Linking Collagen Genotypes to Molecular Phenotypes

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Collagen is the most abundant protein in humans, and mutations in collagen can lead to death or disease. The ways in which individual mutations affect collagen structure/function are poorly understood. Collagen is a fibrillar protein, and thus many of the principles elucidated for the study of globular proteins are not immediately applicable in investigating the relationship between its structure and function. We now have an opportunity to use genomic technologies to survey the variation in key collagen genes throughout the human population, link the discovered polymorphisms to their structural effects, and develop an understanding of the mechanism of collagenous disorders. This work will also provide a foundation for engineering new treatments and the designing of novel collagen-like biomaterials. The long-term goal of this proposal is to determine the chemical, physical and structural properties of biopolymers in the context of natural sequence variation. We will take advantage of our joint capabilities in genomics and structural biology to pursue the following specific aims: (1) to identify Single Nucleotide Polymorphisms (SNPs) in an ethnically diverse population to determine the background genetic variation across the collagen genes COL1A1, COL1A2, COL2A1 and COL3A1 and then determine the distribution of SNPs in individuals with collagen disorders; (2) to model collagen-like peptides and full-length Type I and Type III collagen triple helices to determine the structural and energetic effects resulting from single point glycine substitutions in the collagen-like peptides and genetic variation in the full-length collagen models.; (3) to develop analysis tools that incorporate function and phenotypes observed in molecular dynamics simulations to construct a working model of type I collagen for OI-associated mutations; and, (4) to develop methods to simulate the folding and unfolding of native and mutant collagen-like peptides to determine the effects induced by mutations with phenotypic consequences.