DETERMINING THE FOLDING PATHWAYS OF RNA USING LARGE-SCALE OPTIMIZATION

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Large biopolymers (such as proteins and RNA) fold into complex three-dimensional structures that carry out highly specific functions in the cell. The folding process is often regulatory, as only the correct structure carries out function. At the heart of folding (or assembly) are basic physical principles that drive the reaction. Our ability to model these systems is limited by the very large size and complexity of biologically relevant molecules. We have developed an algorithm (KinFold, described in Laederach et al., J Mol Biol, 358, 1179-1190) that identifies the best fitting kinetic models to measures of solvent accessibility based on time-resolved footprinting experiments. The approach exhaustively enumerates all possible kinetic model topologies and identifies the best fitting model topology. We have now collected a series of 7 experiments in which we have folded a large RNA at different temperatures to determine the thermodynamic activation parameters. This data will require testing 84 model topologies for each experimental condition. Each optimization requires 50 hours of CPU on an Intel processor. I would therefore like to request 7x84x50= 29400 CPU hours on the IA 64 cluster at SDSC. Start Date 03/14/2007 00:00:00