High-Resolution CryoEM Reconstruction of Large Complexes

描述（由申请人提供）：本申请的长期目标是通过电子低温显微镜（cryoEM）开发有效测定大型生物复合物在其原生非晶体状态下的原子分辨率三维（3D）结构的方法。新兴的低温电镜和三维重建技术为超分子机器的结构研究提供了巨大的希望，这些超分子机器很难通过x射线晶体学或核磁共振进行研究。PI的研究小组已经发表了用低温冷冻技术确定的亚纳米分辨率的许多复合物的结构，包括水稻矮病毒（RDV）的6埃结构，该结构随后被x射线晶体学证实。由于原子分辨率的低温电镜图像已经使用最先进的仪器记录，我们假设可以开发强大的计算和数据挖掘工具来处理tb级的噪声图像数据，以确定低温电镜的大型复合物的原子模型。从而大大提高了低温电镜结构的价值。这个探索性项目的总体目标是建立在我们亚纳米低温电镜研究的初步成功的基础上，开发有效和准确的方法，从低温电镜图像中确定近原子分辨率的3D地图，并从这些地图中建立原子模型。首先，将开发几种新的计算方法，以提高取向和中心估计和细化的准确性和效率，并允许与大型复合体固有的聚焦深度问题相关的完全对比度传递函数校正。其次，数据管理解决方案、结构挖掘和原子模型构建工具将在IMIRS软件包的用户友好界面下实现，并与其他不同的生物信息学工具集成，以解决与高分辨率低温电镜重建相关的不可避免的艰巨任务。为了消除使用模拟数据的方法开发中固有的潜在偏差，我们的新方法将通过确定RDV的原子结构进行严格和无偏的测试和验证，RDV是一个理想的模型系统，由首席研究员进行了大量研究。该项目将产生一系列高效的算法和软件工具，这些算法和软件工具将对其他超分子组装的结构和计算研究的广泛领域有用并免费提供。我们的研究非常符合美国国立卫生研究院路线图倡议的三个主题中的两个：结构、生物信息学和计算生物学的研究，主题是发现的新途径，主题是未来研究团队的跨学科研究。

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.