Understanding the thermodynamics and structure of RNA secondary structure motifs

了解 RNA 二级结构基序的热力学和结构

• 批准号: 8019253
• 负责人: Brent Znosko
• 金额: $ 6.19万
• 依托单位: SAINT LOUIS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-05 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8019253
• 关键词: Algorithms; Bacteria; Biological; Computational algorithm; Data; Databases; Diagnosis; Exposure to; Figs - dietary; Goals; Grant; Health; Human; Hydrogen Bonding; Knowledge; Laboratories; Medical; Methods; Mission; Oligonucleotides; Optics; Pattern; Positioning Attribute; Prevention; Property; Proteins; Protons; RNA; RNA Databases; RNA Sequences; RNA analysis; Research; Research Design; Research Personnel; Right-On; Sampling; Science; Scientist; Secondary to; Structure; Structure-Activity Relationship; Students; Techniques; Therapeutic; Thermodynamics; Time; United States National Institutes of Health; Vertebral column; Virus; X-Ray Crystallography; group I ribozyme; human disease; improved; insight; knowledge base; melting; predictive modeling; programs; public health relevance; rapid technique; research study; stem; three dimensional structure; tool; two-dimensional

DESCRIPTION (provided by applicant): While many important RNA sequences have been determined, there is little definitive secondary and three-dimensional structure information about RNA. Several computer algorithms have been developed to predict RNA secondary structure from sequence; however, the lack of experimental parameters for non-Watson-Crick regions is a major limitation of these algorithms. NMR and X-ray crystallography are powerful tools to determine RNA three-dimensional structure; however, these techniques are time and labor intensive. Thus, there is a need for reliable, rapid methods to predict secondary and three-dimensional structures of RNA from sequence. Therefore, the broad, long-term objective of the PI's laboratory is to improve RNA secondary and tertiary structure prediction from sequence. In order to achieve this long-term objective, it is essential to understand RNA thermodynamics and structure and how these properties are related. Improved nearest neighbor parameters derived from thermodynamic data can improve secondary structure prediction from sequence. In order to improve tertiary structure prediction, knowledge about the structural features of secondary structure motifs in previously solved three-dimensional structures and NMR data for previously unstudied motifs would be beneficial. Therefore, this proposal begins to investigate the thermodynamics and structures of common RNA secondary structure motifs. The specific objectives of the proposed research are: (1) to investigate the major limitations of the current algorithms used to predict secondary structure from sequence, (2) to comprehensively identify, annotate and compare secondary structure motifs in three-dimensional structures, and (3) to investigate structural features of common RNA motifs by one- and two-dimensional proton NMR. The research design and methods for achieving these goals include: optical melting experiments, an in-depth search and analysis of RNA structures in the Protein Data Bank (PDB), and the use of NMR to identify structural properties of underrepresented RNA motifs in the PDB. This proposed research is relevant to the mission of the NIH and the objectives of the AREA Grant program. An improved method to predict RNA secondary and tertiary structure from sequence is essential to move the field of RNA research forward and should impact researchers in any field relying on RNA structure prediction, especially those attempting to understand the structure-function relationship of RNA, understand the interactions of RNA with other biological molecules, and target RNA with therapeutics. As a result, the proposed research will advance the Nation's capacity to protect and improve health, expand the knowledge base in medical and associated sciences, and benefit available students through exposure to and participation in research in the biomedical sciences. PUBLIC HEALTH RELEVANCE: The proposed research will provide essential information in order to move the field of RNA research forward. The data that is collected from this proposed research can be used to better understand humans, bacteria, and viruses and can be utilized by other scientists who are researching the causes, diagnosis, prevention, and cure of human diseases.

描述（由申请人提供）：虽然已经确定了许多重要的RNA序列，但关于RNA的二级和三维结构信息很少。已经开发了几种计算机算法来从序列预测RNA二级结构;然而，缺乏非沃森-克里克区域的实验参数是这些算法的主要限制。NMR和X射线晶体学是确定RNA三维结构的有力工具;然而，这些技术是时间和劳动密集型的。因此，需要可靠、快速的方法来从序列预测RNA的二级和三维结构。因此，PI实验室的长期目标是改进RNA二级和三级结构的序列预测。为了实现这一长期目标，有必要了解RNA的热力学和结构以及这些性质之间的关系。改进的热力学最近邻参数可以提高序列二级结构预测的准确性。为了改善三级结构预测，关于先前解析的三维结构中的二级结构基序的结构特征和先前未研究的基序的NMR数据的知识将是有益的。因此，本研究计划开始研究RNA二级结构模体的热力学和结构。本研究的具体目标是：（1）调查目前用于从序列预测二级结构的算法的主要局限性，（2）全面识别、注释和比较三维结构中的二级结构基序，（3）通过一维和二维质子NMR研究常见RNA基序的结构特征。实现这些目标的研究设计和方法包括：光学解链实验，深入搜索和分析蛋白质数据库（PDB）中的RNA结构，以及使用NMR来识别PDB中代表性不足的RNA基序的结构特性。这项拟议的研究与NIH的使命和AREA资助计划的目标有关。一种改进的从序列预测RNA二级和三级结构的方法对于推动RNA研究领域的发展至关重要，并且应该影响依赖于RNA结构预测的任何领域的研究人员，特别是那些试图了解RNA的结构-功能关系，了解RNA与其他生物分子的相互作用以及靶向RNA与治疗的研究人员。因此，拟议的研究将提高国家保护和改善健康的能力，扩大医学和相关科学的知识基础，并通过接触和参与生物医学科学的研究使现有学生受益。公共卫生相关性：拟议的研究将提供必要的信息，以推动RNA研究领域的发展。从这项拟议研究中收集的数据可用于更好地了解人类，细菌和病毒，并可供研究人类疾病的原因，诊断，预防和治疗的其他科学家使用。