RNA viruses are one of Nature's most successful self-assembling nanosystems. This Career Award project aims to determine the conformation of ribonucleic acid (RNA) inside viral particles. The conformation of the RNA has remained elusive since the first crystals of viruses were studied 50 years ago. Viral RNA changes conformation as the RNA is replicated, translated, and encapsidated. A viral RNA sequence encodes the structure and the function of the viral RNA, viral proteins, small interfering RNA (siRNA), and target sites for host small RNA. As genome sequencing projects produce increasingly vast amounts of data, the need for tools to interpret genomic sequence information at a structural level becomes increasingly urgent. This research will provide fundamental knowledge to better understand the structure of encapsidated viral RNA, improve predictions of RNA structure from sequence, and thus elucidate dynamic viral RNA structure-function relationships. Satellite tobacco mosaic virus (STMV) will be studied as a small model system to improve viral RNA structure prediction. Excellent crystallographic data for STMV particles has revealed the position and length of RNA helices within the viral particle. A lack of RNA secondary structure information limits the complete modeling of STMV RNA structure. Current programs predict a large number and variety of RNA secondary structures within a small free-energy range, but the lowest energy structures are inconsistent with the crystallography data. The STMV RNA secondary structure will be further probed with chemical modification reagents and site-directed mutagenesis. Prediction programs will be modified to include global restraints, such as the number and length of helices, and to search low energy structures more efficiently. Thermodynamic parameters for RNA secondary structure motifs form the basis for most RNA structure prediction programs and are essential for predictions based on free energy minimization. Although consecutive terminal noncanonical pairs at the ends of RNA helices commonly occur, the thermodynamic parameters for this motif have not been explored. Measuring thermodynamic parameters for RNA also provides an excellent opportunity for undergraduates to apply concepts from physical chemistry and biochemistry courses to a practical biological problem and contribute to an ongoing effort to improve RNA thermodynamic parameters.
The broader impacts of this research include the improvement of the thermodynamic parameters and RNA folding algorithms that are widely used by the RNA research community through the internet. Thousands of scientists use these RNA prediction programs to analyze data, generate hypotheses about RNA structure-function relationships, or design siRNA strategies. The project provides long-term research and educational opportunities for undergraduate, graduate and post doctoral students at the interface of biology, chemistry, and computer science. Students are encouraged to develop skills in the communication of science to the general public through science based displays relating to the research project at the local library.
