Computational Methods Towards the Spatio-Temporal Organization of the Proteome

蛋白质组时空组织的计算方法

• 批准号: 8337795
• 负责人: Frank Alber
• 金额: $ 31.07万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-30 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8337795
• 关键词: Algorithms; Area; Atlases; Cell membrane; Cell physiology; Cells; Collaborations; Collection; Communities; Complex; Computer software; Computing Methodologies; Cryoelectron Microscopy; Data; Data Set; Disease; Electrons; Elements; Environment; Equipment and supply inventories; Escherichia coli; Genomics; Goals; Herpes Simplex Infections; Human; Imagery; Individual; Knowledge; Lead; Leptospira interrogans; Life; Maps; Membrane Proteins; Methods; Mining; Modeling; Molecular; Noise; Pattern; Pattern Recognition; Positioning Attribute; Protein Dynamics; Proteins; Proteome; Proteomics; Public Domains; Public Health; Recurrence; Research Personnel; Resolution; Role; Series; Signal Transduction; Source Code; Spatial Distribution; Structure; System; Time; Tomogram; Virion; Visual; density; electron tomography; insight; macromolecular assembly; novel; pathogen; programs; protein complex; protein distribution; protein structure; public health relevance; secretory protein; tool

DESCRIPTION (provided by applicant): Proteomics and genomics projects have yielded a detailed inventory of proteins in a cell. However, little is known about how these proteins are spatially and temporally arranged within the cell. Such knowledge is essential to understanding how proteins contribute to the structure and function of a living cell. Just as words must be assembled into sentences, paragraphs, and chapters to make sense, vital cellular functions are performed by structured assemblies (or complexes) of proteins rather than individual molecules. Often, these complexes comprise tens or hundreds of proteins. This proposal describes a set of computational methods that will exploit and integrate several kinds of emerging experimental data to uncover the structure and dynamics of protein complexes, toward the ultimate goal of achieving a mechanistic understanding of the cell. In particular, we will characterize proteome organization on three levels through the following projects. (1) We will develop an efficient computational method to determine the structure of individual protein complexes by simultaneously fitting multiple components to cryo-electron microscopy maps. (2) We will develop advanced pattern mining methods to discover and localize unknown protein complexes in whole-cell cryoelectron tomograms - a prerequisite towards comprehensive visual proteomics. (3) We will develop simulation methods to study the systems dynamics of protein interaction networks on biologically relevant time scales and within realistic cellular environments. With these tools, we are poised to model the spatial and temporal organizations of proteome. We will freely provide software packages and source code for all methods to the scientific community.

描述（由申请人提供）：蛋白质组学和基因组学项目已经产生了细胞中蛋白质的详细清单。然而，人们对这些蛋白质在细胞内的空间和时间排列方式知之甚少。这些知识对于理解蛋白质如何对活细胞的结构和功能做出贡献至关重要。就像单词必须组装成句子、段落和章节才有意义一样，重要的细胞功能是由蛋白质的结构化组装（或复合物）而不是单个分子来执行的。通常，这些复合物包含数十或数百种蛋白质。该提案描述了一套计算方法，将利用和整合几种新兴的实验数据来揭示蛋白质复合物的结构和动力学，最终目标是实现对细胞的机械理解。特别是，我们将通过以下项目在三个层面上表征蛋白质组组织。(1)我们将开发一种有效的计算方法，通过同时拟合多个组件到冷冻电子显微镜图来确定单个蛋白质复合物的结构。(2)我们将开发先进的模式挖掘方法，以发现和定位未知的蛋白质复合物在全细胞冷冻电子断层扫描-全面的可视化蛋白质组学的先决条件。(3)我们将开发模拟方法来研究蛋白质相互作用网络在生物相关的时间尺度和现实的细胞环境中的系统动力学。有了这些工具，我们准备对蛋白质组的空间和时间组织进行建模。我们将免费向科学界提供所有方法的软件包和源代码。