Multi-Resolution Docking Methods for Electron Microscopy

 描述（由申请人提供）：在过去的十年中，在通过电子显微镜对大分子组装体进行3D成像方面以及在将所得体积图与原子分辨率结构相关联的计算算法的开发方面取得了重大进展。拟议研究的总体目标是进一步开发电子显微镜（EM）的计算拟合和验证工具。我们打算建立新的建模，可视化和模拟技术，将作为原子结构和EM密度之间的桥梁。拟议的多尺度软件将有助于生物分子组装体的大尺度结构的常规测定和结构模型的验证，这些结构模型将存入公共数据库，如蛋白质数据库（PDB）和EM数据库（EMDB）。要解决的关键问题包括以下几个方面：（一）如何可以改善，验证，并传播成熟的匹配算法的中间分辨率（8-15毫米）冷冻电子显微镜？(ii)如何能准确地识别和部分几何特征的亚细胞组件在低分辨率（4-5纳米）低温电子断层扫描或聚焦离子束铣削树脂包埋的标本块？(iii)考虑到最近直接检测相机实现的分辨率的增加，如何系统地表征高分辨率（2-10 μ m）密度模式并基于数据中的本地签名验证原子模型？我们将采用一种新的建模范式进行这些研究，即同时细化多个子单元。这种方法是基于“系统”的观点，因为生物组件在空间域中表现出“涌现行为”，也就是说，整体大于其部分的总和。新的范例，结合对接协议，提高了模型的准确性，并打开了大门，在上述三个领域的新的全球拟合应用。此外，我们将使用本地签名的统计分析和机器学习 以补充全球战略。这项资助支持的合作努力将包括细胞骨架丝，分子马达，染色质纤维和毛细胞静纤毛的改进。算法和方法的发展将通过Situs和Sculptor软件包所使用的已建立的基于互联网的机制免费分发。

 DESCRIPTION (provided by applicant): In the past decade, significant progress was made in 3D imaging of macromolecular assemblies via electron microscopy and in the development of computational algorithms that relate the resulting volumetric maps to atomic-resolution structures. The overall goal of the proposed research is to further develop computational fitting and validation tools for electron microscopy (EM). We intend to establish new modeling, visualization, and simulation techniques that would serve as bridges between atomic structures and EM densities. The proposed multi-scale software will aid in the routine determination of large-scale structures of biomolecular assemblies and in the validation of structural models that will be deposited to public databases such as the Protein Data Bank (PDB) and the EM Data Bank (EMDB). Key questions to be addressed include the following: (i) How can one improve, validate, and disseminate well-established matching algorithms for intermediate-resolution (8-15 Å) cryo-electron microscopy? (ii) How can one accurately identify and segment geometric features of subcellular assemblies in low-resolution (4-5 nm) cryo-electron tomograms or in focused ion beam milling of resin-embedded specimen blocks? (iii) Given the recent increase in resolution achieved with direct detection cameras, how can one systematically characterize high-resolution (2-10 Å) density patterns and validate atomic models based on local signatures in the data? We will adapt a new modeling paradigm for these studies, namely simultaneous refinement of multiple subunits. This approach is based on a "systems" perspective because biological assemblies exhibit "emergent behavior" in the spatial domain, that is, the whole is more than the sum of its parts. The new paradigm, in combination with docking protocols, improves model accuracy and opens the door to new global fitting applications in the above three areas. In addition, we will use statistical analysis and machine learning of local signatures to complement the global strategies. The collaborative efforts supported by this grant will include refinement of cytoskeletal filaments, molecular motors, chromatin fibers, 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.