ArticleThe Journal of chemical physics2012
Krylov subspace methods for computing hydrodynamic interactions in brownian dynamics simulations.
Article in The Journal of chemical physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Multiscale modelling of transport in polymer-based reverse-osmosis/nanofiltration membranes: present and future.Discover nano · 2024Review
- Orientationally Averaged Version of the Rotne-Prager-Yamakawa Tensor Provides a Fast but Still Accurate Treatment of Hydrodynamic Interactions in Brownian Dynamics Simulations of Biological Macromolecules.Journal of chemical theory and computation · 2023Article
- Brownian Dynamics Simulations of Biological Molecules.Trends in chemistry · 2019Article
- Whole-Cell Models and Simulations in Molecular Detail.Annual review of cell and developmental biology · 2019Review
- RPYFMM: Parallel Adaptive Fast Multipole Method for Rotne-Prager-Yamakawa Tensor in Biomolecular Hydrodynamics Simulations.Computer physics communications · 2018Article
- Review
- Perspective: On the importance of hydrodynamic interactions in the subcellular dynamics of macromolecules.The Journal of chemical physics · 2016Article
- SOP-GPU: influence of solvent-induced hydrodynamic interactions on dynamic structural transitions in protein assemblies.Journal of computational chemistry · 2016Article
- Effects of confinement on models of intracellular macromolecular dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Evaluation of the Kirkwood approximation for the diffusivity of channel-confined DNA chains in the de Gennes regime.Biomicrofluidics · 2015Article
- Hydrodynamics of DNA confined in nanoslits and nanochannels.The European physical journal. Special topics · 2014Article
- Sliding of proteins non-specifically bound to DNA: Brownian dynamics studies with coarse-grained protein and DNA models.PLoS computational biology · 2014Article
- Physicochemical properties of cells and their effects on intrinsically disordered proteins (IDPs).Chemical reviews · 2014Review
- Dynamic simulation of concentrated macromolecular solutions with screened long-range hydrodynamic interactions: algorithm and limitations.The Journal of chemical physics · 2013Article
- Reaching new levels of realism in modeling biological macromolecules in cellular environments.Journal of molecular graphics & modelling · 2013Review
- A molecule-centered method for accelerating the calculation of hydrodynamic interactions in Brownian dynamics simulations containing many flexible biomolecules.Journal of chemical theory and computation · 2013Article
- Computer Simulations of the Bacterial Cytoplasm.Biophysical reviews · 2013Article
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4 authors.
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Abstract
Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a brownian dynamics simulation. However, the calculation of correlated brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studies methods based on Krylov subspaces for computing brownian noise vectors. These methods are related to Chebyshev polynomial approximations, but do not require eigenvalue estimates. We show that only low accuracy is required in the brownian noise vectors to accurately compute values of dynamic and static properties of polymer and monodisperse suspension models. With this level of accuracy, the computational time of Krylov subspace methods scales very nearly as O(N(2)) for the number of particles N up to 10 000, which was the limit tested. The performance of the Krylov subspace methods, especially the "block" version, is slightly better than that of the Chebyshev method, even without taking into account the additional cost of eigenvalue estimates required by the latter. Furthermore, at N = 10,000, the Krylov subspace method is 13 times faster than the exact Cholesky method. Thus, Krylov subspace methods are recommended for performing large-scale brownian dynamics simulations with hydrodynamic interactions.
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