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）：项目摘要电子冷冻微镜和基于计算机的3D图像重建技术正在彻底改变了研究大型，复杂的生物acromacomolocolocular分子机的结构的方式。这些方法为了解这些机器的功能提供了关键。我们的目标是在最短的时间内可靠地确定病毒结构。这将增强我们了解病毒如何引起各种第二干虫的能力，并可能产生有关如何最好地发展抗病毒剂的重要线索。显微镜和图像重建都构成了自己的一系列重大挑战，而新颖软件的开发显然代表了我们研究工作以及其他人的成功的关键。我们的目标是实质上增强了构成冷冻重建工作中3D结构确定部分的核心的计算能力。实现的决议和在冷冻重建中解决的结构受到许多因素的限制，其中最重要的是包括所使用的数值技术。因此，我们将重点关注算法改进，以扩大可以研究的问题范围，使得达到更高的分辨率并减少解决方案的时间。例如，我们将扩展软件的功能，以检查名义上的二十面体病毒的非面体成分以及具有较低对称性的颗粒。除了上述改进外，我们的软件开发兴趣还包括自动化，并行计算以及对可用性的增强功能。对于许多病毒结构，尤其是大型和/或不对称结构，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，并缩小了新手和专家用户可以达到的分辨率之间的差距，我们将增强自动3DEM，即我们的自动化系统，用于智能整合图像重建中所需的多个应用程序。该系统还提供了一个测试床，用于评估新想法，并使该软件易于访问更广泛的用户。拟议的工作应该使我们更接近显微镜的实时图像重建目标，或至少与数据采集紧密耦合，以提供快速的反馈和快速筛选样本属性。我们的研究还通过与同事在冷冻微观镜检查，图像处理以及数据可视化和解释，在NIH，UCSD和Agouron Foundation的支持下获得现代显微镜的收购以及与圣地亚哥超级能力中心的相互作用的相互作用，从而在严重的杠杆上杠杆化。电子显微镜社区将很容易访问我们的所有软件。