2003/12/07 by Dov Bai, Bai, Dov
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · Physics and Astronomy · #Advanced Mathematical Modeling in Engineering #Enzyme Structure and Function #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Protein Structure and Dynamics #Statistical Mechanics (cond-mat.stat-mech) #cond-mat.mtrl-sci #cond-mat.stat-mech
paper · pdf · doi:10.48550/arxiv.cond-mat/0312185
Submitted to Journal of Computational Chemistry
arxiv created 2003/12/07 · openalex publication_date 2003/12/07 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The multiscale Monte-Carlo algorithm outlined in Bai and Brandt[1] is applied to a simple model of the polypeptide backbone. Effective coarse level Hamiltonians are derived by a fast Newtonian iterative scheme. The coarse Hamiltonian parameters are adjusted so that local structural properties have the same value in both coarse and fine level simulations. It is demonstrated that at convergence of iterations, global structural properties are reproduced very well in coarse level simulations.