Tackling Concrete Problems in Molecular Biophysics Using Monte Carlo and Related Methods: Glycosylation, Folding, Solvation

We show how Monte Carlo and related methods as complete enumeration can help to predict and understand the outcomes of concrete biophysical experiments. Three examples are discussed: the eeect of glycosylation on conformational distributions of peptides, the folding of an-helical hairpin model protein, and the structure of a longer cycloamy-lose. One of the major factors hampering the use of Monte Carlo in simulations of detailed models of biomolecular systems is the handling of the aqueous solvent. Here we demonstrate that a combination of atomistic solute model based on a conventional force eld, and continuum solvent model based on the fast solution of the Poisson-Boltzmann equation, is an eecient way of treating the solvent quantitatively in biomolecular Monte Carlo simulations.