Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T07:42:28.592Z Has data issue: false hasContentIssue false

Rotne–Prager–Yamakawa approximation for different-sized particles in application to macromolecular bead models

Published online by Cambridge University Press:  11 February 2014

P. J. Zuk
Affiliation:
Institute of Theoretical Physics, Faculty of Physics, University of Warsaw, Hoza 69, 00-681 Warsaw, Poland
E. Wajnryb
Affiliation:
Department of Mechanics and Physics of Fluids, Institute of Fundamental and Technological Research, Polish Academy of Sciences, Pawinskiego 5B, 02-106 Warsaw, Poland
K. A. Mizerski
Affiliation:
Department of Magnetism, Institute of Geophysics, Polish Academy of Sciences, ul. Ksiecia Janusza 64, 01-452 Warsaw, Poland
P. Szymczak*
Affiliation:
Institute of Theoretical Physics, Faculty of Physics, University of Warsaw, Hoza 69, 00-681 Warsaw, Poland
*
Email address for correspondence: piotrek@fuw.edu.pl

Abstract

The Rotne–Prager–Yamakawa (RPY) approximation is a commonly used approach to model the hydrodynamic interactions between small spherical particles suspended in a viscous fluid at a low Reynolds number. However, when the particles overlap, the RPY tensors lose their positive definiteness, which leads to numerical problems in the Brownian dynamics simulations as well as errors in calculations of the hydrodynamic properties of rigid macromolecules using bead modelling. These problems can be avoided by using regularizing corrections to the RPY tensors; so far, however, these corrections have only been derived for equal-sized particles. Here we show how to generalize the RPY approach to the case of overlapping spherical particles of different radii and present the complete set of mobility matrices for such a system. In contrast to previous ad hoc approaches, our method relies on the direct integration of force densities over the sphere surfaces and thus automatically provides the correct limiting behaviour of the mobilities for the touching spheres and for a complete overlap, with one sphere immersed in the other one. This approach can then be used to calculate hydrodynamic properties of complex macromolecules using bead models with overlapping, different-sized beads, which we illustrate with an example.

Type
Rapids
Copyright
© 2014 Cambridge University Press 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Antosiewicz, J. & Porschke, D. 1989 Volume correction for bead model simulations of rotational friction coefficients of macromolecules. J. Phys. Chem. 93, 53015305.CrossRefGoogle Scholar
Arya, G., Zhang, Q. & Schlick, T. 2006 Flexible histone tails in a new mesoscopic oligonucleosome model. Biophys. J. 91, 133150.Google Scholar
Banachowicz, E., Gapinski, J. & Patkowski, A. 2000 Solution structure of biopolymers: a new method of constructing a bead model. Biophys. J. 78, 7078.Google Scholar
Bloomfield, V., Dalton, W. O. & Van Holde, K. E. 1967 Frictional coefficients of multisubunit structures. I. Theory. Biopolymers 5, 135148.Google Scholar
Byron, O. 1997 Construction of hydrodynamic bead models from high-resolution X-ray crystallographic or nuclear magnetic resonance data. Biophys. J. 72, 408415.CrossRefGoogle ScholarPubMed
Carrasco, B. & de la Torre, G. J. 1999 Hydrodynamic properties of rigid particles: comparison of different modeling and computational procedures. Biophys. J. 76, 30443057.Google Scholar
Carrasco, B., de la Torre, J. G. & Zipper, P. 1999 Calculation of hydrodynamic properties of macromolecular bead models with overlapping spheres. Eur. Biophys. J. 28, 510515.Google Scholar
Cichocki, B., Felderhof, B. U., Hinsen, K., Wajnryb, E. & Bławzdziewicz, J. 1994 Friction and mobility of many spheres in Stokes flow. J. Chem. Phys. 100, 37803790.CrossRefGoogle Scholar
Cichocki, B., Jones, R. B., Kutteh, R. & Wajnryb, E. 2000 Friction and mobility for colloidal spheres in Stokes flow near a boundary: the multipole method and applications. J. Chem. Phys. 112, 25482561.Google Scholar
Clementi, C. 2008 Coarse-grained models of protein folding. Curr. Opin. Struct. Biol. 18, 1015.CrossRefGoogle ScholarPubMed
Dhont, J. K. G. 1996 An Introduction to Dynamics of Colloids. Elsevier Science.Google Scholar
Długosz, M., Zieliński, P. & Trylska, J. 2011 Brownian dynamics simulations on CPU and GPU with BD BOX. J. Comput. Chem. 32, 27342744.CrossRefGoogle ScholarPubMed
Duguet, E., Désert, A., Perro, A. & Ravaine, S. 2011 Design and elaboration of colloidal molecules: an overview. Chem. Soc. Rev. 40, 941960.Google Scholar
Ermak, D. L. & McCammon, J. A. 1978 Brownian dynamics with hydrodynamic interactions. J. Chem. Phys. 69, 13521360.CrossRefGoogle Scholar
Felderhof, B. U. & Jones, R. B. 1989 Displacement theorems for spherical solutions of the linear Navier–Stokes equations. J. Math. Phys. 30, 339342.CrossRefGoogle Scholar
Frembgen-Kesner, T. & Elcock, A. H. 2009 Striking effects of hydrodynamic interactions on the simulated diffusion and folding of proteins. J. Chem. Theory Comput. 5, 242256.Google Scholar
Geyer, T. 2011 Many-particle Brownian and Langevin dynamics simulations with the Brownmove package. BMC Biophys. 4, 7.CrossRefGoogle ScholarPubMed
Hellweg, T., Eimer, W., Krahn, E., Schneider, K. & Müller, A. 1997 Hydrodynamic properties of nitrogenase – the MoFe protein from Azotobacter vinelandii studied by dynamic light scattering and hydrodynamic modelling. Biochem. Biophys. Acta 1337, 311318.Google Scholar
Hills, R. D. Jr. & Brooks, C. L. III 2009 Insights from coarse-grained Go models for protein folding and dynamics. Intl J. Mol. Sci. 10, 889905.CrossRefGoogle ScholarPubMed
Kim, S. & Karrila, S. J. 1991 Microhydrodynamics: Principles and Selected Applications. Butterworth-Heinemann.Google Scholar
Kirkwood, J. G. & Riseman, J. 1948 The intrinsic viscosities and diffusion constants of flexible macromolecules in solution. J. Chem. Phys. 16, 565573.Google Scholar
Nägele, G. 2006 Brownian dynamics simulations. In Computational Condensed Matter Physics, vol. B4:1 (ed. Blügel, S., Gompper, G., Koch, E., Müller-Krumbhaar, H., Spatschek, R. & Winkler, R. G.), Forschungszentrum Jülich.Google Scholar
Rotne, J. & Prager, S. 1969 Variational treatment of hydrodynamic interaction in polymers. J. Chem. Phys. 50, 48314837.Google Scholar
Szymczak, P. & Cieplak, M. 2007 Proteins in a shear flow. J. Chem. Phys. 127, 155106.CrossRefGoogle Scholar
Szymczak, P. & Cieplak, M. 2011 Hydrodynamic effects in proteins. J. Phys.: Condens. Matter 23, 033102.Google ScholarPubMed
de la Torre, J. G. & Bloomfield, V. A. 1977 Hydrodynamic properties of macromolecular complexes. I. Translation. Biopolymers 16, 17471763.Google Scholar
de la Torre, G. J., Huertas, M. L. & Carrasco, B. 2000 Calculation of hydrodynamic properties of globular proteins from their atomic-level structure. Biophys. J. 78, 719730.Google Scholar
Tozzini, V. 2005 Coarse-grained models for proteins. Curr. Opin. Struct. Biol. 15 (2), 144150.Google Scholar
Wajnryb, E., Mizerski, K. A., Zuk, P. J. & Szymczak, P. 2013 Generalization of the Rotne–Prager–Yamakawa mobility and shear disturbance tensors. J. Fluid Mech. 731, R3.CrossRefGoogle Scholar
Wajnryb, E., Szymczak, P. & Cichocki, B. 2004 Brownian dynamics: divergence of mobility tensor. Physica A 335, 339358.Google Scholar
Zipper, P. & Durchschlag, H. 1997 Calculation of hydrodynamic parameters of proteins from crystallographic data using multibody approaches. Prog. Colloid. Polym. Sci. 107, 5871.Google Scholar
Zurita-Gotor, M., Bławzdziewicz, J. & Wajnryb, E. 2007 Motion of a rod-like particle between parallel walls with application to suspension rheology. J. Rheol. 51, 7197.CrossRefGoogle Scholar
Zwanzig, R., Kiefer, J. & Weiss, G. H. 1968 On the validity of the Kirkwood–Riseman theory. Proc. Natl Acad. Sci. USA 60, 381386.CrossRefGoogle ScholarPubMed