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: 8727050
• 负责人: Frank Alber
• 金额: $ 31.15万
• 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/8727050
• 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

Project Summary 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 two 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 cryo- electron tomograms - a prerequisite towards comprehensive visual proteomics. We will also develop methods to study the systems dynamics of protein interaction networks 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.

项目摘要 蛋白质组学和基因组学项目已经在细胞中产生了蛋白质的详细清单。 但是，对于这些蛋白质如何在空间和时间上排列的知识知之甚少 在细胞内。这种知识对于了解蛋白质如何贡献 活细胞的结构和功能。就像单词必须集中在 句子，段落和章节是有道理的，重要的蜂窝功能是 由蛋白质的结构化组件（或复合物）而不是个体进行 分子。通常，这些复合物包含数十或数百种蛋白质。这个建议 描述一组计算方法，这些方法将利用和整合几种 新兴的实验数据以发现蛋白质的结构和动力学 复合物，达到实现机械理解的最终目标 细胞。特别是，我们将通过两个层面的蛋白质组组织来表征 以下项目。 （1）我们将开发一种有效的计算方法来确定 通过同时拟合多个蛋白质复合物的结构 组件到冷冻电子显微镜图。 （2）我们将开发高级模式 在全细胞冷冻中发现和定位未知蛋白复合物的采矿方法 电子断层图 - 综合视觉蛋白质组学的先决条件。我们将 还开发了研究蛋白质相互作用网络系统动力学的方法 在现实的蜂窝环境中。有了这些工具，我们准备建模 蛋白质组的空间和时间组织。我们将自由提供软件 为科学界的所有方法的包装和源代码。