T-cell epitope vaccine design by immunoinformatics

被引:282
作者
Patronov, Atanas [1 ]
Doytchinova, Irini [1 ]
机构
[1] Med Univ Sofia, Fac Pharm, Dept Chem, Sofia, Bulgaria
关键词
T-cell epitopes; major histocompatibility-binding prediction; immunoinformatics; MHC CLASS-I; PEPTIDE BINDING-AFFINITY; HIDDEN MARKOV-MODELS; WORLD-WIDE-WEB; MOLECULAR-DYNAMICS; BIOINFORMATIC APPROACH; PROTEIN-PEPTIDE; DNA VACCINES; QUANTITATIVE PREDICTION; ACTIVE IMMUNIZATION;
D O I
10.1098/rsob.120139
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Vaccination is generally considered to be the most effective method of preventing infectious diseases. All vaccinations work by presenting a foreign antigen to the immune system in order to evoke an immune response. The active agent of a vaccine may be intact but inactivated ('attenuated') forms of the causative pathogens (bacteria or viruses), or purified components of the pathogen that have been found to be highly immunogenic. The increased understanding of antigen recognition at molecular level has resulted in the development of rationally designed peptide vaccines. The concept of peptide vaccines is based on identification and chemical synthesis of B-cell and T-cell epitopes which are immunodominant and can induce specific immune responses. The accelerating growth of bioinformatics techniques and applications along with the substantial amount of experimental data has given rise to a new field, called immunoinformatics. Immunoinformatics is a branch of bioinformatics dealing with in silico analysis and modelling of immunological data and problems. Different sequence- and structure-based immunoinformatics methods are reviewed in the paper.
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页数:13
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