Reliable model building for cryo-EM

项目摘要 结构模型的可靠性对于细胞过程的机理研究和合理设计是非常重要的 药物和治疗。Cryo-EM单粒子重建（Cryo-EM SPR）是一种扩展技术， 可以生成结构生物学的原子模型，并且具有不需要将样品 结晶相反，原子模型是基于通过平均数十万个 弱图像，每个图像包含悬浮在薄层中的单个大分子的快照， 冰由于平均噪声图像的内在困难，冷冻EM图通常具有有限的分辨率 并且可以表示多个结构状态的平均值。可靠地构建和重建结构模型 这种地图仍然是一个挑战，而且由于缺乏既定的标准， 验证在低分辨率下构建的模型的质量。 当几个原子组成的组在地图上可以单独识别时， 模型然而，当只有较大的原子群是单独可识别的时，这是有问题的，这是 称为低分辨率。已经观察到，对于低至5 μ m的分辨率，可以建立可靠的模型 (with如果地图是非常精确的。这一观察是我们制定计划的一个重要因素， 实现了自动、全面和准确地为这些低层建立原子模型方法 分辨率为了实现这一目标，在目标1中，我们将通过计算 地图，使他们被纠正的物理影响，目前没有适当考虑在地图创建。在目标2中， 我们将开发和实现一个低分辨率自动建模的综合程序。它将 联合收割机使用通过数据获得的连续和不连续片段库进行快速6D搜索 挖掘已知结构。从6D搜索中获得的假设将被分析用于形成自我- 在多阶段过程中保持一致。接下来将进行GPU加速的分子动力学 受实验数据约束的计算。动力学的输出将经历额外的数据层 挖掘，以识别和触发有问题的起始假设的纠正，并创建一个简洁的描述 大量计算出的结构状态中的信息。最后一步将涉及评估 实验者可能无法解决的模糊性，实验者可能有额外的相关知识指导实验。 选择特定的结构假设。 我们的SBIR第一阶段提案将产生两个软件模块，它们将被纳入商业解决方案 用于冷冻EM中的数据处理、分析和验证。

Project Abstract Reliability of structural models is important for mechanistic studies of cellular processes and for rational design of drugs and treatment. Cryo-EM single particle reconstruction (Cryo-EM SPR) is an expanding technique that can generate atomic models for structural biology and has the advantage that it does not require samples to be crystallized. Instead, atomic models are built based on maps obtained by averaging hundreds of thousands of weak images, with each image containing snapshots of individual macromolecules suspended in a thin layer of ice. Due to the intrinsic difficulties with averaging noisy images, cryo-EM maps frequently have limited resolution and may represent averages of multiple structural states. Building and rebuilding structural models reliably in such maps remains a challenge and the process is additionally complicated by the lack of established criteria for validating the quality of models built at low resolution. When groups of a few atoms are individually recognizable in maps, established methods easily create reliable models. However, it is problematic when only larger groups of atoms are individually recognizable, and this is referred to as low resolution. It has been observed that for resolutions as low as 5 Å, reliable models can be built (with effort) if the maps are highly precise. This observation is an important factor for our plan to develop and implement methods for automatic, comprehensive and accurate building of atomic models for such low resolution. To achieve this goal, in Aim 1 we will improve the low resolution quality of cryo-EM maps by computing maps so that they are corrected for physical effects currently not properly considered in map creation. In Aim 2, we will develop and implement an integrative procedure for automatic model building at low resolution. It will combine a fast 6D search using a library of continuous and discontinuous fragments obtained through the data mining of known structures. The hypotheses obtained from the 6D search will be analyze for forming self- consistent groups in a multi-stage process. This will be followed by GPU-accelerated molecular dynamics computations restrained by experimental data. The output of dynamics will undergo an additional layer of data mining to identify and trigger corrections of problematic starting assumptions and to create a concise description of information present in a multitude of calculated structural states. The final step will involve an assessment of possible unresolved ambiguities by the experimenter, who may have additional relevant knowledge guiding the selection of a specific structural hypothesis. Our SBIR phase I proposal will result in two software modules that will be incorporated into a commercial solution for data processing, analysis, and validation in cryo-EM.