STRUCTURE DETERMIN OF PROTEIN ASSEMBLIES BY SATISFACTION OF SPATIAL RESTRAINTS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 为了理解细胞，我们需要确定 大分子组装体，其中许多由数十到数百个组分组成。 大量的实验数据可以用来表征 从原子结构到组件的多个分辨率级别的组装 配置。最大限度地提高完整性、分辨率、准确度、精确度和效率 对于结构确定，需要一种计算方法，该方法可以 使用来自各种实验方法的空间信息。我们建议这样做 一种方法，由其三个主要组件定义： 该组件是由来自实验的空间约束组成的计分函数 数据以及生成符合以下条件的结构的优化方法 数据。我们通过确定456的配置来说明该方法 面包酵母核孔复合体中的蛋白质。已经出版了描述这种方法的一章。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. To understand the cell, we need to determine the structures of macromolecular assemblies, many of which consist of tens to hundreds of components. A great variety of experimental data can be used to characterize the assemblies at several levels of resolution, from atomic structures to component configurations. To maximize completeness, resolution, accuracy, precision and efficiency of the structure determination, a computational approach is needed that can use spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. We illustrate the approach by determining the configuration of the 456 proteins in the nuclear pore complex from Baker's yeast. A chapter describing this approach has been published.