ADVANCEMENTS IN COARSE-GRAINED MOLECULAR DYNAMICS: STOCHASTIC MODELS AND NON-GAUSSIAN FORCE DISTRIBUTIONS
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...
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Published in | NeuroQuantology Vol. 19; no. 9; p. 951 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Bornova Izmir
NeuroQuantology
01.01.2021
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 1303-5150 |
DOI: | 10.48047/nq.2021.19.9.NQ21167 |