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Modeling a cellular protein homeostasis network

细胞蛋白质稳态网络建模

基本信息

批准号：
8560963
负责人：
LILA M GIERASCH
金额：
$ 42.35万
依托单位：
UNIVERSITY OF MASSACHUSETTS AMHERST
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-05 至 2017-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8560963
关键词：
Address Affect Aging Alzheimer&apos s Disease Animal Model Behavior Biochemical Cell Aging Cell physiology Cells Code Collaborations Communities Complex Computer Simulation Coupled Cystic Fibrosis Cytoplasm Data Disease Drug Industry Engineering Enzymes Equation Equilibrium Escherichia coli Escherichia coli Proteins Failure Generations Growth Health Heat shock proteins Heat-Shock Response High temperature of physical object Homeostasis Homologous Gene In Vitro Individual Knowledge Literature Longevity Malignant Neoplasms Massachusetts Measures Modeling Molecular Chaperones Mutate Non-Insulin-Dependent Diabetes Mellitus Organism Outcome Parkinson Disease Physiological Physiological Processes Play Process Property Protein Biosynthesis Proteins Proteome Protocols documentation Quality Control Reaction Research Research Institute Research Personnel Role Set protein Stress System Testing Translations Universities Work biochemical model biological adaptation to stress cell age coping improved in vivo insight member protein folding protein misfolding public health relevance research study response therapeutic development tool web based interface

项目摘要

DESCRIPTION (provided by applicant): We propose to develop a computational model of a complete cellular protein homeostasis (proteostasis) network, including protein synthesis, degradation, folding stability, aggregation, and competing/cooperating chaperoning systems. This project is a collaboration between Lila Gierasch (University of Massachusetts Amherst) and Evan Powers (The Scripps Research Institute). Our model, called FoldEco, aims to describe the balance of biochemical and physical aspects of folding and aggregation, and their impact on the "health" of the proteins in proteomes in general, and here the proteome of the E. coli cytoplasm, in particular. FoldEco begins with the current extensive knowledge of mechanisms, biochemical circuits, and parameters, and allows for the generation of hypotheses about large-scale, complex protein folding networks under various conditions. We propose now: (1) to advance FoldEco so that it better captures the full complexity of the E. coli proteome as well as physiological processes such as the heat-shock regulatory response that play a role in proteostasis in E. coli; (2) to experimentally interrogate E. coli proteostasis under physiological conditions in order to test and ultimately improve the FoldEco model. As part of our work, we will be addressing the burden placed on the proteome by perturbation of individual proteins, how well the proteostasis network copes with such perturbations, and whether some proteins are particularly vulnerable to such perturbations. We will continue to make the FoldEco model freely available to the broad community through a web-based interface. We already have the FoldEco code in a first generation version and several experimental tests of predictions of the code. Because chaperone networks are conserved across all organisms, this work in the simple model organism, E. coli, will provide insight into protein homeostasis in higher organisms and potentially assist in the development of therapeutic strategies for protein misfolding diseases. Additionally, FoldEco will benefit the biotechnological and pharmaceutical industries where the need to produce functional proteins efficiently is critical. If successful, this work will broadly advance our ability to comprehend complex circuits that play critical roles in health and disease.

描述（由申请人提供）：我们建议开发一个完整的细胞蛋白质稳态（proteostasis）网络的计算模型，包括蛋白质合成，降解，折叠稳定性，聚集和竞争/合作伴侣系统。这个项目是Lila Gierasch（马萨诸塞大学阿姆赫斯特分校）和Evan Powers（斯克里普斯研究所）的合作项目。我们的模型称为FoldEco，旨在描述折叠和聚集的生化和物理方面的平衡，以及它们对蛋白质组中蛋白质的“健康”的影响，特别是大肠杆菌细胞质的蛋白质组。FoldEco从目前广泛的机制，生化电路和参数知识开始，并允许在各种条件下产生关于大规模，复杂蛋白质折叠网络的假设。我们现在建议：(1)推进FoldEco，使其能够更好地捕捉大肠杆菌蛋白质组的全部复杂性以及在大肠杆菌蛋白质停滞中发挥作用的热休克调节反应等生理过程；(2)实验探讨大肠杆菌在生理条件下的蛋白酶抑制作用