A Configurational Bias Monte Carlo Method for Linear and Cyclic Peptides
Soft Condensed Matter
2015-06-25 v1 q-bio
Abstract
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.
Cite
@article{arxiv.cond-mat/9709330,
title = {A Configurational Bias Monte Carlo Method for Linear and Cyclic Peptides},
author = {Michael W. Deem and Joel Bader},
journal= {arXiv preprint arXiv:cond-mat/9709330},
year = {2015}
}
Comments
19 pages, LaTeX. Figures 3-9 available in PostScript