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Joint epitope selection and spacer design for string-of-beads vaccines
MOTIVATION: Conceptually, epitope-based vaccine design poses two distinct problems: (i) selecting the best epitopes to elicit the strongest possible immune response and (ii) arranging and linking them through short spacer sequences to string-of-beads vaccines, so that their recovery likelihood durin...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773482/ https://www.ncbi.nlm.nih.gov/pubmed/33381831 http://dx.doi.org/10.1093/bioinformatics/btaa790 |
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author | Dorigatti, Emilio Schubert, Benjamin |
author_facet | Dorigatti, Emilio Schubert, Benjamin |
author_sort | Dorigatti, Emilio |
collection | PubMed |
description | MOTIVATION: Conceptually, epitope-based vaccine design poses two distinct problems: (i) selecting the best epitopes to elicit the strongest possible immune response and (ii) arranging and linking them through short spacer sequences to string-of-beads vaccines, so that their recovery likelihood during antigen processing is maximized. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing, thus resulting in vaccines with less effective immunogenicity in vivo. RESULTS: In this work, we present a computational approach based on linear programming, called JessEV, that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte Carlo cleavage simulations to show that a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen and population coverage of the resulting vaccines by at least 2-fold. AVAILABILITY AND IMPLEMENTATION: The software and the data analyzed are available at https://github.com/SchubertLab/JessEV. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-7773482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77734822021-01-05 Joint epitope selection and spacer design for string-of-beads vaccines Dorigatti, Emilio Schubert, Benjamin Bioinformatics Genomes MOTIVATION: Conceptually, epitope-based vaccine design poses two distinct problems: (i) selecting the best epitopes to elicit the strongest possible immune response and (ii) arranging and linking them through short spacer sequences to string-of-beads vaccines, so that their recovery likelihood during antigen processing is maximized. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing, thus resulting in vaccines with less effective immunogenicity in vivo. RESULTS: In this work, we present a computational approach based on linear programming, called JessEV, that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte Carlo cleavage simulations to show that a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen and population coverage of the resulting vaccines by at least 2-fold. AVAILABILITY AND IMPLEMENTATION: The software and the data analyzed are available at https://github.com/SchubertLab/JessEV. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-12-29 /pmc/articles/PMC7773482/ /pubmed/33381831 http://dx.doi.org/10.1093/bioinformatics/btaa790 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Genomes Dorigatti, Emilio Schubert, Benjamin Joint epitope selection and spacer design for string-of-beads vaccines |
title | Joint epitope selection and spacer design for string-of-beads vaccines |
title_full | Joint epitope selection and spacer design for string-of-beads vaccines |
title_fullStr | Joint epitope selection and spacer design for string-of-beads vaccines |
title_full_unstemmed | Joint epitope selection and spacer design for string-of-beads vaccines |
title_short | Joint epitope selection and spacer design for string-of-beads vaccines |
title_sort | joint epitope selection and spacer design for string-of-beads vaccines |
topic | Genomes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773482/ https://www.ncbi.nlm.nih.gov/pubmed/33381831 http://dx.doi.org/10.1093/bioinformatics/btaa790 |
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