ADVANCEMENTS IN COARSE-GRAINED MOLECULAR DYNAMICS: STOCHASTIC MODELS AND NON-GAUSSIAN FORCE DISTRIBUTIONS

• Published in: NeuroQuantology Vol. 19; no. 9; p. 951
• Main Authors: Ammaji, S, Raju, B, Rao, A Srinivasa, Srinivas, B R
• Format: Journal Article
• Language: English
• Published: Bornova Izmir NeuroQuantology 01.01.2021
• Subjects: Accuracy; Atoms & subatomic particles; Crystallography; Differential equations; Force distribution; Gamma function; Molecular dynamics; Nonlinear systems; Nonlinearity; Normal distribution; Parameterization; Simulation; Stochastic models
• ISSN: 1303-5150
• DOI: 10.48047/nq.2021.19.9.NQ21167

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 coarsegrained 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.