Applications of simulated annealing to peptides

Abstract

We report the application of a new conformation searching algorithm called simulated annealing to the location of the global minimum energy conformation of peptides. Simulated annealing is a Metropolis Monte Carlo approach to conformation generation in which both the energy and temperature dependence of the Boltzmann distribution guides the search for the global minimum. Both uphill and downhill moves are possible, which allows the molecule to escape from local minima. Applications to the 20 natural amino acid "dipeptide models" as well as to polyalanines up to Ala80 are very successful in finding the lowest energy conformation. A history file of the simulated annealing process allows reconstruction and examination of the random walk around conformation space. A separate program, Conf-Gen, reads the history file and extracts all low-energy conformations visited during the run.