Literature DB >> 27131531

Hybrid finite element and Brownian dynamics method for charged particles.

Gary A Huber1, Yinglong Miao1, Shenggao Zhou2, Bo Li3, J Andrew McCammon4.   

Abstract

Diffusion is often the rate-determining step in many biological processes. Currently, the two main computational methods for studying diffusion are stochastic methods, such as Brownian dynamics, and continuum methods, such as the finite element method. A previous study introduced a new hybrid diffusion method that couples the strengths of each of these two methods, but was limited by the lack of interactions among the particles; the force on each particle had to be from an external field. This study further develops the method to allow charged particles. The method is derived for a general multidimensional system and is presented using a basic test case for a one-dimensional linear system with one charged species and a radially symmetric system with three charged species.

Year:  2016        PMID: 27131531      PMCID: PMC4851620          DOI: 10.1063/1.4947086

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


  28 in total

1.  Finite element simulations of acetylcholine diffusion in neuromuscular junctions.

Authors:  Kaihsu Tai; Stephen D Bond; Hugh R MacMillan; Nathan Andrew Baker; Michael Jay Holst; J Andrew McCammon
Journal:  Biophys J       Date:  2003-04       Impact factor: 4.033

2.  Brownian dynamics simulations of simplified cytochrome c molecules in the presence of a charged surface.

Authors:  C Gorba; T Geyer; V Helms
Journal:  J Chem Phys       Date:  2004-07-01       Impact factor: 3.488

3.  Hybrid finite element and Brownian dynamics method for diffusion-controlled reactions.

Authors:  Patricia Bauler; Gary A Huber; J Andrew McCammon
Journal:  J Chem Phys       Date:  2012-04-28       Impact factor: 3.488

4.  Hybrid approach combining dissipative particle dynamics and finite-difference diffusion model: simulation of reactive polymer coupling and interfacial polymerization.

Authors:  Anatoly V Berezkin; Yaroslav V Kudryavtsev
Journal:  J Chem Phys       Date:  2013-10-21       Impact factor: 3.488

5.  Computational modeling of three-dimensional electrodiffusion in biological systems: application to the node of Ranvier.

Authors:  Courtney L Lopreore; Thomas M Bartol; Jay S Coggan; Daniel X Keller; Gina E Sosinsky; Mark H Ellisman; Terrence J Sejnowski
Journal:  Biophys J       Date:  2008-06-13       Impact factor: 4.033

6.  Analysis of synaptic transmission in the neuromuscular junction using a continuum finite element model.

Authors:  J L Smart; J A McCammon
Journal:  Biophys J       Date:  1998-10       Impact factor: 4.033

Review 7.  Everything you wanted to know about Markov State Models but were afraid to ask.

Authors:  Vijay S Pande; Kyle Beauchamp; Gregory R Bowman
Journal:  Methods       Date:  2010-06-04       Impact factor: 3.608

8.  Multiscale modeling in rodent ventricular myocytes.

Authors:  Shaoying Lu; Anushka Michailova; Jeffrey Saucerman; Yuhui Cheng; Zeyun Yu; Timothy Kaiser; Wilfred Li; Randolph Bank; Michael Holst; J McCammon; Takeharu Hayashi; Masahiko Hoshijima; Peter Arzberger; Andrew McCulloch
Journal:  IEEE Eng Med Biol Mag       Date:  2009 Mar-Apr

9.  Stochastic binding of Ca2+ ions in the dyadic cleft; continuous versus random walk description of diffusion.

Authors:  Johan Hake; Glenn T Lines
Journal:  Biophys J       Date:  2008-02-08       Impact factor: 4.033

10.  Continuum simulations of acetylcholine consumption by acetylcholinesterase: a Poisson-Nernst-Planck approach.

Authors:  Y C Zhou; Benzhuo Lu; Gary A Huber; Michael J Holst; J Andrew McCammon
Journal:  J Phys Chem B       Date:  2007-12-05       Impact factor: 2.991

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