Webb Benjamin, Lasker Keren, Velázquez-Muriel Javier, Schneidman-Duhovny Dina, Pellarin Riccardo, Bonomi Massimiliano, Greenberg Charles, Raveh Barak, Tjioe Elina, Russel Daniel, Sali Andrej
Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quanstitative Biosciences (QB3), University of California San Francisco, San Francisco, CA, USA.
Methods Mol Biol. 2014;1091:277-95. doi: 10.1007/978-1-62703-691-7_20.
To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resolution structural characterization of these assemblies is frequently beyond the reach of current experimental methods, such as X-ray crystallography, NMR spectroscopy, electron microscopy, footprinting, chemical cross-linking, FRET spectroscopy, small angle X-ray scattering, and proteomics. However, the information garnered from different methods can be combined and used to build models of the assembly structures that are consistent with all of the available datasets, and therefore more accurate, precise, and complete. Here, we describe a protocol for this integration, whereby the information is converted to a set of spatial restraints and a variety of optimization procedures can be used to generate models that satisfy the restraints as well as possible. These generated models can then potentially inform about the precision and accuracy of structure determination, the accuracy of the input datasets, and further data generation. We also demonstrate the Integrative Modeling Platform (IMP) software, which provides the necessary computational framework to implement this protocol, and several applications for specific use cases.
为了理解活细胞的运作机制，我们需要对构成细胞的蛋白质组装体进行表征（例如核糖体、26S蛋白酶体和核孔复合体）。目前的实验方法，如X射线晶体学、核磁共振光谱、电子显微镜、足迹法、化学交联、荧光共振能量转移光谱、小角X射线散射和蛋白质组学，往往难以对这些组装体进行可靠的高分辨率结构表征。然而，从不同方法获得的信息可以结合起来，用于构建与所有可用数据集一致的组装体结构模型，从而更准确、精确和完整。在这里，我们描述了一种整合方案，通过该方案，信息被转换为一组空间约束条件，并且可以使用各种优化程序来生成尽可能满足这些约束条件的模型。这些生成的模型随后有可能为结构测定的精度和准确性、输入数据集的准确性以及进一步的数据生成提供信息。我们还展示了整合建模平台（IMP）软件，它提供了实施该方案所需的计算框架，以及针对特定用例的几个应用程序。
