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: 8432617
• 负责人: Brent Znosko
• 金额: $ 30万
• 依托单位: SAINT LOUIS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-03-01 至 2016-09-22
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8432617
• 关键词: Address; Algorithms; Bacteria; Biochemical; Biological; Biological Process; Classification; Computational Technique; Data; Databases; Diagnosis; Drug Targeting; Exposure to; Free Energy; Goals; Grant; Health; Human; Hydrogen Bonding; Knowledge; Laboratories; Lead; Medical; Methods; Mission; Molecular; Nature; Nucleotides; Oligonucleotides; Optics; Pattern; Prevention; Property; Proteins; Protocols documentation; RNA; RNA Sequences; RNA Stability; Research; Research Design; Research Methodology; Research Personnel; Science; Scientist; Source; Space Perception; Structure; Structure-Activity Relationship; Students; Techniques; Temperature; Testing; Therapeutic; Thermodynamics; Time; United States National Institutes of Health; Variant; Vertebral column; Virus; X-Ray Crystallography; base; functional group; human disease; improved; inorganic phosphate; insight; knowledge base; melting; predictive modeling; programs; public health relevance; rapid technique; research study; three dimensional structure; tool; web site

DESCRIPTION (provided by applicant): While many important RNA sequences have been determined, there is little definitive secondary and three-dimensional (3D) structure information about RNA. Several 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 3D structure; however, these techniques are time and labor intensive. Thus, there is a need for reliable, rapid methods to predict secondary and 3D 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. Computational techniques can be used to understand the relationship between RNA thermodynamics and RNA structure. Therefore, this proposal begins to investigate the thermodynamics, structures, and energetics of common RNA secondary structure motifs. The specific objectives of the proposed research are: (1) to address the major limitations of the current algorithms used to predict secondary structure from sequence, (2) to identify structural patterns of secondary structure motifs in 3D structures, and (3) to investigate the relationship between RNA stability and structure on a molecular level via computational techniques. The research design and methods for achieving these goals include: optical melting experiments, an in-depth analysis of previously solved RNA structures, the use of NMR to identify structural properties of underrepresented RNA motifs, and hydrogen bonding and base stacking calculations. 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.

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（3D）结构信息很少。已经开发了几种算法来预测RNA二级结构的序列，然而，缺乏实验参数的非沃森-克里克地区是这些算法的一个主要限制。NMR和X射线晶体学是确定RNA 3D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3D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。计算技术可以用来理解RNA热力学和RNA结构之间的关系。因此，本计划开始研究常见RNA二级结构基序的热力学、结构和能量学。该研究的具体目标是：（1）解决目前用于从序列预测二级结构的算法的主要局限性，（2）识别三维结构中二级结构基序的结构模式，以及（3）通过计算技术在分子水平上研究RNA稳定性和结构之间的关系。实现这些目标的研究设计和方法包括：光学解链实验，对先前解决的RNA结构的深入分析，使用NMR来识别代表性不足的RNA基序的结构特性，以及氢键和碱基堆积计算。 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。