A computational model to predict the immune system activation by citrus-derived vaccine adjuvants.
Bioinformatics
; 32(17): 2672-80, 2016 09 01.
Article
em En
| MEDLINE
| ID: mdl-27162187
ABSTRACT
MOTIVATION 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. RESULTS:
We developed a computational framework that provides a complete pipeline capable of predicting the best citrus-derived adjuvants for enhancing the immune system response using, as a target disease model, influenza A infection. In silico simulations suggested a good immune efficacy of specific citrus-derived adjuvant (Beta Sitosterol) that was then confirmed in vivoAvailability:
The model is available visiting the following URL http//vaima.dmi.unict.it/AdjSim CONTACT francesco.pappalardo@unict.it; fp@francescopappalardo.net.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Vacinas contra Influenza
/
Adjuvantes Imunológicos
/
Citrus
/
Sistema Imunitário
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Aged
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Humans
/
Newborn
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2016
Tipo de documento:
Article