Skip to main content
SpringerLink
Log in

In situ synthesis and simulation of polydisperse amphiphilic membranes

  • Published:
International Journal of Advances in Engineering Sciences and Applied Mathematics Aims and scope Submit manuscript

Abstract

The field of coarse-grained simulations of biopolymers and membranes has grown rapidly in recent years. Industrial groups manufacture and use polymers in fields as diverse as chemicals processing and personal care products, while academic researchers are interested in uncovering fundamental relations between molecular structure and macroscopic material properties. Biological membranes such as the cellular plasma membrane are of great interest to life scientists because of their role in cellular function. Experimental systems are usually polydisperse, and the cellular plasma membrane contains hundreds of distinct molecule types. Many coarse-grained simulation techniques have been used to explore amphiphilic membrane material properties and dynamics, but they typically contain only one or two species of molecule. They also require the precise configuration of the molecular components of a simulation to be specified in advance by the user to avoid the time-consuming stage of aggregate self-assembly. We describe here how a planar amphiphilic membrane is created by synthesizing each of its constituent molecules in situ according to user-defined growth rules that set the composition and molecular polydispersity, and subsequently simulated using dissipative particle dynamics. We explore the effects of polydispersity on the membrane material properties. The ability to synthesize and simulate polydisperse molecular aggregates may provide a simpler path to relating simulated and natural amphiphilic aggregates.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Engelman, D.M.: Membranes are more mosaic than fluid. Nature 438, 578–580 (2005)

    Article  Google Scholar 

  2. Singer, S.J., Nicolson, G.L.: The fluid mosaic model of the structure of cell membranes. Science 175, 720–731 (1972)

    Article  Google Scholar 

  3. Allen, M.P., Tildesley, D.J.: Computer Simulations of Liquids. Oxford University Press, Oxford (2007)

    MATH  Google Scholar 

  4. Frenkel, D., Smit, B.: Understanding Molecular Simulation: From Algorithms to Applications. Academic Press, Elsevier, San Diego (2002)

    MATH  Google Scholar 

  5. Monticelli, L., Salonen, E. (eds): Biomolecular Simulations. Methods in Molecular Biology 924. Humana Press, Springer (2012)

  6. Shillcock, J.C.: Spontaneous vesicle self-assembly: a mesoscopic view of membrane dynamics. Langmuir 28, 541–547 (2012)

    Article  Google Scholar 

  7. Israelachvili, J.: Intermolecular and Surface Forces, 2nd edn. Academic Press, London (1992)

    Google Scholar 

  8. Venturoli, M., Sperotto, M.M., Kranenburg, M., Smit, B.: Mesoscopic models of biological membranes. Phys. Rep. 437, 1–54 (2006)

    Article  Google Scholar 

  9. Goetz, R., Lipowsky, R.: Computer simulations of bilayer membranes: self-assembly and interfacial tension. J. Chem. Phys. 108, 7397–7409 (1998)

    Article  Google Scholar 

  10. Marrink, S.J., Risselada, H.J., Yefimov, S., Tieleman, D.P., de Vries, A.H.: The MARTINI force field: coarse grained model for biomolecular simulations. J. Phys. Chem. B. 111, 7812–7824 (2007)

    Article  Google Scholar 

  11. Ortiz, V., Nielsen, S.O., Discher, D.E., Klein, M.L., Lipowsky, R., Shillcock, J.: Dissipative particle dynamics simulations of polymersomes. J. Phys. Chem. B. 109, 17708–17714 (2005)

    Article  Google Scholar 

  12. Shillcock, J.C., Lipowsky, R.: Equilibrium structure and lateral stress distribution of amphiphilic bilayers from dissipative particle dynamics simulations. J. Chem. Phys. 117, 5048–5061 (2002)

    Article  Google Scholar 

  13. Venturoli, M., Smit, B.: Simulating the self-assembly of model membranes. PhysChemComm 10, 45–49 (1999)

    Article  Google Scholar 

  14. Cooke, I.R., Kremer, K., Deserno, M.: Tunable generic model for fluid bilayer membranes. Phys. Rev. E 72, 011506 (2005)

    Article  Google Scholar 

  15. Sevink, G.J.A., Fraaije, J.G.E.M.: Efficient solvent-free dissipative particle dynamics for lipid bilayers. Soft Matter 10, 5129–5146 (2014)

    Article  Google Scholar 

  16. Illya, G., Lipowsky, R., Shillcock, J.C.: Two-component membrane material properties and domain formation from dissipative particle dynamics. J. Chem. Phys. 125, 114710 (2006)

    Article  Google Scholar 

  17. Laradji, M., Sunil Kumar, P.B.: Domain growth, budding, and fission in phase-separating self-assembled fluid bilayers. J. Chem. Phys. 123, 224902 (2005)

    Article  Google Scholar 

  18. Yang, K., Ma, Y.-Q.: Computer simulations of vesicle fission induced by external amphipathic inclusions. J. Phys. Chem. B. 113, 1048–1057 (2009)

    Article  Google Scholar 

  19. Grafmüller, A., Shillcock, J., Lipowsky, R.: The fusion of membranes and vesicles: pathway and energy barriers from dissipative particle dynamics. Biophys. J. 96, 2658–2675 (2009)

    Article  Google Scholar 

  20. Marrink, S.J., Mark, A.E.: The mechanism of vesicle fusion as revealed by molecular dynamics simulations. JACS 125, 11144–11145 (2003)

    Article  Google Scholar 

  21. Müller, M., Katsov, K., Schick, M.: A new mechanism of model membrane fusion determined from Monte Carlo simulations. Biophys. J. 85, 1611–1623 (2003)

    Article  Google Scholar 

  22. Shillcock, J.C., Lipowsky, R.: Tension-induced fusion of bilayer membranes and vesicles. Nat. Mater. 4, 225–228 (2005)

    Article  Google Scholar 

  23. Stevens, M.J., Hoh, J.H., Woolf, T.B.: Insights into the molecular mechanism of membrane fusion from simulation: evidence for the association of splayed tails. PRL 91, 188102 (2003)

    Article  Google Scholar 

  24. Yang, K., Ma, Y.-Q.: Computer simulation of the translocation of nanoparticles with different shapes across a lipid bilayer. Nat. Nano. 5, 579–583 (2010)

    Article  Google Scholar 

  25. Marrink, S.J., Tieleman, D.P., Mark, A.E.: Molecular dynamics simulation of the kinetics of spontaneous micelle formation. J. Phys. Chem. B 104, 12165–12173 (2000)

    Article  Google Scholar 

  26. Zhou, Y., Xia, H., Long, X., Xue, X., Qian, W.: Complex multicompartment micelles from simple ABC linear triblock copolymers in solution. Macromol. Theory Simul. 24, 85–88 (2015)

    Article  Google Scholar 

  27. Altendorf, H., Jeulin, D.: Random-walk-based stochastic modeling of three-dimensional fiber systems. Phys. Rev. E 83, 041804 (2011)

    Article  MATH  Google Scholar 

  28. Gaiselmann, G., Stenzel, O., Kruglova, A., Muecklich, F., Schmidt, V.: Competitive stochastic growth model for the 3D morphology of eutectic Si in Al–Si alloys. Comput. Mater. Sci. 69, 289–298 (2013)

    Article  Google Scholar 

  29. Hoogerbrugge, P.J., Koelman, J.M.V.A.: Simulating microscopic hydrodynamic phenomena with dissipative particle dynamics. Europhys. Lett. 19, 155–160 (1992)

    Article  Google Scholar 

  30. Español, P., Warren, P.: Statistical mechanics of dissipative particle dynamics. Europhys. Lett. 30, 191–196 (1995)

    Article  Google Scholar 

  31. Groot, R.D., Warren, P.B.: Dissipative particle dynamics: bridging the gap between atomistic and mesoscopic simulation. J. Chem. Phys. 107, 4423–4435 (1997)

    Article  Google Scholar 

  32. Illya, G., Lipowsky, R., Shillcock, J.C.: Effect of chain length and asymmetry on material properties of bilayer membranes. J. Chem. Phys. 122, 244901 (2005)

    Article  Google Scholar 

  33. Martinez, L., Andrade, R., Birgin, E.G., Martinez, J.M.: Packmol: a package for building configurations for molecular dynamics simulations. J. Comp. Chem. 30(13), 2157–2164 (2009)

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by funding from the ETH Domain for the Blue Brain Project (BBP) and funding to the Human Brain Project from the European Union Seventh Framework Programme (FP7/2007-2013) under Grant agreement No. 604102 (HBP). The BlueBrain IV BlueGene/Q system is financed by the ETH Board Funding to the Blue Brain Project as a National Research Infrastructure and hosted at the Swiss National Supercomputing Center (CSCS).

Author information

Authors and Affiliations

  1. Blue Brain Project, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Liesbeth Vanherpe, Lida Kanari, Guy Atenekeng, Juan Palacios & Julian Shillcock

Authors
  1. Liesbeth Vanherpe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lida Kanari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guy Atenekeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Juan Palacios
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Julian Shillcock
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Julian Shillcock.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vanherpe, L., Kanari, L., Atenekeng, G. et al. In situ synthesis and simulation of polydisperse amphiphilic membranes. Int J Adv Eng Sci Appl Math 8, 126–133 (2016). https://doi.org/10.1007/s12572-015-0156-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12572-015-0156-8

Keyword

Search

Navigation