Computational Methods Towards the Spatio-Temporal Organization of the Proteome

项目摘要 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空间和时间上是如何排列的知之甚少。 在细胞内。这些知识对于理解蛋白质如何对 活细胞的结构和功能。就像单词必须被组合成 句子、段落和章节要有意义，关键的细胞功能是 由蛋白质的结构组合(或复合体)执行，而不是单独执行 分子。通常，这些复合体由数十或数百种蛋白质组成。这项建议 描述了一组计算方法，这些方法将利用和集成几种 新出现的实验数据揭示蛋白质的结构和动力学 最终目标是从机械的角度理解 手机。特别是，我们将在两个水平上表征蛋白质组组织 以下是项目。(1)我们将开发一种高效的计算方法来确定 同时拟合多个蛋白质复合体的结构 低温电子显微镜图谱上的成分。(二)发展先进格局 发现和定位全细胞低温中未知蛋白质复合体的挖掘方法 电子断层扫描--全面视觉蛋白质组学的先决条件。我们会 还开发了研究蛋白质相互作用网络的系统动力学的方法 在现实的蜂窝环境中。有了这些工具，我们就可以为 蛋白质组的时空组织。我们将免费提供软件 向科学界提供所有方法的包和源代码。

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.