RNA folding pathway functional intermediates: Their prediction and analysis

The massively parallel genetic algorithm (GA) for RNA structure prediction uses the concepts of mutation, recombination, and survival of the fittest to evolve a population of thousands of possible RNA structures toward a solution structure. As described below, the properties of the algorithm are ideally suited to use in the prediction of possible folding pathways and functional intermediates of RNA molecules given their sequences. Utilizing Stem Trace, an interactive visualization tool for RNA structure comparison, analysis of not only the solution ensembles developed by the algorithm, but also the stages of development of each of these solutions, can give strong insight into these folding pathways. The GA allows the incorporation of information from biological experiments, making it possible to test the influence of particular interactions between structural elements on the dynamics of the folding pathway. These methods are used to reveal the folding pathways of the potato spindle tuber viroid (PSTVd) and the host killing mechanism of Escherichia coli plasmid R1, both of which are successfully explored through the combination of the GA and Stem Trace. We also present novel intermediate folds of each molecule, which appear to be phylogenetically supported, as determined by use of the methods described below.