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真核病原体计算疫苗发现指南。

A guide to in silico vaccine discovery for eukaryotic pathogens.

机构信息

School of Medical and Molecular Sciences, Ithree Institute, University of Technology Sydney. Tel.: +61 2 9514 4161;

出版信息

Brief Bioinform. 2013 Nov;14(6):753-74. doi: 10.1093/bib/bbs066. Epub 2012 Oct 24.

Abstract

In this article, a framework for an in silico pipeline is presented as a guide to high-throughput vaccine candidate discovery for eukaryotic pathogens, such as helminths and protozoa. Eukaryotic pathogens are mostly parasitic and cause some of the most damaging and difficult to treat diseases in humans and livestock. Consequently, these parasitic pathogens have a significant impact on economy and human health. The pipeline is based on the principle of reverse vaccinology and is constructed from freely available bioinformatics programs. There are several successful applications of reverse vaccinology to the discovery of subunit vaccines against prokaryotic pathogens but not yet against eukaryotic pathogens. The overriding aim of the pipeline, which focuses on eukaryotic pathogens, is to generate through computational processes of elimination and evidence gathering a ranked list of proteins based on a scoring system. These proteins are either surface components of the target pathogen or are secreted by the pathogen and are of a type known to be antigenic. No perfect predictive method is yet available; therefore, the highest-scoring proteins from the list require laboratory validation.

摘要

本文提出了一个计算管道框架,作为高通量疫苗候选物发现的指导,用于真核病原体,如蠕虫和原生动物。真核病原体大多是寄生虫,会导致人类和家畜中一些最具破坏性和最难治疗的疾病。因此,这些寄生虫病原体对经济和人类健康有重大影响。该管道基于反向疫苗学的原理,并由免费提供的生物信息学程序构建。反向疫苗学已成功应用于针对原核病原体的亚单位疫苗的发现,但尚未应用于真核病原体。该管道的主要目标是针对真核病原体,通过消除和收集证据的计算过程,根据评分系统生成基于蛋白质的排序列表。这些蛋白质要么是目标病原体的表面成分,要么是由病原体分泌的,并且属于已知具有抗原性的类型。目前还没有完美的预测方法;因此,列表中得分最高的蛋白质需要实验室验证。

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