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Benchmark datasets of immune receptor-epitope structural complexes

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...

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Autores principales: Mahajan, Swapnil, Yan, Zhen, Jespersen, Martin Closter, Jensen, Kamilla Kjærgaard, Marcatili, Paolo, Nielsen, Morten, Sette, Alessandro, Peters, Bjoern
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785892/
https://www.ncbi.nlm.nih.gov/pubmed/31601176
http://dx.doi.org/10.1186/s12859-019-3109-6
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author Mahajan, Swapnil
Yan, Zhen
Jespersen, Martin Closter
Jensen, Kamilla Kjærgaard
Marcatili, Paolo
Nielsen, Morten
Sette, Alessandro
Peters, Bjoern
author_facet Mahajan, Swapnil
Yan, Zhen
Jespersen, Martin Closter
Jensen, Kamilla Kjærgaard
Marcatili, Paolo
Nielsen, Morten
Sette, Alessandro
Peters, Bjoern
author_sort Mahajan, Swapnil
collection PubMed
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.
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spelling pubmed-67858922019-10-17 Benchmark datasets of immune receptor-epitope structural complexes Mahajan, Swapnil Yan, Zhen Jespersen, Martin Closter Jensen, Kamilla Kjærgaard Marcatili, Paolo Nielsen, Morten Sette, Alessandro Peters, Bjoern BMC Bioinformatics Methodology Article 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. BioMed Central 2019-10-10 /pmc/articles/PMC6785892/ /pubmed/31601176 http://dx.doi.org/10.1186/s12859-019-3109-6 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Mahajan, Swapnil
Yan, Zhen
Jespersen, Martin Closter
Jensen, Kamilla Kjærgaard
Marcatili, Paolo
Nielsen, Morten
Sette, Alessandro
Peters, Bjoern
Benchmark datasets of immune receptor-epitope structural complexes
title 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_short Benchmark datasets of immune receptor-epitope structural complexes
title_sort benchmark datasets of immune receptor-epitope structural complexes
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785892/
https://www.ncbi.nlm.nih.gov/pubmed/31601176
http://dx.doi.org/10.1186/s12859-019-3109-6
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