The Potential, U, is Essential: The many conformations from
a simulation produce a free energy surface. The surface is realistic, if the
force field, FF, is. The database of RNA sequences is exploding, but knowledge
of energetics, structures, and dynamics lags behind. All-atom computational
methods, such as molecular dynamics, hold promise for closing this gap. New
algorithms and faster computers have accelerated progress in improving the
reliability and accuracy of predictions. Currently, the methods can facilitate
refinement of experimentally determined NMR and x-ray structures, but are less
reliable for predictions based only on sequence. Much remains to be discovered,
however, about the many molecular interactions driving RNA folding and the best
way to approximate them quantitatively. The large number of parameters required
means that a wide variety of experimental results will be required to benchmark
force fields and different approaches. As computational methods become more
reliable and accessible, they will be used by an increasing number of
biologists, much as x-ray crystallography has expanded. Thus, many fundamental
physical principles underlying the computational methods are described. This
review presents a summary of the current state of molecular dynamics as applied
to RNA. It is designed to be helpful to students, postdoctoral fellows, and
faculty who are considering or starting computational studies of RNA.