
Anders Irbäck
Professor

Monte Carlo update for chain molecules: Biased Gaussian steps in torsional space
Author
Summary, in English
We develop a new elementary move for simulations of polymer chains in torsion angle space. The method is flexible and easy to implement. Tentative updates are drawn from a (conformation-dependent) Gaussian distribution that favors approximately local deformations of the chain. The degree of bias is controlled by a parameter b. The method is tested on a reduced model protein with 54 amino acids and the Ramachandran torsion angles as its only degrees of freedom, for different b. Without excessive fine tuning, we find that the effective step size can be increased by a factor of 3 compared to the unbiased b = 0 case. The method may be useful for kinetic studies, too.
Department/s
- Computational Biology and Biological Physics - Undergoing reorganization
Publishing year
2001
Language
English
Pages
8154-8158
Publication/Series
Journal of Chemical Physics
Volume
114
Issue
8
Document type
Journal article
Publisher
American Institute of Physics (AIP)
Topic
- Biophysics
Status
Published
ISBN/ISSN/Other
- ISSN: 0021-9606