title: Graph-based optimization of epitope coverage for vaccine antigen design.
abstract: 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.
authors.affiliation: Los Alamos National Laboratory, Los Alamos, 87545, NM, U.S.A.|New Mexico Consortium, Los Alamos, 87545, NM, U.S.A.
authors.forename: James
authors.initials: J
authors.lastname: Theiler
authors.affiliation: Los Alamos National Laboratory, Los Alamos, 87545, NM, U.S.A.|New Mexico Consortium, Los Alamos, 87545, NM, U.S.A.
authors.forename: Bette
authors.identifier: http://orcid.org/0000-0002-2026-5757
authors.initials: B
authors.lastname: Korber
mesh_terms: D016915:AIDS Vaccines / Q000737:chemistry / Q000235:genetics / Q000276:immunology; D000465:Algorithms; D000595:Amino Acid Sequence; D056808:Biostatistics / Q000379:methods; D003196:Computer Graphics; D015195:Drug Design; D000939:Epitopes / Q000737:chemistry / Q000235:genetics / Q000276:immunology*; D018984:Epitopes, T-Lymphocyte / Q000737:chemistry / Q000235:genetics / Q000276:immunology; D016655:HIV Core Protein p24 / Q000737:chemistry / Q000235:genetics / Q000276:immunology; D006801:Humans; D020407:Internet; D014584:User-Computer Interface; D014612:Vaccines / Q000737:chemistry / Q000235:genetics / Q000276:immunology*
chemical_list: D016915:AIDS Vaccines; D000939:Epitopes; D018984:Epitopes, T-Lymphocyte; D016655:HIV Core Protein p24; D014612:Vaccines
keywords: algorithm; antigen; de Bruijn graph; directed acyclic graph; epitope; vaccine