High-Resolution CryoEM Reconstruction of Large Complexes

描述(申请人提供)：本申请的长期目标是开发利用电子冷冻显微镜(CryoEM)有效地确定处于天然非晶态的大型生物复合体的原子分辨三维(3D)结构的方法。新兴的低温电子显微镜和三维重建技术为X射线结晶学或核磁共振难以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亚纳米分辨率的复合体的低温电子显微镜确定的结构，包括水稻矮缩病毒(RDV)的6埃结构，这随后得到了X射线结晶学的证实。由于原子分辨率的低温电子显微镜图像是使用最先进的仪器记录的，我们假设可以开发出强大的计算和数据挖掘工具来处理兆兆字节的噪声图像数据，以便用低温电子显微镜确定大型络合物的原子模型。从而显著提高了低温电子显微镜结构的价值。这个探索性项目的总体目标是在我们亚纳米低温电磁研究初步成功的基础上，开发有效和准确的方法，从低温电磁图像确定近原子分辨率的3D图，并根据这种图建立原子模型。首先，将开发几种新的计算方法来提高定向和中心估计和细化的精度和效率，并允许与大型复合体固有的焦深问题相关的全对比度传递函数校正。第二，将实施数据管理解决方案、结构挖掘和原子模型建立工具，并在IMIRS包的用户友好界面下与其他不同的生物信息学工具相结合，以处理与高分辨率低温EM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差，我们的新方法将通过确定RDV的原子结构进行严格和公正的测试和验证，RDV是首席研究员大量研究的理想模型系统。该项目将产生一系列高效和有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和免费提供。我们的研究很好地符合NIH路线图倡议的三个主题中的两个：在新发现途径主题下的结构、生物信息学和计算生物学研究，以及在未来研究团队主题下的跨学科研究。

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.