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

• 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
• 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

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.

项目总结/文摘: