Hierarchical Multiscale Modeling of Macromolecules and their Assemblies

TL;DR

This paper introduces a self-consistent multiscale modeling approach for simulating soft materials, enabling long-time atomic-detail simulations of structural transitions and self-assembly processes.

Contribution

It presents a novel co-evolution method of order parameters and reference structures for improved long-time soft matter simulations.

Findings

Enables calibration-free, atomistic simulations of soft matter.

Successfully models structural transitions and self-assembly.

Derives Langevin equations for coupled order parameter dynamics.

Abstract

Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character of such systems often makes traditional molecular dynamics simulation impractical, a multiscale approach has been presented that allows for long-time simulation with atomic detail based on the co-evolution of slowly-varying order parameters (OPs) with the quasi-equilibrium probability density of atomic configurations. However, this approach breaks down when the structural change is extreme, or when nearest-neighbor connectivity of atoms is not maintained. In the current study, a self-consistent approach is presented wherein OPs and a reference structure co-evolve slowly to yield long-time simulation for dynamical soft-matter phenomena such as structural transitions and self assembly. The development begins with the Liouville equation for N classical atoms and an ansatz on the form of the associated N-atom probability density. Multiscale techniques are used to derive Langevin equations for the coupled OP configurational dynamics. The net result is a set of equations for the coupled stochastic dynamics of the OPs and centers of mass of the subsystems that constitute a soft material body. The theory is based on an all-atom methodology and an interatomic force field, and therefore enables calibration-free simulations of soft matter, such as macromolecular assemblies.