T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities
- Autores
- Lanzarotti, Esteban Omar; Marcatili, Paolo; Nielsen, Morten
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- T-cell receptors (TCR) mediate immune responses recognizing peptides in complex with major histocompatibility complexes (pMHC) displayed on the surface of cells. Resolving the challenge of predicting the cognate pMHC target of a TCR would benefit many applications in the field of immunology, including vaccine design/discovery and the development of immunotherapies. Here, we developed a model for prediction of TCR targets based on similarity to a database of TCRs with known targets. Benchmarking the model on a large set of TCRs with known target, we demonstrated how the predictive performance is increased (i) by focusing on CDRs rather than the full length TCR protein sequences, (ii) by incorporating information from paired α and β chains, and (iii) integrating information for all 6 CDR loops rather than just CDR3. Finally, we show how integration of the structure of CDR loops, as obtained through homology modeling, boosts the predictive power of the model, in particular in situations where no high-similarity TCRs are available for the query. These findings demonstrate that TCRs that bind to the same target also share, to a very high degree, sequence, and structural features. This observation has profound impact for future development of prediction models for TCR-pMHC interactions and for the use of such models for the rational design of T cell based therapies.
Fil: Lanzarotti, Esteban Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina
Fil: Marcatili, Paolo. Technical University of Denmark; Dinamarca
Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina. Technical University of Denmark; Dinamarca - Materia
-
CDR
EPITOPE
MHC
STRUCTURE
TCR - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/152984
Ver los metadatos del registro completo
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T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similaritiesLanzarotti, Esteban OmarMarcatili, PaoloNielsen, MortenCDREPITOPEMHCSTRUCTURETCRhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3T-cell receptors (TCR) mediate immune responses recognizing peptides in complex with major histocompatibility complexes (pMHC) displayed on the surface of cells. Resolving the challenge of predicting the cognate pMHC target of a TCR would benefit many applications in the field of immunology, including vaccine design/discovery and the development of immunotherapies. Here, we developed a model for prediction of TCR targets based on similarity to a database of TCRs with known targets. Benchmarking the model on a large set of TCRs with known target, we demonstrated how the predictive performance is increased (i) by focusing on CDRs rather than the full length TCR protein sequences, (ii) by incorporating information from paired α and β chains, and (iii) integrating information for all 6 CDR loops rather than just CDR3. Finally, we show how integration of the structure of CDR loops, as obtained through homology modeling, boosts the predictive power of the model, in particular in situations where no high-similarity TCRs are available for the query. These findings demonstrate that TCRs that bind to the same target also share, to a very high degree, sequence, and structural features. This observation has profound impact for future development of prediction models for TCR-pMHC interactions and for the use of such models for the rational design of T cell based therapies.Fil: Lanzarotti, Esteban Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Marcatili, Paolo. Technical University of Denmark; DinamarcaFil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina. Technical University of Denmark; DinamarcaFrontiers Media2019-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/152984Lanzarotti, Esteban Omar; Marcatili, Paolo; Nielsen, Morten; T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities; Frontiers Media; Frontiers in Immunology; 10; 2080; 8-2019; 1-101664-3224CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3389/fimmu.2019.02080info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fimmu.2019.02080/fullinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:00:02Zoai:ri.conicet.gov.ar:11336/152984instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:00:02.645CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities |
title |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities |
spellingShingle |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities Lanzarotti, Esteban Omar CDR EPITOPE MHC STRUCTURE TCR |
title_short |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities |
title_full |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities |
title_fullStr |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities |
title_full_unstemmed |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities |
title_sort |
T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities |
dc.creator.none.fl_str_mv |
Lanzarotti, Esteban Omar Marcatili, Paolo Nielsen, Morten |
author |
Lanzarotti, Esteban Omar |
author_facet |
Lanzarotti, Esteban Omar Marcatili, Paolo Nielsen, Morten |
author_role |
author |
author2 |
Marcatili, Paolo Nielsen, Morten |
author2_role |
author author |
dc.subject.none.fl_str_mv |
CDR EPITOPE MHC STRUCTURE TCR |
topic |
CDR EPITOPE MHC STRUCTURE TCR |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/3.3 https://purl.org/becyt/ford/3 |
dc.description.none.fl_txt_mv |
T-cell receptors (TCR) mediate immune responses recognizing peptides in complex with major histocompatibility complexes (pMHC) displayed on the surface of cells. Resolving the challenge of predicting the cognate pMHC target of a TCR would benefit many applications in the field of immunology, including vaccine design/discovery and the development of immunotherapies. Here, we developed a model for prediction of TCR targets based on similarity to a database of TCRs with known targets. Benchmarking the model on a large set of TCRs with known target, we demonstrated how the predictive performance is increased (i) by focusing on CDRs rather than the full length TCR protein sequences, (ii) by incorporating information from paired α and β chains, and (iii) integrating information for all 6 CDR loops rather than just CDR3. Finally, we show how integration of the structure of CDR loops, as obtained through homology modeling, boosts the predictive power of the model, in particular in situations where no high-similarity TCRs are available for the query. These findings demonstrate that TCRs that bind to the same target also share, to a very high degree, sequence, and structural features. This observation has profound impact for future development of prediction models for TCR-pMHC interactions and for the use of such models for the rational design of T cell based therapies. Fil: Lanzarotti, Esteban Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina Fil: Marcatili, Paolo. Technical University of Denmark; Dinamarca Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina. Technical University of Denmark; Dinamarca |
description |
T-cell receptors (TCR) mediate immune responses recognizing peptides in complex with major histocompatibility complexes (pMHC) displayed on the surface of cells. Resolving the challenge of predicting the cognate pMHC target of a TCR would benefit many applications in the field of immunology, including vaccine design/discovery and the development of immunotherapies. Here, we developed a model for prediction of TCR targets based on similarity to a database of TCRs with known targets. Benchmarking the model on a large set of TCRs with known target, we demonstrated how the predictive performance is increased (i) by focusing on CDRs rather than the full length TCR protein sequences, (ii) by incorporating information from paired α and β chains, and (iii) integrating information for all 6 CDR loops rather than just CDR3. Finally, we show how integration of the structure of CDR loops, as obtained through homology modeling, boosts the predictive power of the model, in particular in situations where no high-similarity TCRs are available for the query. These findings demonstrate that TCRs that bind to the same target also share, to a very high degree, sequence, and structural features. This observation has profound impact for future development of prediction models for TCR-pMHC interactions and for the use of such models for the rational design of T cell based therapies. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-08 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/152984 Lanzarotti, Esteban Omar; Marcatili, Paolo; Nielsen, Morten; T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities; Frontiers Media; Frontiers in Immunology; 10; 2080; 8-2019; 1-10 1664-3224 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/152984 |
identifier_str_mv |
Lanzarotti, Esteban Omar; Marcatili, Paolo; Nielsen, Morten; T-cell receptor cognate target prediction based on paired α and β chain sequence and structural CDR loop similarities; Frontiers Media; Frontiers in Immunology; 10; 2080; 8-2019; 1-10 1664-3224 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.3389/fimmu.2019.02080 info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fimmu.2019.02080/full |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Frontiers Media |
publisher.none.fl_str_mv |
Frontiers Media |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1842269616281223168 |
score |
13.13397 |