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A Review of Two Multiscale Methods for the Simulation of Macromolecular Assemblies: Multiscale Perturbation and Multiscale Factorization

Authors: Stephen Pankavich; Peter Ortoleva;

A Review of Two Multiscale Methods for the Simulation of Macromolecular Assemblies: Multiscale Perturbation and Multiscale Factorization

Abstract

Many mesoscopic N-atom systems derive their structural and dynamical properties from processes coupled across multiple scales in space and time. That is, they simultaneously deform or display collective behaviors, while experiencing atomic scale vibrations and collisions. Due to the large number of atoms involved and the need to simulate over long time periods of biological interest, traditional computational tools, like molecular dynamics, are often infeasible for such systems. Hence, in the current review article, we present and discuss two recent multiscale methods, stemming from the N-atom formulation and an underlying scale separation, that can be used to study such systems in a friction-dominated regime: multiscale perturbation theory and multiscale factorization. These novel analytic foundations provide a self-consistent approach to yield accurate and feasible long-time simulations with atomic detail for a variety of multiscale phenomena, such as viral structural transitions and macromolecular self-assembly. As such, the accuracy and efficiency of the associated algorithms are demonstrated for a few representative biological systems, including satellite tobacco mosaic virus (STMV) and lactoferrin.

Keywords

multiscale perturbation theory, Langevin equation, Electronic computers. Computer science, Fokker–Planck equation, QA75.5-76.95, satellite tobacco mosaic virus, multiscale factorization, lactoferrin

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold