  We apply a recently developed method, multicanonical algorithm, to the
problem of tertiary structure prediction of peptides and proteins. As a simple
example to test the effectiveness of the algorithm, Met-enkephalin is studied
and the ergodicity problem, or multiple-minima problem, is shown to be overcome
by this algorithm. The lowest-energy conformation obtained agrees with that
determined by other efficient methods such as Monte Carlo simulated annealing.
The superiority of the present method to simulated annealing lies in the fact
that the relationship to the canonical ensemble remains exactly controlled.
Once the multicanonical parameters are determined, only one simulation run is
necessary to obtain the lowest-energy conformation and furthermore the results
of this one run can be used to calculate various thermodynamic quantities at
any temperature. The latter point is demonstrated by the calculation of the
average potential energy and specific heat as functions of temperature.
