Applying Spatial Covariance to Understand Human Variation in Genetic Disease

应用空间协方差来了解遗传疾病的人类变异

基本信息

批准号：
10734426
负责人：
William Edward Balch
金额：
$ 45.25万
依托单位：
SCRIPPS RESEARCH INSTITUTE, THE
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-01 至 2027-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10734426
关键词：
Address Affect Amino Acid Sequence Automobile Driving Biological Biology Cell surface Cells Chemicals ClinVar Clinic Clinical Code Cystic Fibrosis Cystic Fibrosis Transmembrane Conductance Regulator Delta F508 mutation Disease Endoplasmic Reticulum Environment Event Evolution Foundations Functional disorder Genetic Genetic Diseases Genetic Variation Genome Genomics Genotype Goals Golgi Apparatus Health Human Human Biology Human Genetics Individual Inherited Link Logistics Machine Learning Membrane Membrane Protein Traffic Modeling Molecular Molecular Chaperones Mutation Paper Pathway interactions Phenotype Population Predisposition Process Protein Engineering Proteins Publications Reporting Resolution Role Severities Severity of illness Structure System Technology Therapeutic Time Uncertainty Validation Variant clinical phenotype computer framework cystic fibrosis patients design fitness functional improvement functional restoration gain of function genetic variant genomic variation healthspan human disease in silico loss of function misfolded protein new technology novel patient population phenome polypeptide programs protein folding protein function protein structure proteostasis response screening small molecule small molecule therapeutics spatial relationship statistics trafficking

项目摘要

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.

项目摘要/摘要：该提案的重点是基于我们不断努力将基因序列变异与导致变化联系起来使用前所未有的变异空间分析（VSP）在触发人类遗传疾病的蛋白质折叠中我们开创的方法。 VSP 是一种高斯过程 (GP) 回归机器学习方法，利用人类变异来为蛋白质折叠中负责基因型的每个残基分配功能驱动人类生物学的表型转化——一种普遍适用于任何蛋白质的新技术。 VSP 建立在空间协方差 (SCV) 的一般原理之上，它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来定义残基-残基使用变异捕获 (VarC) 驱动蛋白质结构功能的相互作用。我们关注囊性纤维化跨膜电导调节因子 (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胞吐折叠和运输的影响途径。了解影响蛋白质折叠设计的遗传变异如何通过蛋白质稳态折叠来管理和基于 COPII 的贩运途径，以及我们如何通过促进蛋白质来改善遗传疾病的功能通过小分子校正器折叠健身，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 伴侣/共伴侣蛋白质稳态系统的贡献无法正确管理引发疾病的自然发生的遗传变异，并且这些成分可以通过分子和化学方法调整其活性来重新调整。瞄准如图 2 所示，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，作为通过胞质将 CFTR 呈现给 COPII ER 输出机制的主调节器暴露“YKDAD”退出代码。我们假设 COPII 组件对 SCV 设定点的响应存在差异受遗传变异的影响而在个体中产生疾病。我们将确定遗传的影响每个步骤的变化指示 COPII 组件来了解那些负责的事件病理生理学。在目标 3 中，我们基于 GP 逻辑进一步假设变体 CFTR 多肽将对直接与折叠相互作用以恢复功能的新型校正器高度敏感。我们将利用 SCV- 基于“三角测量”的方法来识别直接影响 YKDAD 出口基序稳定性的小分子 F508del 和其他变体中存在缺陷，无法在计算机中识别影响 CF 治愈的化合物计算筛选和实验验证。目标 1-3 中概述的共同努力将使我们能够定义基于基因组的机制基础，以了解如何重新编程折叠以获得最佳适应度通过减少引发人类遗传疾病的变异的影响来个体化。