The multiscale coarse-graining method. I. A rigorous bridge between atomistic and coarse-grained models

2008/06/27 by W. G. Noid, Jhih‐Wei Chu, Jhih-Wei Chu +7 · 888 citations
Biochemistry, Genetics and Molecular Biology · Materials Science · #Block Copolymer Self-Assembly #Computer science #Granularity #Material Dynamics and Properties #Molecular dynamics #Physics #Potential of mean force #Protein Structure and Dynamics #Quantum mechanics #Statistical physics #Thermodynamics #Work (physics)

paper · pdf · doi:10.1063/1.2938860

published in The Journal of Chemical Physics 128(24), 244114 (American Institute of Physics)

openalex publication_date 2008/06/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Coarse-grained (CG) models provide a computationally efficient method for rapidly investigating the long time- and length-scale processes that play a critical role in many important biological and soft matter processes. Recently, Izvekov and Voth introduced a new multiscale coarse-graining (MS-CG) method [J. Phys. Chem. B 109, 2469 (2005); J. Chem. Phys. 123, 134105 (2005)] for determining the effective interactions between CG sites using information from simulations of atomically detailed models. The present work develops a formal statistical mechanical framework for the MS-CG method and demonstrates that the variational principle underlying the method may, in principle, be employed to determine the many-body potential of mean force (PMF) that governs the equilibrium distribution of positions of the CG sites for the MS-CG models. A CG model that employs such a PMF as a "potential energy function" will generate an equilibrium probability distribution of CG sites that is consistent with the atomically detailed model from which the PMF is derived. Consequently, the MS-CG method provides a formal multiscale bridge rigorously connecting the equilibrium ensembles generated with atomistic and CG models. The variational principle also suggests a class of practical algorithms for calculating approximations to this many-body PMF that are optimal. These algorithms use computer simulation data from the atomically detailed model. Finally, important generalizations of the MS-CG method are introduced for treating systems with rigid intramolecular constraints and for developing CG models whose equilibrium momentum distribution is consistent with that of an atomically detailed model.

Citations

• The multiscale coarse-graining method. II. Numerical implementation for coarse-grained molecular models
• Multiscale coarse graining of liquid-state systems

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