Applying Spatial Covariance to Understand Human Variation in Genetic Disease

项目概要/摘要： 这项建议的重点是基于我们正在进行的努力，以联系基因序列变异导致的变化 在蛋白质折叠触发人类遗传疾病使用前所未有的变异空间分析（VSP） 我们开创的方法。VSP是一种高斯过程（GP）回归机器学习方法， 利用人类变异来分配蛋白质折叠中负责基因型的每个残基的功能， 表型转化驱动人类生物学-一种普遍适用于任何蛋白质的新技术。 VSP是建立在空间协方差（SCV）的一般原理上的，SCV描述了基本协变 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 用指定的不确定性定义每个残基在遗传疾病中的作用，以定义残基-残基 使用变异捕获（VarC）驱动蛋白质结构功能的相互作用。我们专注于囊性纤维化 跨膜传导调节因子（CFTR），CF的致病因子，作为模型蛋白来了解 SCV/VarC关系决定了遗传变异对折叠和通过胞吐转运的影响 通路了解影响蛋白质折叠设计的遗传变异如何通过蛋白质稳定折叠来管理 以及基于COPII的运输途径，以及我们如何通过促进蛋白质合成来改善遗传疾病的功能， 折叠健身通过小分子校正器，我们提出了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Hsp 70和Hsp 90分子伴侣/共分子伴侣蛋白质稳定系统的贡献 对于自然发生的引发疾病的遗传变异的适当管理是不一致的-并且 这些组分可以通过分子和化学方法调节它们的活性来重新调谐。在Aim中 2，我们假设蛋白质稳态系统产生SCV定义的“设定点”。SCV设定点为 由选择的SCV簇组成，定义了蛋白质结构中的残基-残基空间关系， 作为CFTR通过细胞溶质转运到COPII ER输出机制的主要调节剂， 暴露了“YKDAD”退出代码。我们假设COPII成分对SCV设定点的反应不同 受到遗传变异的影响而在个体中产生疾病。我们将确定基因的影响 每个步骤的变化指示COPII组件，以了解负责 病理生理学在目的3中，我们进一步基于GP逻辑假设变体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剂高度响应。我们将使用一个SCV- 基于“三角测量”的方法来鉴定直接影响YKDAD退出基序稳定性的小分子 在F508 del和其他变体中存在缺陷，以通过计算机模拟鉴定影响CF治愈的化合物 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 定义一个基于基因组的机械基础，用于如何重新编程折叠以获得最佳适应性， 通过减少引发人类遗传疾病的变异的影响，

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.