High-Resolution CryoEM Reconstruction of Large Complexes

描述（由申请人提供）：本申请的长期目标是开发通过电子低温显微镜（cryoEM）有效测定天然非结晶状态下大型生物复合物的原子分辨率三维（3D）结构的方法。cryoEM和3D重建的新兴技术为难以通过X射线晶体学或NMR研究的超分子机器的结构研究提供了巨大的希望。PI的小组已经发表了许多复合物在亚纳米分辨率下的cryoEM确定的结构，包括水稻矮缩病毒（RDV）的6埃结构，随后通过X射线晶体学证实。由于原子分辨率cryoEM图像已被记录使用国家的最先进的仪器，我们假设，强大的计算和数据挖掘工具可以开发来处理TB的噪声图像数据，以确定原子模型的大型复杂的cryoEM。从而显著提高了cryoEM结构的价值。这个探索性项目的总体目标是在亚纳米cryoEM研究的初步成功基础上，开发出有效和准确的方法，用于从cryoEM图像确定近原子分辨率的3D地图，并从这些地图中构建原子模型。首先，将开发几种新的计算方法，以提高定位和中心估计和细化的准确性和效率，并允许与大复合体的固有焦深问题相关的全对比度传递函数校正。其次，将实施数据管理解决方案，结构挖掘和原子模型构建工具，并在IMIRS软件包的用户友好界面下与其他不同的生物信息学工具集成，以解决与高分辨率cryoEM重建相关的不可避免和艰巨的任务。为了消除使用模拟数据的方法开发中固有的潜在偏倚，我们的新方法将通过确定RDV的原子结构进行严格和无偏倚的测试和验证，RDV是主要研究者大量研究的理想模型系统。该项目将产生一个高效和有效的算法和软件工具，将是有用的，免费提供给其他超分子组装的结构和计算研究的广泛领域的全方位。我们的研究非常适合NIH路线图倡议的三个主题中的两个：以发现新途径为主题的结构，生物信息学和计算生物学研究以及以未来研究团队为主题的跨学科研究。

DESCRIPTION (provided by applicant): The long-term objective of this application is to develop methods for the efficient determination of atomic-resolution three-dimensional (3D) structures of large biological complexes in their native, non-crystalline states by electron cryomicroscopy (cryoEM). The emerging technology of cryoEM and 3D reconstruction offer great promise for structural studies of supramolecular machines that are difficult to study by X-ray crystallography or NMR. The PI's group has published the cryoEM-determined structures of a number of complexes at subnanometer resolutions, including the 6-Angstrom structure of rice dwarf virus (RDV), which was subsequently confirmed by X-ray crystallography. Because atomic-resolution cryoEM images have been recorded using state-of-the-art instruments, we hypothesize that powerful computation and data mining tools can be developed to process terabytes of noisy image data for determining atomic models of large complexes by cryoEM. thus significantly enhancing the value of cryoEM structures. The overall goal of this exploratory project is to build upon our initial success of subnanometer cryoEM studies to develop efficient and accurate methods for determining near-atomic resolution 3D maps from cryoEM images and for building atomic models from such maps. First, several novel computational methods will be developed to improve the accuracy and efficiency of orientation and center estimation and refinement, and to allow full contrast transfer function correction associated with the inherent depth-of-focus problem of large complexes. Second, data management solutions, structure mining and atomic model-building tools will be implemented and integrated with other disparate bioinformatics tools under a user-friendly interface of the IMIRS package to tackle the inevitable and daunting tasks associated with high-resolution cryoEM reconstructions. To eliminate potential bias inherent in method developments using simulated data, our new methods will be subjected to rigorous and unbiased testing and validation by determining the atomic structures of RDV, an ideal model system substantially studied by the Principal Investigator. This project will result in a full spectrum of efficient and effective algorithms and software tools that will be useful and freely available to the broad areas of structural and computational studies of other supramolecular assemblies. Our study fits well in two of the three themes of the NIH Roadmap initiatives: research in structural, bioinformatics and computational biology under the theme of New Pathways to Discovery and interdisciplinary research under the theme of Research Teams of the Future.