Coarse-graining molecular dynamics: stochastic models with non-Gaussian force distributions

Author: 

Erban, R

Publication Date: 

21 September 2019

Journal: 

Journal of Mathematical Biology

Last Updated: 

2020-07-21T02:57:58.21+01:00

abstract: 

Incorporating atomistic and molecular information into models of cellular
behaviour is challenging because of a vast separation of spatial and temporal
scales between processes happening at the atomic and cellular levels.
Multiscale or multi-resolution methodologies address this difficulty by using
molecular dynamics (MD) and coarse-grained models in different parts of the
cell. Their applicability depends on the accuracy and properties of the
coarse-grained model which approximates the detailed MD description. A family
of stochastic coarse-grained (SCG) models, written as relatively
low-dimensional systems of nonlinear stochastic differential equations, is
presented. The nonlinear SCG model incorporates the non-Gaussian force
distribution which is observed in MD simulations and which cannot be described
by linear models. It is shown that the nonlinearities can be chosen in such a
way that they do not complicate parametrization of the SCG description by
detailed MD simulations. The solution of the SCG model is found in terms of
gamma functions.

Symplectic id: 

1048888

Download URL: 

Submitted to ORA: 

Submitted

Publication Type: 

Journal Article