Multi-Resolution Docking Methods for Electron Microscopy

摘要 在过去的十年里，我们见证了相机技术和可实现的革命性进步 通过低温电子显微镜(CRYO-EM)和发展中的大分子组件的拆分 将生成的3D地图与原子分辨率结构相关联的计算算法。而单人- 今天的粒子冷冻-EM能够孤立地直接求解生物分子组件的原子结构， 在未染色的冷冻水化样品中，电子断层成像(ET)被广泛用于捕捉3D组织 在其天然(细胞器、细胞或组织)环境中的超分子复合体。我们已经确认了三个 相互关联的研究领域，我们的计算建模经验(历史上植根于革命前 多规模方法)为革命后的EM社区提供了最大的价值：(1)中等 分辨率低温电磁建模，(2)低温数据的分割和去噪，以及(3)验证 原子模型及其对应的地图。第一个目标是将有希望的新想法延伸到灵活的 中分辨率地图的拟合和二级结构预测一直是我们的关键 过去的研究领域。在EM中仍广泛使用中分辨率(5-10？)地图，可以 具有重要的生物学意义。这在冷冻地图的情况下尤其如此，因为它们更难阅读 因为它们通常表现出相当大的噪声、各向异性分辨率和 由于低剂量要求和傅里叶空间中缺失楔形的原因，密度的各向异性变化。在……里面 紧密堆积或拥挤的大分子结构的情况，附近生物分子密度的融合 防止自动分割几何形状，需要通过以下方式进行劳动密集型手动跟踪 人类专家。我们目前正在开发新的计算方法，以提供更客观的 断层图像均匀样本区缺失楔形校正策略。我们的混合方法 将去卷积和去噪与模板匹配结合在一个统一的数学框架中，从而 在最小二乘优化过程中要施加的建模约束。我们的方法也可以是 扩展到使用我们的阻尼动力学柔性拟合方法的原子结构的柔性精化 将内部点扩展函数调整到ET数据的缺失楔形。为了支持这些目标，我们将 定量测量原子模型在局部密度区域的适合性，并表征 具有可靠参考结构的地图。这笔赠款支持的合作努力将包括 细胞骨架细丝、分子马达、细菌化学感受器阵列和毛细胞的改进 立体纤毛。算法和方法的发展将通过已建立的 SUTUS和Sculptor包使用的基于互联网的机制，以及作为流行的UCSF的插件 Chimera图形程序。

Summary In the past decade, we have witnessed a revolutionary progress in camera technology and the attainable resolution of macromolecular assemblies via cryogenic electron microscopy (cryo-EM) and in the development of computational algorithms that relate the resulting 3D maps to atomic resolution structures. Whereas single- particle cryo-EM today is capable of directly solving atomic structures of biomolecular assemblies in isolation, electron tomography (ET) in unstained frozen-hydrated samples is widely used to capture the 3D organization of supramolecular complexes in their native (organelle, cell, or tissue) environments. We have identified three inter-related research areas where our computational modeling experience (historically rooted in pre-revolution multi-scale approaches) offers the biggest value to today's post-revolution EM community: (1) medium resolution cryo-EM modeling, (2) the segmentation and denoising of cryo-ET data, and (3) the validation of atomic models and their corresponding maps. The first aim is an extension of promising new ideas in flexible fitting as well as secondary structure prediction for medium resolution maps, which have been our key research areas in the past. medium resolution (5-10Å) maps are still widely used in EM and can be of significant biological importance. This is particularly true in the case of cryo-ET maps, which are harder to read than single particle cryo-EM maps because they often exhibit considerable noise, anisotropic resolution, and anisotropic density variations due to the low dose requirements and the missing wedge in the Fourier space. In the case of tightly packed or crowded macromolecular structures, the fusion of nearby biomolecular densities prevents an automated segmentation of geometric shapes, requiring a labor-intensive manual tracing by human experts. We are currently developing novel computational approaches to provide a more objective strategy for missing wedge correction in homogeneous specimen areas of tomograms. Our hybrid approach combines deconvolution and denoising with template matching in a unified mathematical framework that allows modeling constraints to be imposed in a least-squares optimization process. Our approach can also be extended to the flexible refinement of atomic structures using our damped dynamics flexible fitting approach by tuning the internal point-spread functions to the missing wedge of the ET data. To support these aims, we will quantitatively measure the fitness of an atomic model in local density regions and characterize the fitness of maps with reliable reference structures. The collaborative efforts supported by this grant will include the refinement of cytoskeletal filaments, molecular motors, bacterial chemoreceptor arrays, and hair cell stereocilia. The algorithmic and methodological developments will be distributed freely through the established Internet-based mechanisms used by the Situs and Sculptor packages and as plugins for the popular UCSF Chimera graphics program.