Understanding the thermodynamics and structure of RNA secondary structure motifs

描述(申请人提供)：虽然许多重要的RNA序列已经被确定，但关于RNA的确定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根据序列预测RNA二级结构；然而，缺乏针对非Watson-Crick区域的实验参数是这些算法的主要限制。核磁共振和X射线结晶学是确定RNA三维结构的有力工具，但这些技术都是费时费力的。因此，需要可靠、快速的方法从序列中预测RNA的二级和三维结构。因此，PI实验室的广泛、长期的目标是改进从序列中预测RNA的二级和三级结构。为了实现这一长期目标，了解RNA热力学和结构以及这些性质是如何相关的是至关重要的。从热力学数据中提取改进的最近邻参数可以提高从序列中预测二级结构的效果。为了改进三级结构预测，了解以前求解的三维结构中二级结构基序的结构特征和以前未研究的基序的核磁共振数据将是有益的。因此，这一建议开始研究常见的RNA二级结构基序的热力学和结构。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)用一维和二维质子核磁共振研究常见RNA基序的结构特征。实现这些目标的研究设计和方法包括：光学熔融实验，在蛋白质数据库(PDB)中对RNA结构进行深入搜索和分析，以及使用核磁共振来确定PDB中表达不足的RNA基序的结构特性。这项拟议的研究与美国国立卫生研究院的使命和区域拨款计划的目标相关。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研究领域的发展是至关重要的，并将对依赖RNA结构预测的任何领域的研究人员产生影响，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治疗的研究者。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库，并通过接触和参与生物医学科学的研究使现有的学生受益。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。从这项拟议的研究中收集的数据可以用来更好地了解人类、细菌和病毒，并可以被其他研究人类疾病的原因、诊断、预防和治疗的科学家利用。

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.