While many important RNA sequences have been determined, there is little definitive secondary and three-dimensional (3D) structure information about RNA. Several algorithms predict RNA secondary structure from sequence. However, they are limited by a lack of experimental parameters for non-Watson-Crick regions, the inability to incorporate non-standard nucleotides, and lack of knowledge about how different solvent conditions affect stability. NMR and X-ray crystallography are powerful tools to determine RNA 3D structure but 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. To do so, it is essential to understand RNA thermodynamics and structure and how these are related. Improved nearest neighbor parameters derived from thermodynamic data can improve secondary structure prediction from sequence. To improve tertiary structure prediction, it would help to know the structural features of secondary structure motifs in solved three-dimensional structures and NMR data for unstudied motifs. Computations can be used to understand the relationship between RNA thermodynamics and RNA structure. Therefore, this proposal continues to investigate the thermodynamics, structures, and energetics of common RNA secondary structure motifs. Specific objectives are: (1) improve current algorithms to predict secondary structure from sequence, (2) identify patterns of secondary structure motifs in 3D structures, and (3) investigate the relationship between RNA stability and structure on a molecular level via computation and NMR. Design and methods include: optical melting experiments, in-depth analysis of solved RNA structures, NMR to identify structural properties of RNA motifs, and hydrogen bonding and base stacking calculations. This proposed research is relevant to the NIH mission and AREA grant program objectives. An improved method to predict RNA secondary and tertiary structure from sequence is essential to move RNA research forward. Furthermore, the work should impact researchers in any field relying on RNA structure prediction, especially those attempting to understand the structure-function relationship of RNA, understand RNA interactions 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 knowledge in medical and associated sciences, and benefit students through exposure to and participation in research in the biomedical sciences.
The proposed research will provide essential information to advance RNA research. The data collected 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.
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