The European Physical Journal Special Topics

, Volume 224, Issue 12, pp 2289–2304 | Cite as

Advantages and challenges in coupling an ideal gas to atomistic models in adaptive resolution simulations

  • K. KreisEmail author
  • A. C. Fogarty
  • K. Kremer
  • R. Potestio
Regular Article A. Representation of Molecular Systems Across Scales
Part of the following topical collections:
  1. Discussion and Debate: Recurrent Problems in Scale Bridging Techniques in Molecular Simulation – What are the Current Options?


In adaptive resolution simulations, molecular fluids are modeled employing different levels of resolution in different subregions of the system. When traveling from one region to the other, particles change their resolution on the fly. One of the main advantages of such approaches is the computational efficiency gained in the coarse-grained region. In this respect the best coarse-grained system to employ in the low resolution region would be the ideal gas, making intermolecular force calculations in the coarse-grained subdomain redundant. In this case, however, a smooth coupling is challenging due to the high energetic imbalance between typical liquids and a system of non-interacting particles. In the present work, we investigate this approach, using as a test case the most biologically relevant fluid, water. We demonstrate that a successful coupling of water to the ideal gas can be achieved with current adaptive resolution methods, and discuss the issues that remain to be addressed.


European Physical Journal Special Topic Atomistic Simulation Atomistic Region Drift Force Soft Matter System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    G. Grest, K. Kremer, Phys. Rev. A 33, 3628 (1986)CrossRefADSGoogle Scholar
  2. 2.
    K. Kremer, G. Grest, I. Carmesin, Phys. Rev. Lett. 61, 566 (1988)CrossRefADSGoogle Scholar
  3. 3.
    L. Yelash, M. Müller, W. Paul, K. Binder, J. Chem. Theory Comput. 2, 588 (2006)CrossRefGoogle Scholar
  4. 4.
    T. Spyriouni, C. Tzoumanekas, D. Theodorou, F. Müller-Plathe, G. Milano, Macromolecules 40, 3876 (2007)CrossRefADSGoogle Scholar
  5. 5.
    J. McCammon, M. Karplus, Nature 268, 765 (1977)CrossRefADSGoogle Scholar
  6. 6.
    M. Karplus, J. McCammon, Nature 277, 578 (1979)CrossRefADSGoogle Scholar
  7. 7.
    P. Raiteri, A. Laio, F.L. Gervasio, C. Micheletti, M. Parrinello, J. Phys. Chem. B 110, 3533 (2006)CrossRefGoogle Scholar
  8. 8.
    H. Lou, R.I. Cukier, J. Phys. Chem. B 110, 12796 (2006)CrossRefGoogle Scholar
  9. 9.
    K. Arora, C.L. Brooks, Proc. Natl. Acad. Sci. USA 104, 18496 (2007)CrossRefADSGoogle Scholar
  10. 10.
    F. Pontiggia, A. Zen, C. Micheletti, Biophys. J 95, 5901 (2008)CrossRefGoogle Scholar
  11. 11.
    M.M. Tirion, D. ben Avraham, J. Mol. Biol. 230, 186 (1993)CrossRefGoogle Scholar
  12. 12.
    M.M. Tirion, Phys. Rev. Lett. 77, 1905 (1996)CrossRefADSGoogle Scholar
  13. 13.
    I. Bahar, A.R. Atilgan, B. Erman, Folding Design 2, 173 (1997)CrossRefGoogle Scholar
  14. 14.
    C. Micheletti, P. Carloni, A. Maritan, Proteins 55, 635 (2004)CrossRefGoogle Scholar
  15. 15.
    R. Potestio, F. Pontiggia, C. Micheletti, Biophys. J 96, 4993 (2009)CrossRefGoogle Scholar
  16. 16.
    C. Globisch, V. Krishnamani, M. Deserno, C. Peter, PLoS ONE 8, e60582 (2013)CrossRefADSGoogle Scholar
  17. 17.
    K. Kremer, Computer simulations in soft matter science, Vol. 53 (IOP Publishing Ltd., 2000), p. 145Google Scholar
  18. 18.
    K. Kremer, F. Müller-Plathe, MRS Bulletin 26, 205 (2001)CrossRefGoogle Scholar
  19. 19.
    N.A. van der Vegt, C. Peter, K. Kremer, Structure-Based Coarse- and Fine-Graining in Soft Matter Simulations, (CRC Press – Taylor and Francis Group, 2009), p. 379Google Scholar
  20. 20.
    C. Hijón, E. Vanden-Eijnden, R. Delgado-Buscalioni, P. Español, Farad. Discuss. 144, 301 (2010)CrossRefADSGoogle Scholar
  21. 21.
    W. Noid, Systematic methods for structurally consistent coarse-grained models, Vol. 924 (Humana Press, 2013), p. 487Google Scholar
  22. 22.
    W.G. Noid, J. Chem. Phys. 139, 090901 (2013)CrossRefADSGoogle Scholar
  23. 23.
    M. Praprotnik, L. Delle Site, K. Kremer, J. Chem. Phys. 123, 224106 (2005)CrossRefADSGoogle Scholar
  24. 24.
    M. Praprotnik, L. Delle Site, K. Kremer, Phys. Rev. E. 73, 066701 (2006)CrossRefADSGoogle Scholar
  25. 25.
    M. Praprotnik, L. Delle Site, K. Kremer, J. Chem. Phys. 126, 134902 (2007)CrossRefADSGoogle Scholar
  26. 26.
    M. Praprotnik, L. Delle Site, K. Kremer, Ann. Rev. Phys. Chem. 59, 545 (2008)CrossRefADSGoogle Scholar
  27. 27.
    S. Fritsch, C. Junghans, K. Kremer, J. Chem. Theory Comput. 8, 398 (2012)CrossRefGoogle Scholar
  28. 28.
    A.B. Poma, L.D. Site, Phys. Rev. Lett. 104, 250201 (2010)CrossRefADSGoogle Scholar
  29. 29.
    R. Potestio, L. Delle Site, J. Chem. Phys. 136, 054101 (2012)CrossRefADSGoogle Scholar
  30. 30.
    B. Ensing, S. Nielsen, P. Moore, M. Klein, M. Parrinello, J. Chem. Theor. Comp. 3, 1100 (2007)CrossRefGoogle Scholar
  31. 31.
    M. Praprotnik, S. Poblete, L. Delle Site, K. Kremer, Phys. Rev. Lett. 107, 099801 (2011)CrossRefADSGoogle Scholar
  32. 32.
    S. Fritsch, S. Poblete, C. Junghans, G. Ciccotti, L. Delle Site, K. Kremer, Phys. Rev. Lett. 108, 170602 (2012)CrossRefADSGoogle Scholar
  33. 33.
    R. Potestio, S. Fritsch, P. Español, R. Delgado-Buscalioni, K. Kremer, R. Everaers, D. Donadio, Phys. Rev. Lett. 110, 108301 (2013)CrossRefADSGoogle Scholar
  34. 34.
    R. Potestio, P. Español, R. Delgado-Buscalioni, R. Everaers, K. Kremer, D. Donadio, Phys. Rev. Lett. 111, 060601 (2013)CrossRefADSGoogle Scholar
  35. 35.
    A. Agarwal, H. Wang, C. Schütte, L.D. Site, J. Chem. Phys. 141, 034102 (2014)CrossRefADSGoogle Scholar
  36. 36.
    K. Kreis, D. Donadio, K. Kremer, R. Potestio, Europhys. Lett. 108, 30007 (2014)CrossRefGoogle Scholar
  37. 37.
    P. Español, R. Delgado-Buscalioni, R. Everaers, R. Potestio, D. Donadio, K. Kremer, J. Chem. Phys. 142, 064115 (2015)CrossRefADSGoogle Scholar
  38. 38.
    B. Mukherjee, L. Delle Site, K. Kremer, C. Peter, J. Phys. Chem. B. 116, 8474 (2012)CrossRefGoogle Scholar
  39. 39.
    B. Mukherjee, C. Peter, K. Kremer, Phys. Rev. E. 88, 010502 (2013)CrossRefADSGoogle Scholar
  40. 40.
    D. Reith, M. Putz, F. Müller-Plathe, J. Comp. Chem. 24, 1624 (2003)CrossRefGoogle Scholar
  41. 41.
    H. Wang, C. Junghans, K. Kremer, Eur. Phys. J. E 28, 221 (2009)CrossRefGoogle Scholar
  42. 42.
    L. Delle Site, Phys. Rev. E. 76, 047701 (2007)CrossRefADSGoogle Scholar
  43. 43.
    H. Wang, C. Hartmann, C. Schütte, L. Delle Site, Phys. Rev. X 3, 011018 (2013)Google Scholar
  44. 44.
    J. Kirkwood, J. Chem. Phys. 3, 300 (1935)CrossRefADSGoogle Scholar
  45. 45.
    J.D. Halverson, T. Brandes, O. Lenz, A. Arnold, S. Bevc, V. Starchenko, K. Kremer, T. Stühn, D. Reith, Comput. Phys. Commun. 184, 1129 (2013)CrossRefADSGoogle Scholar
  46. 46.
    H. Berendsen, J. Grigera, T. Straatsma, J. Phys. Chem. 91, 6269 (1987)CrossRefGoogle Scholar
  47. 47.
    S. Miyamoto, P.A. Kollman, J. Comput. Chem. 13, 952 (1992)CrossRefGoogle Scholar
  48. 48.
    D. Mukherji, N.F.A. van der Vegt, K. Kremer, L. Delle Site, J. Chem. Theory Comput. 8, 375 (2012)CrossRefGoogle Scholar
  49. 49.
    V. Rühle, C. Junghans, A. Lukyanov, K. Kremer, D. Andrienko, J. Chem. Theory Comput. 5, 3211 (2009)CrossRefGoogle Scholar

Copyright information

© EDP Sciences and Springer 2015

Authors and Affiliations

  • K. Kreis
    • 1
    • 2
    Email author
  • A. C. Fogarty
    • 1
  • K. Kremer
    • 1
  • R. Potestio
    • 1
  1. 1.Max-Planck-Institute for Polymer ResearchMainzGermany
  2. 2.Graduate School Materials Science in MainzMainzGermany

Personalised recommendations