High Resolution in Single Particle Reconstruction

描述（由申请人提供）：在本次更新申请中，重点将是开发稳健的单颗粒冷冻EM分析方法，该方法从一开始就包含结果的统计验证。我们将集中在三个具体领域：（1）2-D图像对齐，（2）从头计算结构测定，和（3）定量描述的大分子构象变异性的基础上的数据存储方法。在（1）中，基于最大似然（ML）范例的新颖的2-D图像对准方法将利用期望最大化算法并结合精确的图像形成模型。该方法的可行性需要良好的计算效率，这将是通过跨越的角度参数的似然函数在一个有限的集合，在协议的典型EM数据的属性。我们将能够通过在傅立叶谐波基础上使用滤波来对图像数据的衰减引起的模糊进行建模，从而优化所提出的方法的性能。我们还建议使用从ML获得的对准参数协方差矩阵的特征分析，直接从对准信息中对图像进行分类。在（2）中，我们将通过引入额外的差异项来大大提高以前开发的基于公共线的方法的性能和可靠性，这些差异项是从考虑相交傅立叶平面之间的二维重叠而来的。结合改进的比对算法，该方法将产生用于生成初始冷冻EM结构的稳健方法，该方法将克服由于低信噪比和数据的结构异质性而导致的当前限制。在（3）中，一种新的数据重建方法，旨在克服由cryo-EM数据集中投影的强各向异性分布引起的限制，将允许用于3-D重建的方差和协方差估计的自动化。通过数据重建生成的大体积集的本征分析将用于计算（直接从图像数据）描述大分子组装体的构象模式的本征向量。通过这种特征向量分析确定的数据子集计算的结构将提供更高分辨率的构象相关的分子功能的研究模型。而不是渐进式的改进，我们建议开发的方法代表了新的方法，解决目前阻碍单粒子冷冻EM进一步发展的具体问题。为了确保最大限度的可移植性和有效传播，这些新方法将在目前部署的SPARX图象处理程序包内实施。公共卫生相关性：高分辨率低温电子显微镜（cryo-EM）已成为大分子复合物结构/功能测定的重要工具。即使在亚纳米分辨率cryo-EM地图提供了丰富的结构信息，最终导致确定的二级结构，如我们的工作所证明的核糖体的结构。此外，cryo-EM是一种独特的结构技术，能够检测一个样品中大分子组装体的构象变异性，该样品可能含有各种构象状态的复合物的混合物。我们建议开发专用的数据处理和统计工具，用于建立在数据集中的构象的数量，并用于结构的构象模式的研究，直接从EM数据。

DESCRIPTION (provided by applicant): In this renewal application, the focus will be on the development of robust single particle cryo-EM analysis methods that incorporate, from their inception, statistical verification of the results. We will concentrate on three specific areas: (1) 2-D image alignment, (2) ab initio structure determination, and (3) quantitative description of macromolecular conformational variability based on data resampling methodology. In (1), a novel 2-D image alignment approach based on the Maximum Likelihood (ML) paradigm will make use of an Expectation Maximization algorithm and incorporate a precise image formation model. The feasibility of the method requires excellent computational efficiency, which will be achieved by spanning the angular parameters in the likelihood function over a finite set, in agreement with properties of typical EM data. We will be able to optimize performance of the proposed method by using filtration in the Fourier Harmonics basis to model alignment-induced blurring of the image data. We also propose to use the eigenanalysis of the alignment parameter covariance matrix obtained from ML to classify images directly from alignment information. In (2), we will greatly improve the performance and reliability of previously developed common lines-based methodology by introducing additional discrepancy terms that follow from considering 2-D overlap between intersecting Fourier planes. In combination with improved alignment algorithms, this methodology will result in a robust approach for generation of initial cryo-EM structures that will overcome current limitations due to low Signal-to-Noise Ratio and structural heterogeneity of the data. In (3), a novel data resampling approach designed to overcome limitations arising from the strongly anisotropic distribution of projections in cryo-EM data sets will permit automation of variance and covariance estimation for 3-D reconstructions. Eigenanalysis of large volume sets generated through data resampling will be used to calculate (directly from the image data) eigenvectors describing the conformational modes of a macromolecular assembly. Structures calculated from data subsets identified through this eigenvector analysis will provide higher-resolution models of conformations relevant for studies of molecular function. Rather than incremental improvements, the methods we propose to develop represent novel approaches that address specific issues currently hindering further development of single particle cryo-EM. To assure maximum portability and efficient dissemination, these new methods will be implemented within the currently deployed SPARX image processing package. PUBLIC HEALTH RELEVANCE: High-resolution cryo-electron microscopy (cryo-EM) has become an important tool for the structure/function determination of large macromolecular complexes. Even at subnanometer resolution cryo-EM maps provide a wealth of structural information, eventually leading to determination of the secondary structure, as demonstrated by our work on the structure of the ribosome. In addition, cryo-EM is a unique structural technique in its ability to detect conformational variability of large molecular assemblies within one sample that may contain a mixture of complexes in various conformational states. We propose development of dedicated data processing and statistical tools for establishing the number of conformers in the data set, and for studies of conformational modes of the structure, as directly obtained from the EM data.