Semantic integration of protein epitopes and functional features for infectious and autoimmune disease knowledge discovery

用于传染病和自身免疫性疾病知识发现的蛋白质表位和功能特征的语义整合

• 批准号: 10442059
• 负责人: DARREN A NATALE
• 金额: $ 48.14万
• 依托单位: GEORGETOWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10442059
• 关键词: Address; Affect; Allergic Disease; Amino Acid Sequence; Animal Model; Animals; Antibodies; Antigens; Area; Autoimmune Diseases; Autoimmunity; Awareness; Base Sequence; Catalogs; Clinical; Communicable Diseases; Communities; Consumption; Cross Reactions; Data; Databases; Detection; Disease; Disease model; Distance Learning; Educational workshop; Ensure; Environment; Epitopes; Funding; Generations; Genetic Variation; Goals; Growth; Homologous Gene; Homologous Protein; Human; Human Genetics; Hypersensitivity; Immune; Immune Evasion; Immune response; Immune system; Immunologics; Immunology; Infection; Insulin-Dependent Diabetes Mellitus; Knowledge; Knowledge Discovery; Link; Lupus; Maps; Monitor; Multiple Sclerosis; National Institute of Allergy and Infectious Disease; Ontology; Organism; Orthologous Gene; Pharmaceutical Preparations; Play; Post-Translational Protein Processing; Proteins; Publications; Research; Research Personnel; Resource Informatics; Resources; Role; Sampling; Semantics; Sequence Homologs; Site; T-Cell Receptor; T-Lymphocyte Epitopes; Transplantation; Variant; Visualization; Visualization software; Work; base; community engagement; cross reactivity; data exchange; data visualization; druggable target; fighting; genetic variant; human disease; improved; information display; insight; interest; knowledge graph; meetings; nonhuman primate; novel; outreach; pathogen; prevent; protein protein interaction; social media; tool; translational scientist; usability; web site

PROJECT SUMMARY Immune epitopes--the portions of an antigen that are recognized by antibodies and T-cell receptors--are key to understanding healthy and abnormal immune responses. The Immune Epitope Database (IEDB) is a freely available resource funded by the National Institute of Allergy and Infectious Diseases (NIAID) that catalogs experimental data on more than one million antibody and T cell epitopes studied in humans, non-human primates, and other animal species in the context of infectious disease, allergy, autoimmunity and transplantation. As well, there is a wealth of information captured in other biomedical databases that could potentially be applied to immunological research. The goal of this work is to integrate immune epitope information from IEDB with the wealth of additional biomedical data in humans and model organisms, thereby enabling novel opportunities for hypothesis generation and discovery. We will seamlessly connect epitopes to the protein information in UniProtKB, which contains rich functional annotation and the means to display protein sequence features, and the Protein Ontology (PRO), which provides orthology information and the explicit representation of proteoforms. We will make further connections to resources specializing in protein post-translational modifications (PTMs), protein-protein interactions, human genetic variation, diseases, and drugs. Display of this information in the UniProt ProtVista environment and via the IEDB website will make it easily accessible to the large community of immunology and disease researchers. Our work will enable novel queries of high interest to translational researchers, such as: (1) What PTMs and/or genetic variants overlap with an epitope of interest? Identification of such overlaps can provide insight into factors that affect auto-antigenicity or immune evasion by pathogens; (2) Is a human epitope of interest found in orthologous/homologous proteins in model organisms or vice-versa? This will allow researchers interested in human disease to fully exploit knowledge derived from model organisms, and conversely, improve disease models in non-human organisms. It will also enable identification of potential cross-reactivities within and across organisms; and (3) Are there any druggable targets among the proteins that interact with autoantigenic proteins associated with an autoimmune disease of interest? This work entails the following specific aims: (i) Aim 1. Data exchange: Guided by use cases, we will connect epitopes within IEDB to data from PRO, UniProt, and other informatics resources; (ii) Aim 2. Information access: Guided by user input, we will enhance navigation, data visualization, and application interfaces at each resource and create connections between them; and (iii) Aim 3. Community engagement: We will build community awareness of the connected resources and ensure that the needs of stakeholders are reflected. This collaborative effort among multiple major resources will overcome barriers to consumption of IEDB data, thereby supporting inquiry into the role of the immune system in human disease.

项目摘要 免疫表位 - 抗体和T细胞受体识别的抗原部分 - 是关键 了解健康和异常的免疫反应。免疫表位数据库（IEDB）是自由的 由国家过敏和传染病研究所（NIAID）资助的可用资源 关于在人类，非人类研究的超过一百万抗体和T细胞表位的实验数据 在传染病，过敏，自身免疫性和 移植。同样，在其他生物医学数据库中也捕获了大量信息 可能应用于免疫研究。这项工作的目的是整合免疫表位 IEDB的信息具有人类和模型生物的大量其他生物医学数据，从而 为假设产生和发现带来新的机会。我们将无缝将表位连接到 Uniprotkb中的蛋白质信息，其中包含丰富的功能注释和显示的手段 蛋白质序列特征和蛋白质本体论（Pro），该蛋白质特征（Pro）提供了矫正信息和 明确表示蛋白质成型。我们将与专门从事蛋白质的资源建立进一步的联系 翻译后修饰（PTMS），蛋白质 - 蛋白质相互作用，人遗传变异，疾病和 毒品。在Uniprot Protvista环境和IEDB网站上显示此信息 庞大的免疫学和疾病研究人员很容易获得。我们的作品将使小说 对转化研究人员的兴趣高度查询，例如：（1）什么PTM和/或遗传变体重叠 有兴趣的表位吗？识别这种重叠可以提供对影响因素的洞察力 病原体自身抗原性或免疫逃避； （2）是在 模型生物或反之亦然的派/同源蛋白？这将使研究人员感兴趣 人类疾病以完全利用来自模型生物的知识，相反，改善疾病 非人类生物的模型。它还将识别内部潜在的交叉反应性 跨生物体； （3）与自身抗原相互作用的蛋白质中是否有任何可药的靶标 与感兴趣的自身免疫性疾病有关的蛋白质？这项工作需要以下特定目的：（i） 目标1。数据交换：在用例引导下，我们将IEDB中的表位与Pro，Uniprot，Uniprot， 和其他信息学资源； （ii）目标2。信息访问：在用户输入的指导下，我们将增强 在每个资源处导航，数据可视化和应用程序接口，并在之间创建连接 他们; （iii）目标3。社区参与：我们将建立社区对互联资源的认识 并确保反映利益相关者的需求。多个专业之间的合作努力 资源将克服消费IEDB数据的障碍，从而支持探究对该角色的作用 人类疾病中的免疫系统。