  We present a novel Monte Carlo algorithm which enhances equilibrization of
low-temperature simulations and allows sampling of configurations over a large
range of energies. The method is based on a non-Boltzmann probability weight
factor and is another version of the so-called generalized-ensemble techniques.
The effectiveness of the new approach is demonstrated for the system of a small
peptide, an example of the frustrated system with a rugged energy landscape.
