Efficient Monte Carlo methods for the computer simulation of biological molecules

We present an alternative approach to efficient Monte Carlo simulations of biological molecules. By relaxing the usual restriction to Markov processes, we are able to optimize performance while dealing directly with the inhomogeneity and anisotropy inherent in these systems. This approach allows us to sample configurational space more efficiently than with either standard Monte Carlo or molecular-dynamics methods.