title: Signalogs: orthology-based identification of novel signaling pathway components in three metazoans.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Genetics, Eötvös Loránd University, Budapest, Hungary.
authors.forename: Tamás
authors.initials: T
authors.lastname: Korcsmáros
authors.forename: Máté S
authors.initials: MS
authors.lastname: Szalay
authors.forename: Petra
authors.initials: P
authors.lastname: Rovó
authors.forename: Robin
authors.initials: R
authors.lastname: Palotai
authors.forename: Dávid
authors.initials: D
authors.lastname: Fazekas
authors.forename: Katalin
authors.initials: K
authors.lastname: Lenti
authors.forename: Illés J
authors.initials: IJ
authors.lastname: Farkas
authors.forename: Péter
authors.initials: P
authors.lastname: Csermely
authors.forename: Tibor
authors.initials: T
authors.lastname: Vellai
mesh_terms: D000465:Algorithms; D000818:Animals; D017173:Caenorhabditis elegans; D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D004331:Drosophila melanogaster; D005786:Gene Expression Regulation; D005823:Genetics; D006801:Humans; D010641:Phenotype; D034622:RNA Interference; D051880:Receptors, Notch / Q000378:metabolism; D015398:Signal Transduction; D013045:Species Specificity
chemical_list: D051880:Receptors, Notch