Computational methods to enable construcution of 3D models of protein complexes by integrating mass spectrometry and biochemical data

通过整合质谱和生化数据构建蛋白质复合物 3D 模型的计算方法

• 批准号: BB/G000360/1
• 负责人: Carol Robinson
• 金额: $ 12.73万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FG000360%2F1
• 关键词: Computational; methods; enable; construcution; 3D

Proteomic studies have yielded detailed lists of proteins but relatively little is known of their interactions and of their spatial arrangement in functional complexes. This gap is being bridged by complementing traditional biochemical and biophysical methods with emerging experimental approaches such as mass spectrometry of intact complexes and their constituents. To exploit this complementary experimental information, integrative computational approaches are required. Eventually we anticipate that these will provide molecular architectures and even atomic models of many protein complexes. Our mass spectrometry approach is typically to begin by measuring the mass of the isolated, intact assembly of proteins that make up the complex. In order to generate data on the connectivity and identity of the components within this complex, we measure the mass of the complex after both partial and complete disruption to observe subcomplexes and subunits of the intact complex respectively. This dataset is used to form the foundation of a contact map of the protein complex (termed a 2-D map). To create a 3-D model of the complex, we plan to incorporate ion mobility (IM) mass spectrometry to measure the size of the complex, along with all of the subcomplexes and components used to generate our 2-D map. While mass spectrometry methods for analyzing protein complexes are becoming well-established, computational approaches for data analysis are lagging seriously behind. To date, we have developed several pilot algorithms to approach the analysis of mass spectrometry data for protein complexes. For example, in the case of 2-D map generation, we currently use a simple network algorithm to find the shortest path that connects all subunit interactions determined in this way. This approach, while acceptable for very simple protein complexes, has serious limitations when we attempt to apply the algorithm to more complicated protein complexes with a high degree of modularity. To overcome this and other limitations we will develop a more sophisticated computer package capable of dealing with a variety of complexes, other than just globular-compact ones and able to incorporate data from a variety of methods including the shape of the individual subcomplexes.

蛋白质组学研究已经得出了蛋白质的详细清单，但对它们之间的相互作用和它们在功能复合体中的空间排列知之甚少。这一差距正在通过补充传统的生化和生物物理方法与新兴的实验方法来弥补，例如对完整的络合物及其成分进行质谱分析。为了利用这种互补的实验信息，需要综合的计算方法。最终，我们预计这些将提供许多蛋白质复合体的分子结构甚至原子模型。我们的质谱学方法通常是从测量组成复合体的孤立的、完整的蛋白质组装的质量开始。为了产生关于该复合体中各组分的连接性和身份的数据，我们测量了部分和完全破坏后的复合体的质量，以分别观察亚复合体和完整复合体的亚单位。这个数据集被用来形成蛋白质复合体的联系地图(称为二维地图)的基础。为了创建复合体的3-D模型，我们计划结合离子迁移率(IM)质谱仪来测量复合体的大小，以及用于生成我们的2-D地图的所有子复合体和组件。虽然分析蛋白质复合体的质谱学方法正在变得成熟，但用于数据分析的计算方法严重落后。到目前为止，我们已经开发了几个试点算法来接近蛋白质复合体的质谱分析数据。例如，在二维地图生成的情况下，我们目前使用一种简单的网络算法来找到连接以这种方式确定的所有子单元相互作用的最短路径。虽然这种方法对于非常简单的蛋白质复合体是可以接受的，但当我们试图将该算法应用于具有高度模块化程度的更复杂的蛋白质复合体时，它有严重的局限性。为了克服这一限制和其他限制，我们将开发一种更复杂的计算机程序包，能够处理各种复合体，而不仅仅是球形致密的复合体，并能够合并来自各种方法的数据，包括单个亚复合体的形状。

项目成果

Integrating Ion Mobility Mass Spectrometry with Molecular Modelling to Determine the Architecture of Multiprotein Complexes

• DOI: 10.1371/journal.pone.0012080
• 发表时间: 2010-08-10
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Politis, Argyris;Park, Ah Young;Robinson, Carol V.
• 通讯作者: Robinson, Carol V.