A configurational bias Monte Carlo method for linear and cyclic peptides

Abstract

A new configurational bias Monte Carlo technique is described for the simulation of peptides, focusing on the biologically relevant cases of linear and cyclic peptides. The approach leads to 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.