Recovery of known T-cell epitopes by computational scanning of a viral genome
Identifieur interne : 000164 ( Istex/Corpus ); précédent : 000163; suivant : 000165Recovery of known T-cell epitopes by computational scanning of a viral genome
Auteurs : Antoine Logean ; Didier RognanSource :
- Journal of Computer-Aided Molecular Design [ 0920-654X ] ; 2002-04-01.
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Abstract
Abstract: A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.
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DOI: 10.1023/A:1020244329512
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ISTEX:B1B29583F4FFC0308F42FE0E0BD1D6B7C029B1B1Le document en format XML
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Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. 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DisplayOrder="Western"><GivenName>Didier</GivenName><FamilyName>Rognan</FamilyName></AuthorName><Contact><Email>didier.rognan@pharma.u-strasbg.fr</Email></Contact></Author><Affiliation ID="Aff1"><OrgDivision>Bioinformatic Group</OrgDivision><OrgName>Laboratoire de Pharmacochimie de la Communication Cellulaire, UMR CNRS 7081</OrgName><OrgAddress><Street>74 route du Rhin</Street><Postbox>B.P.24</Postbox><Postcode>F-67401</Postcode><City>Illkirch</City><Country>France</Country></OrgAddress></Affiliation><Affiliation ID="Aff2"><OrgDivision>Department of Applied Biosciences</OrgDivision><OrgName>Swiss Federal Institute of Technology</OrgName><OrgAddress><Street>Winterthurerstrasse 190</Street><Postcode>CH 8057</Postcode><City>Zürich</City><Country>Switzerland</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A<Superscript>*</Superscript>0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list.</Para><Para>The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.</Para></Abstract><KeywordGroup Language="En"><Keyword>antigen</Keyword><Keyword>epitope prediction</Keyword><Keyword>free energy scoring</Keyword><Keyword>homology modelling</Keyword><Keyword>major histocompatibility complex</Keyword><Keyword>threading</Keyword></KeywordGroup></ArticleHeader><NoBody></NoBody></Article></Issue></Volume></Journal></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Recovery of known T-cell epitopes by computational scanning of a viral genome</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>Recovery of known T-cell epitopes by computational scanning of a viral genome</title></titleInfo><name type="personal"><namePart type="given">Antoine</namePart><namePart type="family">Logean</namePart><affiliation>Bioinformatic Group, Laboratoire de Pharmacochimie de la Communication Cellulaire, UMR CNRS 7081, 74 route du Rhin, B.P.24, F-67401, Illkirch, France</affiliation><affiliation>Department of Applied Biosciences, Swiss Federal Institute of Technology, Winterthurerstrasse 190, CH 8057, Zürich, Switzerland</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal" displayLabel="corresp"><namePart type="given">Didier</namePart><namePart type="family">Rognan</namePart><affiliation>Bioinformatic Group, Laboratoire de Pharmacochimie de la Communication Cellulaire, UMR CNRS 7081, 74 route du Rhin, B.P.24, F-67401, Illkirch, France</affiliation><affiliation>E-mail: didier.rognan@pharma.u-strasbg.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="OriginalPaper" authority="ISTEX" authorityURI="https://content-type.data.istex.fr" valueURI="https://content-type.data.istex.fr/ark:/67375/XTP-1JC4F85T-7">research-article</genre><originInfo><publisher>Kluwer Academic Publishers</publisher><place><placeTerm type="text">Dordrecht</placeTerm></place><dateIssued encoding="w3cdtf">2002-04-01</dateIssued><copyrightDate encoding="w3cdtf">2002</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><abstract lang="en">Abstract: A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.</abstract><subject lang="en"><topic>antigen</topic><topic>epitope prediction</topic><topic>free energy scoring</topic><topic>homology modelling</topic><topic>major histocompatibility complex</topic><topic>threading</topic></subject><relatedItem type="host"><titleInfo><title>Journal of Computer-Aided Molecular Design</title></titleInfo><titleInfo type="abbreviated"><title>J Comput Aided Mol Des</title></titleInfo><genre type="journal" authority="ISTEX" authorityURI="https://publication-type.data.istex.fr" valueURI="https://publication-type.data.istex.fr/ark:/67375/JMC-0GLKJH51-B">journal</genre><originInfo><publisher>Springer</publisher><dateIssued encoding="w3cdtf">2002-04-01</dateIssued><copyrightDate encoding="w3cdtf">2002</copyrightDate></originInfo><subject><genre>Chemistry</genre><topic>Computer Applications in Chemistry</topic><topic>Physical Chemistry</topic><topic>Animal Anatomy / Morphology / Histology</topic></subject><identifier type="ISSN">0920-654X</identifier><identifier type="eISSN">1573-4951</identifier><identifier type="JournalID">10822</identifier><identifier type="IssueArticleCount">5</identifier><identifier type="VolumeIssueCount">12</identifier><part><date>2002</date><detail type="volume"><number>16</number><caption>vol.</caption></detail><detail type="issue"><number>4</number><caption>no.</caption></detail><extent unit="pages"><start>229</start><end>243</end></extent></part><recordInfo><recordOrigin>Kluwer Academic Publishers, 2002</recordOrigin></recordInfo></relatedItem><identifier type="istex">B1B29583F4FFC0308F42FE0E0BD1D6B7C029B1B1</identifier><identifier type="ark">ark:/67375/VQC-K4D7GJ9P-V</identifier><identifier type="DOI">10.1023/A:1020244329512</identifier><identifier type="ArticleID">5094325</identifier><identifier type="ArticleID">Art1</identifier><accessCondition type="use and reproduction" contentType="copyright">Kluwer Academic Publishers, 2002</accessCondition><recordInfo><recordContentSource authority="ISTEX" authorityURI="https://loaded-corpus.data.istex.fr" valueURI="https://loaded-corpus.data.istex.fr/ark:/67375/XBH-3XSW68JL-F">springer</recordContentSource><recordOrigin>Kluwer Academic Publishers, 2002</recordOrigin></recordInfo></mods><json:item><extension>json</extension><original>false</original><mimetype>application/json</mimetype><uri>https://api.istex.fr/ark:/67375/VQC-K4D7GJ9P-V/record.json</uri></json:item></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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