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A computational model to predict the immune system activation by citrus-derived vaccine adjuvants
Author(s) -
Francesco Pappalardo,
Epifanio Fichera,
Nicoletta Paparone,
A. Lombardo,
Marzio Pennisi,
Giulia Russo,
Marco Leotta,
Alessandro Pedretti,
Francesco De Fiore,
Santo Motta
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw293
Subject(s) - adjuvant , immune system , antigen , vaccine adjuvant , vaccine efficacy , immunology , adverse effect , computational biology , medicine , computer science , biology , pharmacology
Vaccines represent the most effective and cost-efficient weapons against a wide range of diseases. Nowadays new generation vaccines based on subunit antigens reduce adverse effects in high risk individuals. However, vaccine antigens are often poor immunogens when administered alone. Adjuvants represent a good strategy to overcome such hurdles, indeed they are able to: enhance the immune response; allow antigens sparing; accelerate the specific immune response; and increase vaccine efficacy in vulnerable groups such as newborns, elderly or immuno-compromised people. However, due to safety concerns and adverse reactions, there are only a few adjuvants approved for use in humans. Moreover, in practice current adjuvants sometimes fail to confer adequate stimulation. Hence, there is an imperative need to develop novel adjuvants that overcome the limitations of the currently available licensed adjuvants.

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