adapted to incorporate other protein features, such as domain data from other sources, amino acid k-mers and motifs. The DomFun Ruby gem is available from https://rubygems.org/gems/DomFun . Code maintained at https://github.com/ElenaRojano/DomFun . Validation procedure scripts can be found at https://github.com/ElenaRojano/DomFun_project .

Dataset Information

Dominant-negative proteins in herpesviruses - from assigning gene function to intracellular immunization.

Publications

Dominant-negative proteins in herpesviruses - from assigning gene function to intracellular immunization.

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