Modeling a cellular protein homeostasis network

细胞蛋白质稳态网络建模

基本信息

批准号：
8730190
负责人：
LILA M GIERASCH
金额：
$ 40.87万
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/8730190
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 Differential Equation Disease Drug Industry Engineering Enzymes 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稳态（蛋白质量）网络的计算模型，包括蛋白质合成，降解，折叠稳定性，聚集以及竞争/合作的伴侣陪伴系统。该项目是Lila Gierasch（马萨诸塞州阿默斯特大学）与埃文·鲍尔斯（Scripps Research Institute）之间的合作。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蛋白质的“健康”的影响，通常是大肠杆菌细胞质的蛋白质组。 Foldeco始于当前对机制，生化回路和参数的广泛了解，并允许在各种条件下生成有关大规模，复杂蛋白质折叠网络的假设。我们现在提出：（1）推进fordeco，以便更好地捕获大肠杆菌蛋白质组的全部复杂性以及生理过程，例如在大肠杆菌中蛋白质的热浪调节反应，在大肠杆菌中起作用；（2）在生理学下实验询问大肠杆菌蛋白抑制剂条件以测试并最终改善Foldeco模型。作为我们工作的一部分，我们将通过扰动单个蛋白质的扰动，蛋白技术网络对这种扰动的应对程度以及某些蛋白质是否特别容易受到这种扰动的影响来解决蛋白质组上的负担。我们将继续通过基于Web的界面使Foldeco模型免费为广泛社区提供。我们已经在第一代版本中拥有foldeco代码，并且对代码的预测进行了几项实验测试。由于伴侣网络在所有生物体中都是保守的，因此简单模型生物体中的这项工作将提供对较高生物体中蛋白质稳态的见解，并有助于开发用于蛋白质错误折叠疾病的治疗策略。此外，Foldeco将有益于有效产生功能蛋白的生物技术和制药行业至关重要。如果成功，这项工作将广泛地提高我们理解在健康和疾病中起着关键作用的复杂电路的能力。