  In this manuscript, we describe a new configurational bias Monte Carlo
technique for the simulation of peptides. We focus on the biologically relevant
cases of linear and cyclic peptides. Our approach leads to an efficient,
Boltzmann-weighted sampling of the torsional degrees of freedom in these
biological molecules, a feat not possible with previous Monte Carlo and
molecular dynamics methods.
