European Molecular Biology Laboratory, Meyerhofstr. 1, 69117 Heidelberg, Germany.
J Struct Biol. 2011 Mar;173(3):483-96. doi: 10.1016/j.jsb.2010.11.011. Epub 2010 Nov 19.
To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and spatial distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome's spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome's organization into a spatially explicit, predictive model of cellular processes.
为了增进我们对细胞过程（如细胞信号转导和分裂）的现有认识，我们需要了解蛋白质组在不同组织层次上的空间和时间组织。这些层次涵盖了广泛的长度和时间尺度：从推断其分子功能的大分子的原子结构，到其在细胞中的定量描述及其丰度和空间分布。新兴的实验新技术极大地增加了对活细胞中分子组织的这种空间信息的可获得性。这篇综述涉及三个领域，这些领域极大地促进了我们对蛋白质组的空间和时间组织的理解：首先，用于确定单个大分子组装体结构的方法，特别是将原子结构拟合到电子显微镜技术生成的密度图中；其次，使用冷冻电子断层扫描技术结合计算图像处理来可视化这些复合物在细胞环境中的空间分布的研究；以及第三，用于蛋白质组动态组织的空间建模的方法，特别是用于模拟蛋白质和复合物在拥挤的细胞内液中的反应和扩散的那些方法。长期目标是将有关蛋白质组组织的各种数据整合到具有空间显式的、对细胞过程进行预测的模型中。
