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Multi-Epitope Peptide-Based and Vaccinia-Based Universal Influenza Vaccine Candidates Subjected to Clinical Trials.
Romeli, Syazwani; Hassan, Sharifah Syed; Yap, Wei Boon.
Afiliação
  • Romeli S; Biomedical Science Programme, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
  • Hassan SS; Center of Toxicology and Health Risk Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
  • Yap WB; Jeffrey Cheah School of Medicine & Health Sciences, Monash University Malaysia, Selangor, Malaysia.
Malays J Med Sci ; 27(2): 10-20, 2020 Mar.
Article em En | MEDLINE | ID: mdl-32788837
In light of the limited protection conferred by current influenza vaccines, immunisation using universal influenza vaccines has been proposed for protection against all or most influenza sub-types. The fundamental principle of universal influenza vaccines is based on conserved antigens found in most influenza strains, such as matrix 2, nucleocapsid, matrix 1 and stem of hemagglutinin proteins. These antigens trigger cross-protective immunity against different influenza strains. Many researchers have attempted to produce the conserved epitopes of these antigens in the form of peptides in the hope of generating universal influenza vaccine candidates that can broadly induce cross-reactive protection against influenza viral infections. However, peptide vaccines are poorly immunogenic when applied individually owing to their small molecular sizes. Hence, strategies, such as combining peptides as multi-epitope vaccines or presenting peptides on vaccinia virus particles, are employed. This review discusses the clinical and laboratory findings of several multi-epitope peptide vaccine candidates and vaccinia-based peptide vaccines. The majority of these vaccine candidates have reached the clinical trial phase. The findings in this study will indeed shed light on the applicability of universal influenza vaccines to prevent seasonal and pandemic influenza outbreaks in the near future.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article