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Graph‐based optimization of epitope coverage for vaccine antigen design
Epigraph is a recently developed algorithm that enables the computationally efficient design of single or multi‐antigen vaccines to maximize the potential epitope coverage for a diverse pathogen population. Potential epitopes are defined as short contiguous stretches of proteins, comparable in lengt...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763320/ https://www.ncbi.nlm.nih.gov/pubmed/28132437 http://dx.doi.org/10.1002/sim.7203 |
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author | Theiler, James Korber, Bette |
author_facet | Theiler, James Korber, Bette |
author_sort | Theiler, James |
collection | PubMed |
description | Epigraph is a recently developed algorithm that enables the computationally efficient design of single or multi‐antigen vaccines to maximize the potential epitope coverage for a diverse pathogen population. Potential epitopes are defined as short contiguous stretches of proteins, comparable in length to T‐cell epitopes. This optimal coverage problem can be formulated in terms of a directed graph, with candidate antigens represented as paths that traverse this graph. Epigraph protein sequences can also be used as the basis for designing peptides for experimental evaluation of immune responses in natural infections to highly variable proteins. The epigraph tool suite also enables rapid characterization of populations of diverse sequences from an immunological perspective. Fundamental distance measures are based on immunologically relevant shared potential epitope frequencies, rather than simple Hamming or phylogenetic distances. Here, we provide a mathematical description of the epigraph algorithm, include a comparison of different heuristics that can be used when graphs are not acyclic, and we describe an additional tool we have added to the web‐based epigraph tool suite that provides frequency summaries of all distinct potential epitopes in a population. We also show examples of the graphical output and summary tables that can be generated using the epigraph tool suite and explain their content and applications. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Statistics in Medicine published by John Wiley & Sons Ltd. |
format | Online Article Text |
id | pubmed-5763320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley & Sons, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-57633202018-01-17 Graph‐based optimization of epitope coverage for vaccine antigen design Theiler, James Korber, Bette Stat Med Special Issue Papers Epigraph is a recently developed algorithm that enables the computationally efficient design of single or multi‐antigen vaccines to maximize the potential epitope coverage for a diverse pathogen population. Potential epitopes are defined as short contiguous stretches of proteins, comparable in length to T‐cell epitopes. This optimal coverage problem can be formulated in terms of a directed graph, with candidate antigens represented as paths that traverse this graph. Epigraph protein sequences can also be used as the basis for designing peptides for experimental evaluation of immune responses in natural infections to highly variable proteins. The epigraph tool suite also enables rapid characterization of populations of diverse sequences from an immunological perspective. Fundamental distance measures are based on immunologically relevant shared potential epitope frequencies, rather than simple Hamming or phylogenetic distances. Here, we provide a mathematical description of the epigraph algorithm, include a comparison of different heuristics that can be used when graphs are not acyclic, and we describe an additional tool we have added to the web‐based epigraph tool suite that provides frequency summaries of all distinct potential epitopes in a population. We also show examples of the graphical output and summary tables that can be generated using the epigraph tool suite and explain their content and applications. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Statistics in Medicine published by John Wiley & Sons Ltd. John Wiley & Sons, Ltd 2017-01-29 2018-01-30 /pmc/articles/PMC5763320/ /pubmed/28132437 http://dx.doi.org/10.1002/sim.7203 Text en Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Statistics in Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial (http://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Special Issue Papers Theiler, James Korber, Bette Graph‐based optimization of epitope coverage for vaccine antigen design |
title | Graph‐based optimization of epitope coverage for vaccine antigen design |
title_full | Graph‐based optimization of epitope coverage for vaccine antigen design |
title_fullStr | Graph‐based optimization of epitope coverage for vaccine antigen design |
title_full_unstemmed | Graph‐based optimization of epitope coverage for vaccine antigen design |
title_short | Graph‐based optimization of epitope coverage for vaccine antigen design |
title_sort | graph‐based optimization of epitope coverage for vaccine antigen design |
topic | Special Issue Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763320/ https://www.ncbi.nlm.nih.gov/pubmed/28132437 http://dx.doi.org/10.1002/sim.7203 |
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