Signalogs: orthology-based identification of novel signaling pathway components in three metazoans

Uncovering novel components of signal transduction pathways and their interactions within species is a central task in current biological research. Orthology alignment and functional genomics approaches allow the effective identification of signaling proteins by cross-species data integration. Recen...

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Veröffentlicht in:PloS one 2011-05, Vol.6 (5), p.e19240
Hauptverfasser: Korcsmáros, Tamás, Szalay, Máté S, Rovó, Petra, Palotai, Robin, Fazekas, Dávid, Lenti, Katalin, Farkas, Illés J, Csermely, Péter, Vellai, Tibor
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container_title PloS one
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creator Korcsmáros, Tamás
Szalay, Máté S
Rovó, Petra
Palotai, Robin
Fazekas, Dávid
Lenti, Katalin
Farkas, Illés J
Csermely, Péter
Vellai, Tibor
description Uncovering novel components of signal transduction pathways and their interactions within species is a central task in current biological research. Orthology alignment and functional genomics approaches allow the effective identification of signaling proteins by cross-species data integration. Recently, functional annotation of orthologs was transferred across organisms to predict novel roles for proteins. Despite the wide use of these methods, annotation of complete signaling pathways has not yet been transferred systematically between species. Here we introduce the concept of 'signalog' to describe potential novel signaling function of a protein on the basis of the known signaling role(s) of its ortholog(s). To identify signalogs on genomic scale, we systematically transferred signaling pathway annotations among three animal species, the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and humans. Using orthology data from InParanoid and signaling pathway information from the SignaLink database, we predict 88 worm, 92 fly, and 73 human novel signaling components. Furthermore, we developed an on-line tool and an interactive orthology network viewer to allow users to predict and visualize components of orthologous pathways. We verified the novelty of the predicted signalogs by literature search and comparison to known pathway annotations. In C. elegans, 6 out of the predicted novel Notch pathway members were validated experimentally. Our approach predicts signaling roles for 19 human orthodisease proteins and 5 known drug targets, and suggests 14 novel drug target candidates. Orthology-based pathway membership prediction between species enables the identification of novel signaling pathway components that we referred to as signalogs. Signalogs can be used to build a comprehensive signaling network in a given species. Such networks may increase the biomedical utilization of C. elegans and D. melanogaster. In humans, signalogs may identify novel drug targets and new signaling mechanisms for approved drugs.
doi_str_mv 10.1371/journal.pone.0019240
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In humans, signalogs may identify novel drug targets and new signaling mechanisms for approved drugs.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21559328</pmid><doi>10.1371/journal.pone.0019240</doi><tpages>e19240</tpages><oa>free_for_read</oa></addata></record>
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subjects Algorithms
Analysis
Animal species
Animals
Annotations
Bioinformatics
Biological effects
Biological research
Biology
Caenorhabditis elegans
Cancer
Cellular signal transduction
Computational Biology - methods
Computer programs
Data integration
Databases, Genetic
Drosophila melanogaster
Drug approval
Drugs
Gene Expression Regulation
Genes
Genetics
Genomes
Genomics
Humans
Identification
Kinases
Medicine
Nematodes
Notch protein
Organisms
Orthology
Pharmacology
Phenotype
Predictions
Proteins
Receptors, Notch - metabolism
RNA Interference
Signal Transduction
Signaling
Species
Species Specificity
Target recognition
Transcription factors
title Signalogs: orthology-based identification of novel signaling pathway components in three metazoans
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