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

免疫功能网络（IFN）是一个由免疫学家、遗传学家、计算生物化学家和高级生物学家组成的联盟。 通过结构生物学家，致力于协调的结构，体外生化和体内功能 分析控制适应性和先天性的细胞表面分子的分泌分子和胞外域 免疫力这些分子是基于免疫印迹的疗法的经验证的靶点，以治疗广泛的自身免疫性疾病。 疾病、传染病和癌症，它们本身确实是治疗方法。IFN订阅了一系列 基本原则：1）靶标选择通过识别独特的初级结构， 氨基酸序列特征，预测独特的结构特征，这反过来又负责独特的 生物学功能; 2）这些分子的高分辨率结构非常具有启发性，因为它们提供了 低聚状态、化合价、特异性和一般结构特征，所有这些都是基本的机械性 贡献者的免疫功能; 3）这些结构可以很容易地利用生物化学和计算 引导具有特异性改变的生物化学和生物物理特性的分子的产生的方法; 4） 这些“化学定义的”突变体代表了新的试剂， 5）被预测为最具信息性的分子将指导疾病的诊断和治疗。 产生敲入小鼠模型以提供先天性和适应性的体内结构-功能关系 免疫力这种“原子到动物”的方法代表了结构生物学进化的下一步，因为它 最大限度地利用结构信息，为研究提供全面而强大的范式 正常、病理和治疗性免疫应答。

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.