Literature DB >> 24089734

Dynamic simulation of concentrated macromolecular solutions with screened long-range hydrodynamic interactions: algorithm and limitations.

Tadashi Ando1, Edmond Chow, Jeffrey Skolnick.   

Abstract

Hydrodynamic interactions exert a critical effect on the dynamics of macromolecules. As the concentration of macromolecules increases, by analogy to the behavior of semidilute polymer solutions or the flow in porous media, one might expect hydrodynamic screening to occur. Hydrodynamic screening would have implications both for the understanding of macromolecular dynamics as well as practical implications for the simulation of concentrated macromolecular solutions, e.g., in cells. Stokesian dynamics (SD) is one of the most accurate methods for simulating the motions of N particles suspended in a viscous fluid at low Reynolds number, in that it considers both far-field and near-field hydrodynamic interactions. This algorithm traditionally involves an O(N(3)) operation to compute Brownian forces at each time step, although asymptotically faster but more complex SD methods are now available. Motivated by the idea of hydrodynamic screening, the far-field part of the hydrodynamic matrix in SD may be approximated by a diagonal matrix, which is equivalent to assuming that long range hydrodynamic interactions are completely screened. This approximation allows sparse matrix methods to be used, which can reduce the apparent computational scaling to O(N). Previously there were several simulation studies using this approximation for monodisperse suspensions. Here, we employ newly designed preconditioned iterative methods for both the computation of Brownian forces and the solution of linear systems, and consider the validity of this approximation in polydisperse suspensions. We evaluate the accuracy of the diagonal approximation method using an intracellular-like suspension. The diffusivities of particles obtained with this approximation are close to those with the original method. However, this approximation underestimates intermolecular correlated motions, which is a trade-off between accuracy and computing efficiency. The new method makes it possible to perform large-scale and long-time simulation with an approximate accounting of hydrodynamic interactions.

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Year:  2013        PMID: 24089734      PMCID: PMC3758360          DOI: 10.1063/1.4817660

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


  7 in total

1.  An immersed boundary method for Brownian dynamics simulation of polymers in complex geometries: application to DNA flowing through a nanoslit with embedded nanopits.

Authors:  Yu Zhang; Juan J de Pablo; Michael D Graham
Journal:  J Chem Phys       Date:  2012-01-07       Impact factor: 3.488

2.  Crowding and hydrodynamic interactions likely dominate in vivo macromolecular motion.

Authors:  Tadashi Ando; Jeffrey Skolnick
Journal:  Proc Natl Acad Sci U S A       Date:  2010-10-11       Impact factor: 11.205

3.  Fast computation of many-particle hydrodynamic and electrostatic interactions in a confined geometry.

Authors:  Juan P Hernández-Ortiz; Juan J de Pablo; Michael D Graham
Journal:  Phys Rev Lett       Date:  2007-04-06       Impact factor: 9.161

4.  Krylov subspace methods for computing hydrodynamic interactions in brownian dynamics simulations.

Authors:  Tadashi Ando; Edmond Chow; Yousef Saad; Jeffrey Skolnick
Journal:  J Chem Phys       Date:  2012-08-14       Impact factor: 3.488

Review 5.  Hydrodynamic effects in proteins.

Authors:  Piotr Szymczak; Marek Cieplak
Journal:  J Phys Condens Matter       Date:  2010-12-16       Impact factor: 2.333

6.  Origins of the anomalous stress behavior in charged colloidal suspensions under shear.

Authors:  Amit Kumar; Jonathan J L Higdon
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2010-11-03

7.  Screening of hydrodynamic interactions in semidilute polymer solutions: a computer simulation study.

Authors:  P Ahlrichs; R Everaers; B Dünweg
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2001-09-21
  7 in total
  5 in total

1.  Perspective: Reaches of chemical physics in biology.

Authors:  Martin Gruebele; D Thirumalai
Journal:  J Chem Phys       Date:  2013-09-28       Impact factor: 3.488

2.  Perspective: On the importance of hydrodynamic interactions in the subcellular dynamics of macromolecules.

Authors:  Jeffrey Skolnick
Journal:  J Chem Phys       Date:  2016-09-14       Impact factor: 3.488

3.  A new coarse-grained model for E. coli cytoplasm: accurate calculation of the diffusion coefficient of proteins and observation of anomalous diffusion.

Authors:  Sabeeha Hasnain; Christopher L McClendon; Monica T Hsu; Matthew P Jacobson; Pradipta Bandyopadhyay
Journal:  PLoS One       Date:  2014-09-02       Impact factor: 3.240

4.  Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models.

Authors:  Mohsen Sadeghi; Frank Noé
Journal:  Nat Commun       Date:  2020-06-11       Impact factor: 14.919

5.  Protein Simulations in Fluids: Coupling the OPEP Coarse-Grained Force Field with Hydrodynamics.

Authors:  Fabio Sterpone; Philippe Derreumaux; Simone Melchionna
Journal:  J Chem Theory Comput       Date:  2015-04-14       Impact factor: 6.006

  5 in total

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