Multi-Scale Dynamic Modeling of RNA Folding and Assembly
Multi-Scale Dynamic Modeling of RNA Folding and Assembly
批准号:
7923647
负责人:
Alain T Laederach
金额:
$14.3万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2010-12-31
关键词:
AlgorithmsAntibioticsBiological ModelsBiologyCell physiologyComplexComputer softwareDNA biosynthesisDataData SetDeuteriumDevelopmentEngineeringGenetic ProgrammingGenetic TranscriptionHydroxyl RadicalInformaticsIntronsKineticsLeadMacromolecular ComplexesMeasurementMeasuresMessenger RNAMethodologyMethodsModelingMolecular ConformationMolecular MachinesMolecular StructureNatureNucleotidesPathway interactionsPerformancePharmacologic SubstancePositioning AttributeProcessProtein BindingProteinsPublic HealthPublishingRNARNA FoldingReactionRibosomal ProteinsRibosomesSon of Sevenless ProteinsSpliceosomesStructural ModelsStructureSystemTechniquesTetrahymena thermophilaTranslation ProcessValidationWorkbasecluster computingcombinatorialdirect applicationimprovedmacromolecular assemblymacromoleculemolecular assembly/self assemblynovel
中文摘要
核糖体和剪接体等自组装大分子机器是
基本的细胞过程,包括转录、信使核糖核酸的加工、翻译和DNA复制。
创建对导致其组装的步骤序列的定量和预测性描述
功能构象对于实现对细胞过程的预测性理解是必要的。大的
组成大分子机器的多个组件导致高度复杂的组装
反应。在吞吐量和探索这些的各种实验方法方面的最新进展
反应提供了丰富的信息。集成这些数据并构建一致的描述
组装过程需要开发集成多尺度数据的复杂算法
并利用大型分布式计算网格日益增长的能力。这份提案概述了
创建定量和预测性结构和动态的新算法的扩展和应用
基于反应动力学测量的分子组装过程的描述。这些
算法的发展,结合关于组装反应的大型数据集的获取
30S核糖体亚基将被用来创建对组装的高度详细的定量描述
这台关键的分子机器的反应。这一描述将大大加深我们对
分子组装,因为它还将预测可能的组装路径的数量和复杂性
AS确定机器的RNA和蛋白质组件之间的协同程度。
公共卫生声明:
像所有能够执行复杂任务的机器一样,核糖体由许多不同的
组件。通过了解这些成分是如何聚集在一起形成一个功能齐全的分子的,
我们正在对这台机器进行有效的逆向工程。这种新的认识将有助于我们增强、抑制
和/或修改机器的功能。这项工作的一个直接应用是小说的发展
抗生素作为细菌核糖体是主要的药物靶标。此外,一份详细的蓝图
组装过程将显著提高我们设计新型分子机器的能力,完全
新功能。
英文摘要
Self-assembling macromolecular machines such as the ribosome and spliceosome are central to
fundamental cellular processes including transcription, mRNA processing, translation, and DNA replication.
Creating a quantitative and predictive description of the sequence of steps leading to their assembled and
functional conformation is necessary to achieving a predictive understanding of cellular processes. The large
number of components that make up a macromolecular machine result in a highly complex assembly
reaction. Recent developments in the throughput and variety of experimental approaches that probe these
reactions provide a cornucopia of information. Integrating these data and building consistent descriptions of
the assembly process requires the development of sophisticated algorithms that integrate multi-scale data
and leverage the ever increasing power of large distributed computing grids. This proposal outlines the
extension and application of novel algorithms that create quantitative and predictive structural and dynamic
descriptions of molecular assembly processes based on kinetic measurements of the reaction. These
algorithmic developments, in conjunction with the acquisition of large data sets on the assembly reaction of
the 30S ribosomal subunit, will be used to create a highly detailed quantitative description of the assembly
reaction of this critical molecular machine. The description will greatly deepen our understanding of
molecular assembly, as it will predict the number and complexity of the possible assembly pathways, as well
as establish the degree of cooperativity between the RNA and protein components of the machine.
Public Health Statement:
Like all machines capable of carrying out complex tasks, the ribosome is comprised of many different
components. By understanding how these components come together to make a fully functional molecule,
we are effectively reverse engineering the machine. This new understanding will help us enhance, inhibit
and/or modify the function of the machine. One direct application of this work is the development of novel
antibiotics, as the bacterial ribosome is a major pharmaceutical target. Furthermore, a detailed blueprint of
the assembly process will significantly improve our ability to engineer novel molecular machines with entirely
new function.
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会议论文
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海外基金