Analysis of T cell epitope repertoire.

描述(由申请人提供)： 在移植排斥反应、对病毒的免疫防御和自身免疫的核心，是CD8T细胞和NK细胞识别MHC-I分子背景下的多肽。在这里，我们将结合我们在免疫学、计算机建模、数据库设计和数学分析方面的技能，为小鼠和人的大多数主要MHC-I等位基因生成预测自我和病毒多肽的文库。我们与两个实验小组合作验证预测的多肽，并研究它们与自身免疫的相关性。我们将开发和合并的主要元素是多肽MHC-I结合、TAP结合和多肽切割概率的估计。我们将合并得到的分数，并将它们应用于现有的基因组数据。 为了生产人类文库，我们将开发新的生物信息学工具，并将它们与现有工具合并。结果将是一个分数，该分数决定了呈现多肽的概率。我们将把这个分数应用于人类、小鼠和一些病毒基因组，以确定自我和非自我的曲目。预期的文库将通过与一个实验小组的合作进行验证。每个经过验证的文库将包含一个多肽列表(来自人类、小鼠或病毒来源)，这些多肽可以在给定的MHC-I等位基因上呈现，并伴随着代表多肽“质量”的分数。这个分数将包括估计的与MHC结合槽的结合亲和力，TAP结合概率，切割概率(由常规或免疫蛋白酶体)和携带多肽的基因的平均表达水平。病毒多肽还将包括一个分数，代表它们与自身多肽的最大相似性。由此产生的经验证的图书馆将通过基于网络的服务器向公众开放。 准确预测等位基因特异性的MHC-多肽相互作用可能使我们能够操纵器官特异性自身免疫性疾病的自身免疫反应，以及对病毒的免疫反应。它还可以帮助免疫学家提高他们优化移植MHC配型的能力。将在当前研究计划中开发的文库的主要应用是：a)多肽疫苗开发方法学。我们将使用病毒多肽文库来检测这些文库中存在的保守病毒基因组区域的多肽。我们将使用这些多肽来产生基因序列，这些基因序列编码的蛋白质具有与病毒相同的免疫学特征，而不会产生致病作用。在减毒病毒过于危险或无法获得的情况下，这些多肽是很好的多肽疫苗候选者。B)分析自身免疫性疾病(主要是IDDM和MS)的免疫系统特征，以及MHC的使用和自身免疫之间的联系。这部分研究将与研究自身免疫中的B和T细胞谱系的实验小组合作完成。

DESCRIPTION (provided by applicant): At the core of transplant rejection, immune defense against viruses and autoimmunity and is the recognition of peptides in the context of MHC-I molecules by CD8 T cells and NK cells. Here, we will combine our skills in immunology, computer modeling, database design and mathematical analysis to generate libraries of predicted self and viral peptides for most major MHC-I alleles in mouse and men. We collaborate with two experimental groups to validate the predicted peptides and study their correlation with autoimmunity. The main elements we will develop and merge are estimates of peptide MHC-I binding, TAP binding and peptide cleavage probability. We will combine the resulting scores and apply them to existing genomic data. To produce the human libraries, we will develop new bioinformatics tools and merge them with existing tools. The result will be a score determining the probability of a peptide to be presented. We will apply this score to the human, mouse and to some viral genomes, in order to determine the self and non-self repertoire. The expected libraries will be validated through a collaboration with an experimental group. Each validated library will contain a list of peptides (from human, murine or viral source), which can be presented on a given MHC-I allele, accompanied by a score representing the "quality" of the peptide. This score will include the estimated binding affinity to the MHC binding groove, the TAP binding probability, the cleavage probability (either by the regular or the immuno-proteasome) and the average expression level of the gene carrying the peptide. Viral peptides will also include a score representing their maximal similarity to self peptides. The resulting validated libraries will be publicly accessible through a web based server. The accurate prediction of allele specific MHC-peptide interactions may enable us to manipulate the autoimmune response in organ specific autoimmune diseases, and the immune response against viruses. It may also help immunologist improve their ability to optimize MHC-matching for transplantation. The main applications of the libraries that will be developed in the current research program are: A) A peptide vaccine development methodology. We will use the viral peptide libraries in order to detect peptides from conserved viral genomic regions present in these libraries. We will use these peptides to produce genes sequences that code for proteins having the same immunological profile as the viruses, without its pathogenic effects. These peptides are good candidates for peptide vaccines in cases where an attenuated virus is too dangerous or unavailable. B) Analysis of the profiles presented to the immune system in autoimmune diseases (mainly IDDM and MS) and the link between MHC usage and autoimmunity. This part of the research will be done in colaboration with an experimental group studying the B and T cell repertoire in autoimmunity.