  We introduce a new procedure to construct weight factors, which flatten the
probability density of the overlap with respect to some pre-defined reference
configuration. This allows one to overcome free energy barriers in the overlap
variable. Subsequently, we generalize the approach to deal with the overlaps
with respect to two reference configurations so that transitions between them
are induced. We illustrate our approach by simulations of the brainpeptide
Met-enkephalin with the ECEPP/2 energy function using the global-energy-minimum
and the second lowest-energy states as reference configurations. The free
energy is obtained as functions of the dihedral and the root-mean-square
distances from these two configurations. The latter allows one to identify the
transition state and to estimate its associated free energy barrier.
