  Monte Carlo simulations of proteins are hindered by the system's high density
which often makes local moves ineffective. Here we devise and test a set of
long range moves that work well even when all sites of a lattice simulation are
filled. We demonstrate that for a 27-mer cube, the ground state of random
heteropolymers can quickly be reached. We discuss results for 48-mer systems
where the ground state is known exactly. For ten sequences that were examined,
the introduction of long range moves speeds up the search for the ground state
by about one order of magnitude. The method is compared to a fast folding chain
growth algorithm that had previously been used with much success. The new
algorithm here appears to be more efficient. The point is illustrated by the
folding of an 80-mer four-helix bundle considered previously.
