从基因组和蛋白质组学信息中鉴定细胞毒性T细胞表位:“人类MHC计划”。

Reviews in immunogenetics Pub Date : 2000-01-01
S L Lauemøller, C Kesmir, S L Corbet, A Fomsgaard, A Holm, M H Claesson, S Brunak, S Buus
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引用次数: 0

摘要

包括致病微生物在内的许多物种的完整基因组及其编码蛋白质或蛋白质组正在迅速变得可用。蛋白质组非常多样化,构成了起源生物的独特印记,即使在肽水平上也能进行积极的鉴定和准确的区分。肽是免疫系统的关键靶点,这并不奇怪。因此,一旦知道了免疫系统如何产生和处理多肽,蛋白质组就可以被翻译成免疫原。最近的进展已经确定了许多涉及的基本原则。最具选择性的单一事件是肽与MHC的结合,这使得为最常见的MHC变异建立肽结合的准确描述和预测变得尤为重要。这些预测应与抗原加工中涉及的其他步骤的预测相结合,因为这些预测是可行的。在免疫识别方面翻译积累的初级序列数据库的能力应该使科学家和临床医生能够分析任何感兴趣的蛋白质,以寻找潜在免疫原性表位的存在。还应该开发扫描整个蛋白质组的计算工具,因为这将使疫苗开发和免疫治疗成为一种合理的方法。因此,候选疫苗表位可以从各种微生物基因组计划中预测,从肿瘤mRNA表达谱(“转录组”)中预测肿瘤候选疫苗,以及从人类基因组中预测自身抗原。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying cytotoxic T cell epitopes from genomic and proteomic information: "The human MHC project.".

Complete genomes of many species including pathogenic microorganisms are rapidly becoming available and with them the encoded proteins, or proteomes. Proteomes are extremely diverse and constitute unique imprints of the originating organisms allowing positive identification and accurate discrimination, even at the peptide level. It is not surprising that peptides are key targets of the immune system. It follows that proteomes can be translated into immunogens once it is known how the immune system generates and handles peptides. Recent advances have identified many of the basic principles involved. The single most selective event is that of peptide binding to MHC, making it particularly important to establish accurate descriptions and predictions of peptide binding for the most common MHC variants. These predictions should be integrated with those of other steps involved in antigen processing, as these become available. The ability to translate the accumulating primary sequence databases in terms of immune recognition should enable scientists and clinicians to analyze any protein of interest for the presence of potentially immunogenic epitopes. The computational tools to scan entire proteomes should also be developed, as this would enable a rational approach to vaccine development and immunotherapy. Thus, candidate vaccine epitopes might be predicted from the various microbial genome projects, tumor vaccine candidates from mRNA expression profiling of tumors ("transcriptomes") and auto-antigens from the human genome.

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