RECONSTRUCTION FROM HETEROGENEOUS MOLECULE POPULATIONS

从异质分子群重建

• 批准号: 7598352
• 负责人: JOACHIM FRANK
• 金额: $ 8.02万
• 依托单位: WADSWORTH CENTER
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-02-01 至 2008-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7598352
• 关键词: Address; Algorithms; Classification; Communities; Computer Retrieval of Information on Scientific Projects Database; Computer software; Data; Data Set; Documentation; Funding; Grant; Heterogeneity; Institution; Ligand Binding; Ligands; Maps; Methods; Molecular Conformation; Noise; Phase; Population; Publications; Research; Research Personnel; Resolution; Resources; Roentgen Rays; Sampling; Signal Transduction; Source; Spiders; Structure; Test Result; Testing; United States National Institutes of Health; abstracting; base; concept; density; design; macromolecule; particle; prevent; reconstruction; software development

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. ABSTRACT: This TRD addresses a problem that is paramount in cryo-EM single-particle reconstruction of macromolecules, and that is in many cases the single obstacle preventing the attainment of high resolution (better than 10 ¿). This problem is the heterogeneity of molecules in the sample due to partial ligand occupancy and conformational variability. We will develop general approaches for the classification of heterogeneous molecule populations from their cryo-EM projections, which will include both supervised and unsupervised classification methods. We will interact with leading experts in this field and use typical data both from the PIs group and from other groups pursuing single-particle reconstruction. Resulting software, if successful, will be made available to a wide community. Specific Aims 1. (Exploration phase): Explore methods of classification of single-particle projections that refine existing template-based approaches, or exploit general intrinsic mathematical relationships among projections of unchanged objects. In this phase of the project, algorithms such as self-organized (SOMs) will be designed, or the utility of existing ones explored. Phantom data sets are derived from existing density maps of molecules or from X-ray structures that present different conformations or states of ligand binding. Such maps are projected systematically into a variety of directions, the resulting projections are low-pass filtered and contaminated with noise. These data will allow a determination of which algorithm or which SOM configuration will perform best at different resolutions and signal-to-noise ratios. 2. (Testing phase): Test the resulting algorithms and SOMs on well-defined experimental cryo-EM data sets from single-particle projects that are conducted within and outside the Wadsworth Center. Ideally, these should be data that have been characterized in previous publications, so that the improvements due to the new classification approaches can be easily assessed. 3. (Dissemination phase): Integrate the software with existing SPIDER software and develop comprehensive documentation. Publication of the underlying concepts in explicit form will also allow other authors of software packages such as EMAN (Ludtke et al., 2001) to implement their own version, for wider dissemination.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 摘要： 该TRD解决了在大分子的冷冻EM单粒子重建中至关重要的问题，并且在许多情况下，该问题是阻止实现高分辨率（优于10 μ m）的单一障碍。 这个问题是由于部分配体占据和构象可变性导致的样品中分子的异质性。我们将开发通用的方法从他们的cryo-EM预测，这将包括监督和无监督的分类方法的异质分子群体的分类。 我们将与该领域的领先专家进行互动，并使用来自PI的典型数据的小组和其他小组追求单粒子重建。 所产生的软件，如果成功，将提供给广大社区。 具体目标 1. （探索阶段）：探索改进现有基于模板的方法的单粒子投影分类方法，或利用未改变对象的投影之间的一般内在数学关系。 在项目的这一阶段，将设计自组织（SOM）等算法，或探索现有算法的实用性。 体模数据集源自现有的分子密度图或呈现不同配体结合构象或状态的X射线结构。 这些地图被系统地投影到各个方向，所得到的投影被低通滤波并被噪声污染。 这些数据将允许确定哪种算法或哪种SOM配置在不同分辨率和信噪比下表现最佳。 2. （测试阶段）：在沃兹沃斯中心内外进行的单粒子项目中，在定义良好的实验cryo-EM数据集上测试所得到的算法和SOM。 理想情况下，这些数据应该是以前出版物中描述过的数据，这样就可以很容易地评估新分类方法带来的改进。 3. （传播阶段）：将该软件与现有天基信息平台软件相结合，并编写全面的文件。 以明确的形式公布基本概念也将允许软件包的其他作者，例如EMAN（Ludtke等人，2001年）执行自己的版本，以便更广泛地传播。