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Parallel Software for Fast, Automated Determination of Virus Structures

用于快速、自动确定病毒结构的并行软件

基本信息

批准号：
8475618
负责人：
Timothy S Baker
金额：
$ 29.52万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-06-01 至 2014-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8475618
关键词：
Algorithms Animals Automation Bacteriophages Beds Boxing Cessation of life Communities Complex Computer software Computers Coupled Cryoelectron Microscopy Data Development Disease Double Stranded RNA Virus Electron Microscope Electron Microscopy Famines Feedback Food Foundations Goals Heart Hour Human Image Imagery Knowledge Life Link Lipid Bilayers Methods Microscope Microscopy Modeling Molecular Structure Organism Preparation Property RNA-Directed RNA Polymerase Research Resolution Sampling Solutions Source Structure System Techniques Testing Three-Dimensional Image Time Totivirus United States National Institutes of Health Viral Viral Genome Virus Work base data acquisition image processing image reconstruction interest novel parallel computing particle public health relevance reconstruction screening software development success supercomputer three dimensional structure three-dimensional modeling transmission process usability viral RNA

项目摘要

DESCRIPTION (provided by applicant): Project Summary Electron cryo-microscopy and computer-based, 3D image reconstruction techniques are revolutionizing the way structures of large, complex biomacromolecular machines are studied. These methods provide keys to understanding how these machines function. Our goal is to determine virus structures reliably at the highest possible resolutions in the shortest amount of time. This will enhance our ability to understand how viruses cause a variety of dieases and may yield important clues about how best to develop anti-viral agents. Microscopy and image reconstruction each pose their own set of significant challenges, and development of novel software clearly represents a key to the success of our research efforts as well as that of others. We aim to substantially enhance the computational capabilities that comprise the heart of the 3D structure determination part of our cryo-reconstruction work. The resolutions achieved and structures solved in cryo-reconstruction are limited by many factors, not the least of which includes the numerical techniques employed. Hence, we will focus on algorithmic improvements that expand the range of problems that can be studied, make it possible to reach higher resolutions, and reduce time to solution. For example, we will extend the capabilities of our software to examine the non-icosahedral components of nominally icosahedral viruses as well as particles with lower symmetries. In addition to the improvements noted above, our software development interests include automation, parallel computing, and enhancements to usability. For many virus structures, especially large and/or asymmetric ones, image reconstruction is the rate limiting step. To reduce the time between image acquisition and structure determination and also narrow the gap between the resolutions that can be reached by novice and expert users, we will enhance AUTO3DEM, our automation system for intelligently integrating the multiple applications required in image reconstruction. This system also provides a test bed for evaluating new ideas and makes the software easily accessible to a wider range of users. The proposed work should take us closer to our goal of real-time image reconstruction at the microscope, or at least tightly coupled to data acquisition, to provide rapid feedback and quickly screen sample properties. Our studies are also heavily leveraged by close ties to colleagues in cryo-microscopy, image processing, and data visualization and interpretation, the acquisition of modern microscopes with support from NIH, UCSD, and the Agouron foundation, and interaction with the San Diego Supercomputer Center. All of our software will be made readily accessible to the electron microscopy community.

描述（由申请人提供）：项目摘要电子冷冻显微镜和基于计算机的3D图像重建技术正在彻底改变大型复杂生物大分子机器结构的研究方式。这些方法提供了理解这些机器如何工作的关键。我们的目标是在最短的时间内以尽可能高的分辨率可靠地确定病毒结构。这将增强我们理解病毒如何引起各种疾病的能力，并可能为如何最好地开发抗病毒药物提供重要线索。显微镜和图像重建各自提出了一系列重大挑战，而新软件的开发显然是我们和其他人研究工作成功的关键。我们的目标是大大提高计算能力，包括我们的冷冻重建工作的3D结构确定部分的心脏。在冷冻重建中实现的分辨率和解决的结构受到许多因素的限制，其中包括所采用的数值技术。因此，我们将专注于算法改进，扩大可以研究的问题范围，使其有可能达到更高的分辨率，并减少解决问题的时间。例如，我们将扩展我们的软件的功能，以检查名义上的二十面体病毒的非二十面体组件以及具有较低对称性的粒子。除了上面提到的改进之外，我们的软件开发兴趣还包括自动化、并行计算和增强可用性。对于许多病毒结构，特别是大的和/或不对称的，图像重建是速率限制步骤。为了减少图像采集和结构确定之间的时间，并缩小新手和专家用户可以达到的分辨率之间的差距，我们将增强AUTO 3DEM，我们的自动化系统，智能集成图像重建所需的多种应用程序。该系统还为评估新想法提供了一个试验平台，并使更广泛的用户可以轻松使用该软件。拟议的工作应该使我们更接近我们的目标，即在显微镜下实时图像重建，或者至少与数据采集紧密耦合，以提供快速反馈并快速筛选样品特性。我们的研究也在很大程度上利用了与冷冻显微镜，图像处理和数据可视化和解释的同事的密切联系，在NIH，UCSD和Agouron基金会的支持下获得现代显微镜，以及与圣地亚哥超级计算机中心的互动。我们所有的软件都将随时提供给电子显微镜社区。