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

Journal article

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.

Authors: Erban, R

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer Nature
• Journal: Journal of Mathematical Biology
• Volume: 80
• Issue: 2020
• Pages: 457-479
• Publication date: 2019-09-21
• Acceptance date: 2019-09-09
• DOI: 10.1007/s00285-019-01433-5
• EISSN: 1432-1416
• ISSN: 0303-6812
• Language: English
• Keywords: Multiscale modelling; Coarse-graining; Molecular dynamics; Brownian dynamics; FFR