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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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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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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0019240</identifier><identifier>PMID: 21559328</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>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</subject><ispartof>PloS one, 2011-05, Vol.6 (5), p.e19240</ispartof><rights>COPYRIGHT 2011 Public Library of Science</rights><rights>2011 Korcsmáros et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Korcsmáros et al. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c789t-b492be466cf902a1744971e38aeb3c10e3a87b9ea6eaafc102eb534200702c7d3</citedby><cites>FETCH-LOGICAL-c789t-b492be466cf902a1744971e38aeb3c10e3a87b9ea6eaafc102eb534200702c7d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3086880/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3086880/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79569,79570</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21559328$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Korcsmáros, Tamás</creatorcontrib><creatorcontrib>Szalay, Máté S</creatorcontrib><creatorcontrib>Rovó, Petra</creatorcontrib><creatorcontrib>Palotai, Robin</creatorcontrib><creatorcontrib>Fazekas, Dávid</creatorcontrib><creatorcontrib>Lenti, Katalin</creatorcontrib><creatorcontrib>Farkas, Illés J</creatorcontrib><creatorcontrib>Csermely, Péter</creatorcontrib><creatorcontrib>Vellai, Tibor</creatorcontrib><title>Signalogs: orthology-based identification of novel signaling pathway components in three metazoans</title><title>PloS one</title><addtitle>PLoS One</addtitle><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.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Animal species</subject><subject>Animals</subject><subject>Annotations</subject><subject>Bioinformatics</subject><subject>Biological effects</subject><subject>Biological research</subject><subject>Biology</subject><subject>Caenorhabditis elegans</subject><subject>Cancer</subject><subject>Cellular signal transduction</subject><subject>Computational Biology - methods</subject><subject>Computer programs</subject><subject>Data integration</subject><subject>Databases, Genetic</subject><subject>Drosophila melanogaster</subject><subject>Drug approval</subject><subject>Drugs</subject><subject>Gene Expression Regulation</subject><subject>Genes</subject><subject>Genetics</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Humans</subject><subject>Identification</subject><subject>Kinases</subject><subject>Medicine</subject><subject>Nematodes</subject><subject>Notch protein</subject><subject>Organisms</subject><subject>Orthology</subject><subject>Pharmacology</subject><subject>Phenotype</subject><subject>Predictions</subject><subject>Proteins</subject><subject>Receptors, Notch - 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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.</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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source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry |
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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