Applying Spatial Covariance to Understand Human Variation in Genetic Disease

项目摘要/摘要： 这项提案的重点是基于我们正在进行的将导致变化的基因序列变异联系起来的努力 在触发人类遗传病的蛋白质折叠中使用前所未有的变异空间图谱(VSP) 这是我们首创的方法。VSP是一种高斯过程(GP)回归机器学习方法 利用人类变异来为导致该基因的蛋白质折叠中的每个残基分配功能 表型转化推动人类生物学--一种普遍适用于任何蛋白质的新技术。 VSP建立在描述基本协方差的空间协方差(SCV)的一般原理上 决定蛋白质折叠和功能的所有残基之间的关系。这些空间关系使我们能够 用指定的不确定度定义每个残留物在遗传病中的作用，以确定残留物-残留物 使用变异捕获(VARC)来驱动蛋白质结构中的功能的相互作用。我们关注的是囊性纤维化 以跨膜电导调节因子(CFTR)为模型蛋白来理解CF SCV/VARC关系决定了遗传变异对通过胞外折叠和运输的影响 路径。了解基因变异如何通过蛋白质平衡折叠来影响蛋白质折叠设计 和基于COPII的运输途径，以及我们如何通过促进蛋白质来改善遗传病的功能 通过小分子矫正器折叠健身，我们提出3个目标。在目标1中，我们将利用SCV关系来 剖析我们假设的Hsp70和Hsp90分子伴侣/共分子伴侣蛋白平衡系统的作用 对自然发生的引发疾病的基因变异进行适当的管理是错位的--而且 这些成分可以通过分子和化学方法调整它们的活性来重新调整。在AIM 2，我们假设蛋白质平衡系统产生SCV定义的‘设定点’。SCV设定值为 由选定的SCV簇组成，定义了蛋白质结构中的残基-残基空间关系 作为主调节器，通过胞浆向COPII ER出口机械提交CFTR 已暴露‘YKDAD’退出代码。我们假设COPII组件对SCV设定点有不同的响应 受基因变异的影响而在个体中产生疾病。我们将确定基因的影响 指示COPII程序集理解这些事件的每个步骤的变体 病理生理学。在目标3中，我们基于GP物流进一步假设，变异的CFTR多肽将是 对直接与折叠相互作用以恢复功能的新型校正器具有高度响应性。我们将利用SCV- 基于“三角”的方法识别直接影响YKDAD退出基序稳定性的小分子 F508del和其他变体中存在缺陷，无法识别影响硅胶中使用的CF固化的化合物 计算筛选和实验验证。目标1-3中概述的综合努力将使我们能够 定义基于基因组的机制基础，以确定折叠如何重新编程以实现最优适应 通过减少引发人类遗传病的变异的影响。

Project Summary/Abstract: The focus of this proposal is based on our ongoing efforts to link genetic sequence variation leading to changes in the protein fold triggering human genetic disease using an unprecedented variation spatial profiling (VSP) approach we have pioneered. VSP is a Gaussian process (GP) regression machine learning approach that utilizes human variation to assign function for each residue in the protein fold responsible for the genotype to phenotype transformation driving human biology- a new technology that is universal in application to any protein. VSP is built on the general principle of spatial covariance (SCV) which describes fundamental covariant relationships between all residues dictating the protein fold and function. These spatial relationships allow us to define with assigned uncertainty the role of each residue in genetic disease to define the residue-residue interactions that drive function in protein structure using variation capture (VarC). We focus on the cystic fibrosis transmembrane conductance regulator (CFTR), the causative agent of CF, as a model protein to understand SCV/VarC relationships dictating the impact of genetic variation on folding and trafficking through the exocytic pathway. To understand how genetic variation impacting protein fold design is managed by proteostasis folding and COPII based trafficking pathways, and how we can improve function in genetic disease by promoting protein fold fitness through small molecule correctors, we propose 3 goals. In Aim 1, we will utilize SCV relationships to dissect the contribution of the Hsp70 and Hsp90 chaperone/co-chaperone proteostasis systems we hypothesize are misaligned for the proper management of naturally occurring genetic variants triggering disease- and that these components can be retuned by adjusting their activity through molecular and chemical approaches. In Aim 2, we hypothesize that the proteostasis system generates SCV-defined 'set-points'. SCV set-points are composed of select clusters of SCV defined residue-residue spatial relationships in the protein structure that serve as master regulators for presentation of CFTR to the COPII ER export machinery through a cytosolic exposed 'YKDAD' exit code. We hypothesize that COPII components differentially respond to SCV set-points impacted by genetic variation to generate disease in the individual. We will determine the impact of genetic variation for each of the steps dictating COPII assembly to understand those events responsible for pathophysiology. In Aim 3, we further hypothesize based on GP logistics that variant CFTR polypeptides will be highly responsive to novel correctors that directly interact with the fold to restore function. We will utilize an SCV- based 'triangulation' approach to identify small molecules that directly impact the stability of the YKDAD exit motif defective in F508del and other variants to identify compounds that affect a cure for CF using in silico computational screening and experimental validation. The combined efforts outlined in Aims 1-3 will allow us to define a genome based mechanistic foundation for how the fold can be reprogrammed for optimal fitness in the individual by reducing the impact of variation triggering human genetic disease.