ArticleThe Journal of chemical physics2013
Dynamic simulation of concentrated macromolecular solutions with screened long-range hydrodynamic interactions: algorithm and limitations.
Article in The Journal of chemical physics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Lipoprotein diffusion in dense yolk plasma is governed by softness, hydrodynamics, and caging: Insights from MHz-XPCS.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Size Sensitivity of Metabolite Diffusion in Macromolecular Crowds.Nano letters · 2024Article
- Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models.Nature communications · 2020Article
- Perspective: On the importance of hydrodynamic interactions in the subcellular dynamics of macromolecules.The Journal of chemical physics · 2016Article
- Protein Simulations in Fluids: Coupling the OPEP Coarse-Grained Force Field with Hydrodynamics.Journal of chemical theory and computation · 2015Article
- Article
- Perspective: Reaches of chemical physics in biology.The Journal of chemical physics · 2013Article
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Authors and funding
3 authors.
Funding
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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