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Selection‐based design of in silico dengue epitope ensemble vaccines
Author(s) -
Murphy David,
Reche Pedro,
Flower Darren R.
Publication year - 2019
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/cbdd.13357
Subject(s) - epitope , immunogenicity , dengue fever , virology , dengue virus , in silico , major histocompatibility complex , dengue vaccine , biology , population , mhc class i , antigen , computational biology , immunology , medicine , genetics , gene , environmental health
Dengue virus affects approximately 130 countries. Twenty‐five percentage of infections result in febrile, self‐limiting illness; heterotypic infection results in potentially fatal dengue haemorrhagic fever or dengue shock syndrome. Only one vaccine is currently available. Its efficacy is very variable. Thus, to target dengue, we used an innovative immunoinformatics protocol to design a putative epitope ensemble vaccine by selecting an optimal set of highly conserved epitopes with experimentally verified immunogenicity. From 1597 CD 4+ and MHC II epitopes, six MHC Class I epitopes ( RAVHADMGYW , GPWHLGKLEM , GLYGNGVVTK , NMIIMDEAHF , KTWAYHGSY and WAYHGSYEV ) and nine MHC Class II epitopes ( LAKAIFKLTYQNKVV , GKIVGLYGNGVVTTS , AAIFMTATPPGSVEA , AAIFMTATPPGTADA , GKTVWFVPSIKAGND , KFWNTTIAVSMANIF , RAIWYMWLGARYLEF , VGTYGLNTFTNMEVQ and WTLMYFHRRDLRLAA ) were selected; this candidate vaccine achieved a world population coverage of 92.49%.