DE NOVO RNA STRUCTURES WITH EXPERIMENTAL VALIDATION

经过实验验证的从头 RNA 结构

• 批准号: 8364300
• 负责人: Rhiju Das
• 金额: $ 0.11万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8364300
• 关键词: Algorithms; Benchmarking; Biomedical Research; Catalysis; Code; Computer software; Environment; Funding; Goals; Grant; High Performance Computing; Home environment; Information Storage; Maps; Modeling; National Center for Research Resources; Performance; Principal Investigator; Procedures; Proteins; RNA; RNA Folding; Research; Research Infrastructure; Resolution; Resources; Small RNA; Source; Speed; Structure; Supercomputing; System; Technology; Time; Training; United States National Academy of Sciences; United States National Institutes of Health; Validation; cell growth regulation; cluster computing; cost; molecular dynamics; novel; research study; scale up; simulation; theories

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The past decade has revealed the breadth of RNA's functions, which include information storage, catalysis, and cellular regulation. However, computational approaches to RNA structure have lagged behind those involving proteins. We propose two computational projects that will allow us to produce quality models of RNA structure. We have developed a high resolution RNA force field that has been included in the Rosetta modeling software [1]. Our first goal is to develop and refine novel conformational search algorithms using this force field. However, to validate such procedures requires training and benchmarking on a wide array of existing structures. Such a benchmark will be possible only by scaling up to a larger supercomputing environment. Secondly, we plan to model the dynamics of small RNA systems using CUDA-optimized molecular dynamics code (OpenMM). The performance gains (5x-100x) enabled by GPGPU technology will allow the simulation of RNA folding at atomic resolution. In the past, such computations have been limited to distributed computing environments such as Folding@Home. The resources afforded by the Teragrid infrastructure will allow us to scale up our research both in scope and in speed. We expect that the quick turnaround time afforded by TeraGrid resources will allow a more dynamic relationship between theory and experiment: quantitative predictions will be quickly verified in our lab by high throughput structure mapping approaches that achieve single residue resolution [2]. [1] Das, R. and Baker, D. (2007) "Automated de novo prediction of native-like RNA tertiary structures", Proceedings of the National Academy of Sciences U.S.A. 104, 14644"14669. [2] Das, R., Kudaravalli, M., Jonikas, M., Laederach, A., Fong, R., Schwans, J.P., Baker, D., Piccirilli, J.A., Altman, R.B., and Herschlag, D. (2007) "Structural inference of native and partially folded RNA by high throughput contact mapping", Proceedings of the National Academy of Sciences U.S.A 105, 4144-4149.

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其他NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 过去的十年揭示了RNA功能的广度，包括信息存储，催化和细胞调节。然而，RNA结构的计算方法已经落后于那些涉及蛋白质的方法。我们提出了两个计算项目，这将使我们能够产生RNA结构的质量模型。我们已经开发了一个高分辨率的RNA力场，该力场已包含在Rosetta建模软件中[1]。我们的第一个目标是开发和完善新的构象搜索算法使用这个力场。然而，要验证这些程序，就需要对各种现有结构进行培训和制定基准。这样的基准测试只有通过扩展到更大的超级计算环境才有可能。其次，我们计划使用CUDA优化的分子动力学代码（OpenMM）来模拟小RNA系统的动力学。GPGPU技术带来的性能提升（5倍-100倍）将允许以原子分辨率模拟RNA折叠。在过去，这样的计算一直局限于分布式计算环境，如Folding@Home。Teragrid基础设施提供的资源将使我们能够在范围和速度上扩大我们的研究。我们期望TeraGrid资源提供的快速周转时间将允许理论和实验之间的更动态的关系：定量预测将在我们的实验室中通过实现单个残基分辨率的高通量结构映射方法快速验证[2]。[1]达斯河，巴西-地和Baker，D.（2007）“Automated de novo prediction of native-like RNA tertiary structures”，Proceedings of the National Academy of Sciences U.S.A. 104，14644“14669. [2]达斯河，巴西-地Kudaravalli，M.，Jonikas，M.，Laederach，A.，方河，巴西-地Schwans，J.P.，贝克，D.，Piccirilli，J.A.，阿尔特曼RB和Herschlag，D.等人（2007）“Structural inference of native and partially folded RNA by high throughput contact mapping”，Proceedings of the National Academy of Sciences U.S.A 105，4144-4149。