  RNA/protein interactions play crucial roles in controlling gene expression.
They are becoming important targets for pharmaceutical applications. Due to RNA
flexibility and to the strength of electrostatic interactions, standard docking
methods are insufficient. We here present a computational method which allows
studying the binding of RNA molecules and charged peptides with atomistic,
explicit-solvent molecular dynamics. In our method, a suitable estimate of the
electrostatic interaction is used as an order parameter (collective variable)
which is then accelerated using bi-directional pulling simulations. Since the
electrostatic interaction is only used to enhance the sampling, the
approximations used to compute it do not affect the final accuracy. The method
is employed to characterize the binding of TAR RNA from HIV-1 and a small
cyclic peptide. Our simulation protocol allows blindly predicting the binding
pocket and pose as well as the binding affinity. The method is general and
could be applied to study other electrostatics-driven binding events.
