Predicting the Spurious Acceleration of Coarse-Grained Molecular Dynamics from Molecular Fluid Structure

Reproducing dynamical properties,
such as diffusion coefficients,
in coarse-grained (CG) molecular dynamics simulations can be challenging
due to the loss of fine-grained details, such as atomic vibrations
and local motions of particles in the parent all-atom (AA) system.
In this study, we present a predictive tool for the mobility acceleration
factor, defined as ratio of the CG diffusion coefficient to the AA
diffusion coefficient. According to the well-established Green–Kubo
formalism, the diffusion coefficient is related to integral of the
velocity autocorrelation function. As integral of the velocity autocorrelation
function is influenced by the particle’s acceleration, key
parameters affecting the acceleration differences between an AA molecule
and its corresponding CG bead are identified to develop a predictive
model. By conducting AA and CG simulations on 20 liquid hydrocarbons
with varying masses and sizes, their mobility acceleration factors
are determined, the largest being 62.78. This data is then used to
fit a nonlinear functional form as the predictive model. The identified
molecular descriptors for the predictive model are easy to calculate
for new molecules, enabling the model to be readily applied to predict
the mobility acceleration factor for different molecules in CG simulations.