Analysis of Secondary Structure Biases in Naturally Presented HLA-I Ligands.
Identifieur interne : 000336 ( PubMed/Curation ); précédent : 000335; suivant : 000337Analysis of Secondary Structure Biases in Naturally Presented HLA-I Ligands.
Auteurs : Marta A S. Perez [Suisse] ; Michal Bassani-Sternberg [Suisse] ; George Coukos [Suisse] ; David Gfeller [Suisse] ; Vincent Zoete [Suisse]Source :
- Frontiers in immunology [ 1664-3224 ] ; 2019.
Abstract
Recent clinical developments in antitumor immunotherapy involving T-cell related therapeutics have led to a renewed interest for human leukocyte antigen class I (HLA-I) binding peptides, given their potential use as peptide vaccines. Databases of HLA-I binding peptides hold therefore information on therapeutic targets essential for understanding immunity. In this work, we use in depth and accurate HLA-I peptidomics datasets determined by mass-spectrometry (MS) and analyze properties of the HLA-I binding peptides with structure-based computational approaches. HLA-I binding peptides are studied grouping all alleles together or in allotype-specific contexts. We capitalize on the increasing number of structurally determined proteins to (1) map the 3D structure of HLA-I binding peptides into the source proteins for analyzing their secondary structure and solvent accessibility in the protein context, and (2) search for potential differences between these properties in HLA-I binding peptides and in a reference dataset of HLA-I motif-like peptides. This is performed by an in-house developed heuristic search that considers peptides across all the human proteome and converges to a collection of peptides that exhibit exactly the same motif as the HLA-I peptides. Our results, based on 9-mers matched to protein 3D structures, clearly show enriched sampling for HLA-I presentation of helical fragments in the source proteins. This enrichment is significant, as compared to 9-mer HLA-I motif-like peptides, and is not entirely explained by the helical propensity of the preferred residues in the HLA-I motifs. We give possible hypothesis for the secondary structure biases observed in HLA-I peptides. This contribution is of potential interest for researchers working in the field of antigen presentation and proteolysis. This knowledge refines the understanding of the rules governing antigen presentation and could be added to the parameters of the current peptide-MHC class I binding predictors to increase their antigen predictive ability.
DOI: 10.3389/fimmu.2019.02731
PubMed: 31824508
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Perez</name><affiliation wicri:level="1"><nlm:affiliation>Computer-Aided Molecular Engineering, Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Computer-Aided Molecular Engineering, Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne</wicri:regionArea></affiliation></author><author><name sortKey="Bassani Sternberg, Michal" sort="Bassani Sternberg, Michal" uniqKey="Bassani Sternberg M" first="Michal" last="Bassani-Sternberg">Michal Bassani-Sternberg</name><affiliation wicri:level="1"><nlm:affiliation>Human Integrated Tumor Immunology Discovery Engine, Department of Oncology, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Human Integrated Tumor Immunology Discovery Engine, Department of Oncology, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne</wicri:regionArea></affiliation></author><author><name sortKey="Coukos, George" sort="Coukos, George" uniqKey="Coukos G" first="George" last="Coukos">George Coukos</name><affiliation wicri:level="1"><nlm:affiliation>Human Integrated Tumor Immunology Discovery Engine, Department of Oncology, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Human Integrated Tumor Immunology Discovery Engine, Department of Oncology, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne</wicri:regionArea></affiliation></author><author><name sortKey="Gfeller, David" sort="Gfeller, David" uniqKey="Gfeller D" first="David" last="Gfeller">David Gfeller</name><affiliation wicri:level="1"><nlm:affiliation>Swiss Institute of Bioinformatics, Lausanne, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Swiss Institute of Bioinformatics, Lausanne</wicri:regionArea></affiliation></author><author><name sortKey="Zoete, Vincent" sort="Zoete, Vincent" uniqKey="Zoete V" first="Vincent" last="Zoete">Vincent Zoete</name><affiliation wicri:level="1"><nlm:affiliation>Computer-Aided Molecular Engineering, Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Computer-Aided Molecular Engineering, Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne</wicri:regionArea></affiliation></author></analytic><series><title level="j">Frontiers in immunology</title><idno type="eISSN">1664-3224</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Recent clinical developments in antitumor immunotherapy involving T-cell related therapeutics have led to a renewed interest for <b>h</b>uman <b>l</b>eukocyte <b>a</b>ntigen class <b>I</b> (HLA-I) binding peptides, given their potential use as peptide vaccines. Databases of HLA-I binding peptides hold therefore information on therapeutic targets essential for understanding immunity. In this work, we use in depth and accurate HLA-I peptidomics datasets determined by mass-spectrometry (MS) and analyze properties of the HLA-I binding peptides with structure-based computational approaches. HLA-I binding peptides are studied grouping all alleles together or in allotype-specific contexts. We capitalize on the increasing number of structurally determined proteins to (1) map the 3D structure of HLA-I binding peptides into the source proteins for analyzing their secondary structure and solvent accessibility in the protein context, and (2) search for potential differences between these properties in HLA-I binding peptides and in a reference dataset of HLA-I motif-like peptides. This is performed by an <i>in-house</i> developed heuristic search that considers peptides across all the human proteome and converges to a collection of peptides that exhibit exactly the same motif as the HLA-I peptides. Our results, based on 9-mers matched to protein 3D structures, clearly show enriched sampling for HLA-I presentation of helical fragments in the source proteins. This enrichment is significant, as compared to 9-mer HLA-I motif-like peptides, and is not entirely explained by the helical propensity of the preferred residues in the HLA-I motifs. We give possible hypothesis for the secondary structure biases observed in HLA-I peptides. This contribution is of potential interest for researchers working in the field of antigen presentation and proteolysis. This knowledge refines the understanding of the rules governing antigen presentation and could be added to the parameters of the current peptide-MHC class I binding predictors to increase their antigen predictive ability.</div></front></TEI><pubmed><MedlineCitation Status="In-Data-Review" Owner="NLM"><PMID Version="1">31824508</PMID><DateRevised><Year>2019</Year><Month>12</Month><Day>18</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1664-3224</ISSN><JournalIssue CitedMedium="Internet"><Volume>10</Volume><PubDate><Year>2019</Year></PubDate></JournalIssue><Title>Frontiers in immunology</Title><ISOAbbreviation>Front Immunol</ISOAbbreviation></Journal><ArticleTitle>Analysis of Secondary Structure Biases in Naturally Presented HLA-I Ligands.</ArticleTitle><Pagination><MedlinePgn>2731</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3389/fimmu.2019.02731</ELocationID><Abstract><AbstractText>Recent clinical developments in antitumor immunotherapy involving T-cell related therapeutics have led to a renewed interest for <b>h</b>uman <b>l</b>eukocyte <b>a</b>ntigen class <b>I</b> (HLA-I) binding peptides, given their potential use as peptide vaccines. Databases of HLA-I binding peptides hold therefore information on therapeutic targets essential for understanding immunity. In this work, we use in depth and accurate HLA-I peptidomics datasets determined by mass-spectrometry (MS) and analyze properties of the HLA-I binding peptides with structure-based computational approaches. HLA-I binding peptides are studied grouping all alleles together or in allotype-specific contexts. We capitalize on the increasing number of structurally determined proteins to (1) map the 3D structure of HLA-I binding peptides into the source proteins for analyzing their secondary structure and solvent accessibility in the protein context, and (2) search for potential differences between these properties in HLA-I binding peptides and in a reference dataset of HLA-I motif-like peptides. This is performed by an <i>in-house</i> developed heuristic search that considers peptides across all the human proteome and converges to a collection of peptides that exhibit exactly the same motif as the HLA-I peptides. Our results, based on 9-mers matched to protein 3D structures, clearly show enriched sampling for HLA-I presentation of helical fragments in the source proteins. This enrichment is significant, as compared to 9-mer HLA-I motif-like peptides, and is not entirely explained by the helical propensity of the preferred residues in the HLA-I motifs. We give possible hypothesis for the secondary structure biases observed in HLA-I peptides. This contribution is of potential interest for researchers working in the field of antigen presentation and proteolysis. This knowledge refines the understanding of the rules governing antigen presentation and could be added to the parameters of the current peptide-MHC class I binding predictors to increase their antigen predictive ability.</AbstractText><CopyrightInformation>Copyright © 2019 Perez, Bassani-Sternberg, Coukos, Gfeller and Zoete.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Perez</LastName><ForeName>Marta A S</ForeName><Initials>MAS</Initials><AffiliationInfo><Affiliation>Computer-Aided Molecular Engineering, Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Swiss Institute of Bioinformatics, Lausanne, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bassani-Sternberg</LastName><ForeName>Michal</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Human Integrated Tumor Immunology Discovery Engine, Department of Oncology, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Coukos</LastName><ForeName>George</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Human Integrated Tumor Immunology Discovery Engine, Department of Oncology, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gfeller</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Swiss Institute of Bioinformatics, Lausanne, Switzerland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Computational Cancer Biology, Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zoete</LastName><ForeName>Vincent</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Computer-Aided Molecular Engineering, Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Swiss Institute of Bioinformatics, Lausanne, Switzerland.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>11</Month><Day>22</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Front Immunol</MedlineTA><NlmUniqueID>101560960</NlmUniqueID><ISSNLinking>1664-3224</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">3D structure</Keyword><Keyword MajorTopicYN="N">HLA-I 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