The massively parallel genetic algorithm (GA) for RNA structure prediction
uses the concepts of mutation, recombination, and survival of the fittest t
o evolve a population of thousands of possible RNA structures toward a solu
tion structure. As described below, the properties of the algorithm are ide
ally suited to use in the prediction of possible folding pathways and funct
ional intermediates of RNA molecules given their sequences. Utilizing Stem
Trace, an interactive visualization tool for RNA structure comparison, anal
ysis of not only the solution ensembles developed by the algorithm, but als
o the stages of development of each of these solutions, can give strong ins
ight into these folding pathways. The GA allows the incorporation of inform
ation 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 o
f Escherichia coli plasmid R1, both of which are successfully explored thro
ugh the combination of the GA and Stem Trace. We also present novel interme
diate folds of each molecule, which appear to be phylogenetically supported
, as determined by use of the methods described below.