Consortia for High-Throughput-Enabled Structural Biology Partnerships (U01)

高通量结构生物学合作联盟 (U01)

基本信息

批准号：
8153580
负责人：
STANLEY G NATHENSON
金额：
$ 97.32万
依托单位：
ALBERT EINSTEIN COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-09-30 至 2015-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8153580
关键词：
Adhesives Affinity Amino Acid Sequence Animal Disease Models Animal Model Animals Area Autoimmune Diseases Autoimmunity Biochemical Biological Biological Assay Biological Models Biological Process Biology CD4 Positive T Lymphocytes Cell surface Cells Commit Communicable Diseases Complement Complex Cytotoxic T-Lymphocytes Evolution Family Family member Future Generations Goals Helper-Inducer T-Lymphocyte Immune Immune Targeting Immune response Immunity Immunologic Receptors Immunologist In Vitro Individual Informatics Knock-in Mouse Lead Ligands Malignant Neoplasms Memory Molecular Natural Immunity Property Proteins Reagent Regulation Regulatory T-Lymphocyte Research Infrastructure Resolution Series Signal Transduction Specificity Structural Biologist Structure Structure-Activity Relationship Subgroup T-Lymphocyte Therapeutic Work adaptive immunity base design expectation immune function immunoregulation in vivo insight mouse model mutant novel novel therapeutics protein complex receptor research study structural biology tool

项目摘要

The Immune Function Network (IFN), a consortium of immunologists, geneticists, computational biochemists, and high throughput structural biologists, is committed to the coordinated structural, in vitro biochemical and in vivo ftinctional analyses of the secreted molecules and ectodomains of cell surface molecules that control adaptive and innate immunity. These molecules are validated targets for immime-based therapies to treat a wide range of autoimmune diseases, infectious diseases and cancers, and are indeed therapeutics in their own right. The IFN, subscribes to a series of underlying principles: 1) target selection supports hypothesis-driven structural biology by identifying unique primary amino acid sequence signatures that predict unique structural features, which are in turn responsible for unique biological function; 2) the high resolution structures of these molecules are exceptionally revealing as they inform on oligomeric state, valency, specificity and general architectural features, all of which are fundamental mechanistic contributors to immune function; 3) these structures can be readily exploited by biochemical and computational approaches to guide the generation of molecules with specifically altered biochemical and biophysical properties; 4) these "surgically-defined" mutants represent novel reagents that will lead to new mechanistic insights in in vitro cellbased assays and in vivo animal models of disease; 5) the molecules predicted to be most informative will guide the generation of knock-in mouse models to provide in vivo structure-function relationships for innate and adaptive immunity. This "Atoms-to-Animals" approach represents the next step in the evolution of Structural Biology as it maximally leverages structural information and provides a comprehensive and powerful paradigm for the study of normal, pathological, and therapeutic immune responses.

免疫功能网络（IFN），免疫学家，遗传学家，计算生物化学家的财团和高吞吐量结构生物学家致力于协调的结构，体外生化和体内控制适应性和先天物的细胞表面分子的分泌分子和胞外域的分析免疫。这些分子是验证的基于豁免的疗法的靶标，以治疗多种自身免疫性疾病，传染病和癌症，确实是治疗疾病。 IFN，订阅一个系列基本原则：1）目标选择通过识别独特的主要原理来支持假设驱动的结构生物学预测独特结构特征的氨基酸序列特征，这反过来构成独特生物功能； 2）这些分子的高分辨率结构在告知时非常揭示寡聚状态，价值，特异性和一般体系结构特征，所有这些都是基本的机械免疫功能的贡献者； 3）这些结构可以通过生化和计算很容易利用指导分子具有特异性改变的生化和生物物理特性的方法； 4）这些“手术定义”的突变体代表了新型试剂，这些试剂将导致基于体外细胞的新机械见解测定和体内动物模型的疾病模型； 5）预测最有用的分子将指导生成敲入鼠标模型，以提供天生和适应性的体内结构功能关系免疫。这种“原子对动物”的方法代表了结构生物学演变的下一步最大程度地利用结构信息，并为研究提供了全面而有力的范式正常，病理和治疗性免疫反应。