Literature DB >> 26646864

Combining molecular dynamics with mesoscopic Green's function reaction dynamics simulations.

Adithya Vijaykumar1, Peter G Bolhuis2, Pieter Rein ten Wolde1.   

Abstract

In many reaction-diffusion processes, ranging from biochemical networks, catalysis, to complex self-assembly, the spatial distribution of the reactants and the stochastic character of their interactions are crucial for the macroscopic behavior. The recently developed mesoscopic Green's Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. We propose a novel approach that combines GFRD for simulating the system at the mesoscopic scale where particles are far apart, with a microscopic technique such as Langevin dynamics or Molecular Dynamics (MD), for simulating the system at the microscopic scale where reactants are in close proximity. This scheme defines the regions where the particles are close together and simulated with high microscopic resolution and those where they are far apart and simulated with lower mesoscopic resolution, adaptively on the fly. The new multi-scale scheme, called MD-GFRD, is generic and can be used to efficiently simulate reaction-diffusion systems at the particle level.

Entities:  

Year:  2015        PMID: 26646864     DOI: 10.1063/1.4936254

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  4 in total

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Authors:  Sumantra Sarkar; Angel E García
Journal:  Biophys J       Date:  2020-03-14       Impact factor: 4.033

2.  Stochastic self-tuning hybrid algorithm for reaction-diffusion systems.

Authors:  Á Ruiz-Martínez; T M Bartol; T J Sejnowski; D M Tartakovsky
Journal:  J Chem Phys       Date:  2019-12-28       Impact factor: 3.488

3.  Concentration sensing in crowded environments.

Authors:  Wylie Stroberg; Santiago Schnell
Journal:  Biophys J       Date:  2021-03-04       Impact factor: 4.033

4.  Stochastic model of ERK-mediated progesterone receptor translocation, clustering and transcriptional activity.

Authors:  Tatiana T Marquez-Lago; Stanly Steinberg
Journal:  Sci Rep       Date:  2022-07-11       Impact factor: 4.996

  4 in total

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