Benchmark datasets of immune receptor-epitope structural complexes

Autores
Mahajan, Swapnil; Yan, Zhen; Jespersen, Martin Closter; Jensen, Kamilla Kjærgaard; Marcatili, Paolo; Nielsen, Morten; Sette, Alessandro; Peters, Bjoern
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: The development of accurate epitope prediction tools is important in facilitating disease diagnostics, treatment and vaccine development. The advent of new approaches making use of antibody and TCR sequence information to predict receptor-specific epitopes have the potential to transform the epitope prediction field. Development and validation of these new generation of epitope prediction methods would benefit from regularly updated high-quality receptor-antigen complex datasets. Results: To address the need for high-quality datasets to benchmark performance of these new generation of receptor-specific epitope prediction tools, a webserver called SCEptRe (Structural Complexes of Epitope-Receptor) was created. SCEptRe extracts weekly updated 3D complexes of antibody-antigen, TCR-pMHC and MHC-ligand from the Immune Epitope Database and clusters them based on antigen, receptor and epitope features to generate benchmark datasets. SCEptRe also provides annotated information such as CDR sequences and VDJ genes on the receptors. Users can generate custom datasets based by selecting thresholds for structural quality and clustering parameters (e.g. resolution, R-free factor, antigen or epitope sequence identity) based on their need. Conclusions: SCEptRe provides weekly updated, user-customized comprehensive benchmark datasets of immune receptor-epitope structural complexes. These datasets can be used to develop and benchmark performance of receptor-specific epitope prediction tools in the future. SCEptRe is freely accessible at http://tools.iedb.org/sceptre.
Fil: Mahajan, Swapnil. La Jolla Institute for Allergy and Immunology; Estados Unidos
Fil: Yan, Zhen. La Jolla Institute for Allergy and Immunology; Estados Unidos
Fil: Jespersen, Martin Closter. Technical University of Denmark; Dinamarca
Fil: Jensen, Kamilla Kjærgaard. Technical University of Denmark; Dinamarca
Fil: Marcatili, Paolo. Technical University of Denmark; Dinamarca
Fil: Nielsen, Morten. Technical University of Denmark; Dinamarca. 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: Sette, Alessandro. La Jolla Institute for Allergy and Immunology; Estados Unidos
Fil: Peters, Bjoern. La Jolla Institute for Allergy and Immunology; Estados Unidos
Materia
ANTIBODY
EPITOPE
EPITOPE PREDICTION
IEDB
MHC
PROTEIN STRUCTURES
TCR
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/124580
Acceder
id CONICETDig_81e903d7a0004f4a010b63c3b7f80d82
oai_identifier_str oai:ri.conicet.gov.ar:11336/124580
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Benchmark datasets of immune receptor-epitope structural complexesMahajan, SwapnilYan, ZhenJespersen, Martin ClosterJensen, Kamilla KjærgaardMarcatili, PaoloNielsen, MortenSette, AlessandroPeters, BjoernANTIBODYEPITOPEEPITOPE PREDICTIONIEDBMHCPROTEIN STRUCTURESTCRhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3Background: The development of accurate epitope prediction tools is important in facilitating disease diagnostics, treatment and vaccine development. The advent of new approaches making use of antibody and TCR sequence information to predict receptor-specific epitopes have the potential to transform the epitope prediction field. Development and validation of these new generation of epitope prediction methods would benefit from regularly updated high-quality receptor-antigen complex datasets. Results: To address the need for high-quality datasets to benchmark performance of these new generation of receptor-specific epitope prediction tools, a webserver called SCEptRe (Structural Complexes of Epitope-Receptor) was created. SCEptRe extracts weekly updated 3D complexes of antibody-antigen, TCR-pMHC and MHC-ligand from the Immune Epitope Database and clusters them based on antigen, receptor and epitope features to generate benchmark datasets. SCEptRe also provides annotated information such as CDR sequences and VDJ genes on the receptors. Users can generate custom datasets based by selecting thresholds for structural quality and clustering parameters (e.g. resolution, R-free factor, antigen or epitope sequence identity) based on their need. Conclusions: SCEptRe provides weekly updated, user-customized comprehensive benchmark datasets of immune receptor-epitope structural complexes. These datasets can be used to develop and benchmark performance of receptor-specific epitope prediction tools in the future. SCEptRe is freely accessible at http://tools.iedb.org/sceptre.Fil: Mahajan, Swapnil. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Yan, Zhen. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Jespersen, Martin Closter. Technical University of Denmark; DinamarcaFil: Jensen, Kamilla Kjærgaard. Technical University of Denmark; DinamarcaFil: Marcatili, Paolo. Technical University of Denmark; DinamarcaFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. 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: Sette, Alessandro. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Peters, Bjoern. La Jolla Institute for Allergy and Immunology; Estados UnidosBioMed Central2019-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/124580Mahajan, Swapnil; Yan, Zhen; Jespersen, Martin Closter; Jensen, Kamilla Kjærgaard; Marcatili, Paolo; et al.; Benchmark datasets of immune receptor-epitope structural complexes; BioMed Central; BMC Bioinformatics; 20; 1; 10-2019; 1-71471-2105CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3109-6info:eu-repo/semantics/altIdentifier/doi/10.1186/s12859-019-3109-6info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:20:02Zoai:ri.conicet.gov.ar:11336/124580instacron: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:34982025-09-29 10:20:02.292CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Benchmark datasets of immune receptor-epitope structural complexes
title Benchmark datasets of immune receptor-epitope structural complexes
spellingShingle Benchmark datasets of immune receptor-epitope structural complexes
Mahajan, Swapnil
ANTIBODY
EPITOPE
EPITOPE PREDICTION
IEDB
MHC
PROTEIN STRUCTURES
TCR
title_short Benchmark datasets of immune receptor-epitope structural complexes
title_full Benchmark datasets of immune receptor-epitope structural complexes
title_fullStr Benchmark datasets of immune receptor-epitope structural complexes
title_full_unstemmed Benchmark datasets of immune receptor-epitope structural complexes
title_sort Benchmark datasets of immune receptor-epitope structural complexes
dc.creator.none.fl_str_mv Mahajan, Swapnil
Yan, Zhen
Jespersen, Martin Closter
Jensen, Kamilla Kjærgaard
Marcatili, Paolo
Nielsen, Morten
Sette, Alessandro
Peters, Bjoern
author Mahajan, Swapnil
author_facet Mahajan, Swapnil
Yan, Zhen
Jespersen, Martin Closter
Jensen, Kamilla Kjærgaard
Marcatili, Paolo
Nielsen, Morten
Sette, Alessandro
Peters, Bjoern
author_role author
author2 Yan, Zhen
Jespersen, Martin Closter
Jensen, Kamilla Kjærgaard
Marcatili, Paolo
Nielsen, Morten
Sette, Alessandro
Peters, Bjoern
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ANTIBODY
EPITOPE
EPITOPE PREDICTION
IEDB
MHC
PROTEIN STRUCTURES
TCR
topic ANTIBODY
EPITOPE
EPITOPE PREDICTION
IEDB
MHC
PROTEIN STRUCTURES
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 Background: The development of accurate epitope prediction tools is important in facilitating disease diagnostics, treatment and vaccine development. The advent of new approaches making use of antibody and TCR sequence information to predict receptor-specific epitopes have the potential to transform the epitope prediction field. Development and validation of these new generation of epitope prediction methods would benefit from regularly updated high-quality receptor-antigen complex datasets. Results: To address the need for high-quality datasets to benchmark performance of these new generation of receptor-specific epitope prediction tools, a webserver called SCEptRe (Structural Complexes of Epitope-Receptor) was created. SCEptRe extracts weekly updated 3D complexes of antibody-antigen, TCR-pMHC and MHC-ligand from the Immune Epitope Database and clusters them based on antigen, receptor and epitope features to generate benchmark datasets. SCEptRe also provides annotated information such as CDR sequences and VDJ genes on the receptors. Users can generate custom datasets based by selecting thresholds for structural quality and clustering parameters (e.g. resolution, R-free factor, antigen or epitope sequence identity) based on their need. Conclusions: SCEptRe provides weekly updated, user-customized comprehensive benchmark datasets of immune receptor-epitope structural complexes. These datasets can be used to develop and benchmark performance of receptor-specific epitope prediction tools in the future. SCEptRe is freely accessible at http://tools.iedb.org/sceptre.
Fil: Mahajan, Swapnil. La Jolla Institute for Allergy and Immunology; Estados Unidos
Fil: Yan, Zhen. La Jolla Institute for Allergy and Immunology; Estados Unidos
Fil: Jespersen, Martin Closter. Technical University of Denmark; Dinamarca
Fil: Jensen, Kamilla Kjærgaard. Technical University of Denmark; Dinamarca
Fil: Marcatili, Paolo. Technical University of Denmark; Dinamarca
Fil: Nielsen, Morten. Technical University of Denmark; Dinamarca. 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: Sette, Alessandro. La Jolla Institute for Allergy and Immunology; Estados Unidos
Fil: Peters, Bjoern. La Jolla Institute for Allergy and Immunology; Estados Unidos
description Background: The development of accurate epitope prediction tools is important in facilitating disease diagnostics, treatment and vaccine development. The advent of new approaches making use of antibody and TCR sequence information to predict receptor-specific epitopes have the potential to transform the epitope prediction field. Development and validation of these new generation of epitope prediction methods would benefit from regularly updated high-quality receptor-antigen complex datasets. Results: To address the need for high-quality datasets to benchmark performance of these new generation of receptor-specific epitope prediction tools, a webserver called SCEptRe (Structural Complexes of Epitope-Receptor) was created. SCEptRe extracts weekly updated 3D complexes of antibody-antigen, TCR-pMHC and MHC-ligand from the Immune Epitope Database and clusters them based on antigen, receptor and epitope features to generate benchmark datasets. SCEptRe also provides annotated information such as CDR sequences and VDJ genes on the receptors. Users can generate custom datasets based by selecting thresholds for structural quality and clustering parameters (e.g. resolution, R-free factor, antigen or epitope sequence identity) based on their need. Conclusions: SCEptRe provides weekly updated, user-customized comprehensive benchmark datasets of immune receptor-epitope structural complexes. These datasets can be used to develop and benchmark performance of receptor-specific epitope prediction tools in the future. SCEptRe is freely accessible at http://tools.iedb.org/sceptre.
publishDate 2019
dc.date.none.fl_str_mv 2019-10
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/11336/124580
Mahajan, Swapnil; Yan, Zhen; Jespersen, Martin Closter; Jensen, Kamilla Kjærgaard; Marcatili, Paolo; et al.; Benchmark datasets of immune receptor-epitope structural complexes; BioMed Central; BMC Bioinformatics; 20; 1; 10-2019; 1-7
1471-2105
CONICET Digital
CONICET
url http://hdl.handle.net/11336/124580
identifier_str_mv Mahajan, Swapnil; Yan, Zhen; Jespersen, Martin Closter; Jensen, Kamilla Kjærgaard; Marcatili, Paolo; et al.; Benchmark datasets of immune receptor-epitope structural complexes; BioMed Central; BMC Bioinformatics; 20; 1; 10-2019; 1-7
1471-2105
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3109-6
info:eu-repo/semantics/altIdentifier/doi/10.1186/s12859-019-3109-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
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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score 13.070432

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