Skip to main content
SpringerLink
Log in

Studying equilibria of polymers in solution by direct molecular dynamics simulations: poly(N-isopropylacrylamide) in water as a test case

  • Regular Article
  • Published:
The European Physical Journal Special Topics Aims and scope Submit manuscript

Abstract

It is well known that studying equilibria of polymers in solution by atomistic simulations is computationally demanding as a large phase space has to be adequately sampled. Nevertheless, direct molecular dynamics (MD) simulations are often used for this purpose in the literature. To assess whether such approach is adequate, we have conducted a case study for a polymer + solvent system that has been commonly studied with direct MD simulations by many authors: poly(N-isopropylacrylamide) (PNIPAM) in water. The total simulation time of the present study is much longer than that typically used in MD simulations of that system. A NIPAM chain of 30 monomers was studied in explicit water at 295 K. Three initial configurations were used. For each configuration, five replicas were run for 1000 ns. The statistical analysis of our data shows that the equilibration time is of the order of 600–700 ns and that the remaining time for the production run is not sufficient to sample the equilibrium state adequately. These results underpin the well-known difficulty of sampling equilibrium states of polymers in solution with direct MD simulations and the need for a careful interpretation of results of such studies. The problem with the unsatisfactory sampling persists despite the increasing available computing power. Therefore, enhanced sampling techniques and workarounds, such as simplified scenarios or coarse-graining, remain important.

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

Similar content being viewed by others

References

  1. A. Grosberg, A. Khokhlov, Statistical physics of macromolecules (AIP Press, New York, NY, 1994)

  2. S.M. Mel’nikov, V.G. Sergeyev, K. Yoshikawa, J. Am. Chem. Soc. 117, 2401 (1995)

    Article  Google Scholar 

  3. D. Ito, K. Kubota, Macromolecules 30, 7828 (1997)

    Article  ADS  Google Scholar 

  4. M. Alaghemandi, S. Eckhard, Macromol. Theory Simul. 21, 106 (2011)

    Article  Google Scholar 

  5. S.A. Deshmukh, S.K.R.S. Sankaranarayanan, K. Suthar, D.C. Mancini, J. Phys. Chem. B 116, 2651 (2012)

    Article  Google Scholar 

  6. S.A. Deshmukh, Z. Li, G. Kamath, K.J. Suthar, S.K.R.S. Sankaranarayanan, D.C. Mancini, Polymer 54, 210 (2013)

    Article  Google Scholar 

  7. V. Botan, V. Ustach, R. Faller, K. Leonhard, J. Phys. Chem. B 120, 3434 (2016)

    Article  Google Scholar 

  8. G. Longhi, F. Lebon, S. Abbate, S.L. Fornili, Chem. Phys. Lett. 386, 123 (2004)

    Article  ADS  Google Scholar 

  9. F. Gangemi, G. Longhi, S. Abbate, F. Lebon, R. Cordone, G.P. Ghilardi, S.L. Fornili, J. Phys. Chem. B 112, 11896 (2008)

    Article  Google Scholar 

  10. J. Walter, V. Ermatchkov, J. Vrabec, H. Hasse, Fluid Phase Equilib. 296, 164 (2010)

    Article  Google Scholar 

  11. H. Du, R. Wickramasinghe, X. Qian, J. Phys. Chem. B 114, 16594 (2010)

    Article  Google Scholar 

  12. E. Chiessi, A. Lonardi, G. Paradossi, J. Phys. Chem. B 114, 8301 (2010)

    Article  Google Scholar 

  13. Y. Kang, H. Joo, J.S. Kim, J. Phys. Chem. B 120, 13184 (2016)

    Article  Google Scholar 

  14. T.E. de Oliveira, D. Mukherji, K. Kremer, P.A. Netz, J. Chem. Phys. 146, 034904 (2017)

    Article  ADS  Google Scholar 

  15. T.E. de Oliveira, C.M. Marques, P.A. Netz, Phys. Chem. Chem. Phys. 20, 10100 (2018)

    Article  Google Scholar 

  16. F. Afroze, E. Nies, H. Berghmans, J. Mol. Struct. 554, 55 (2000)

    Article  ADS  Google Scholar 

  17. R. Gomesde Azevedo, L.P.N. Rebelo, A.M. Ramos, J. Szydlowski, H.C. de Sousa, J. Klein, Fluid Phase Equilib. 185, 189 (2001)

    Article  Google Scholar 

  18. A. Milewska, J. Szydlowski, L.P.N. Rebelo, J. Polymer Sci. Part B Polym. Phys. 41, 1219 (2003)

    Article  ADS  Google Scholar 

  19. R. Singh, S.A. Deshmukh, G. Kamath, S.K.R.S. Sankaranarayanan, G. Balasubramanian, Comput. Mater. Sci. 126, 191 (2017)

    Article  Google Scholar 

  20. J.B. Clarage, T. Romo, B.K. Andrews, B.M. Pettitt, G.N. Phillips, Proc. Natl. Acad. Sci. 92, 3288 (1995)

    Article  ADS  Google Scholar 

  21. S. Genheden, U. Ryde, Phys. Chem. Chem. Phys. 14, 8662 (2012)

    Article  Google Scholar 

  22. L. Sawle, K. Ghosh, J. Chem. Theory Comput. 12, 861 (2016)

    Article  Google Scholar 

  23. K. Lindorff-Larsen, S. Piana, R.O. Dror, D.E. Shaw, Science 334, 517 (2011)

    Article  ADS  Google Scholar 

  24. C. Andrea, F. Philippe, C. Amedeo, Proteins Struct. Funct. Bioinf. 47, 305 (2002)

    Article  Google Scholar 

  25. E.J. García, D. Bhandary, M.T. Horsch, H. Hasse, J. Mol. Liq. 268, 294 (2018)

    Article  Google Scholar 

  26. C. Dalgicdir, F. Rodriguez-Ropero, N.F. van der Vegt, J. Phys. Chem. B 121, 7741 (2017)

    Article  Google Scholar 

  27. R.C. Bernardi, M.C. Melo, K. Schulten, Biochim. Biophys. Acta BBA-Gen. Subj. 1850, 872 (2015)

    Article  Google Scholar 

  28. M. Saunders, K.N. Houk, Y.D. Wu, W.C. Still, M. Lipton, G. Chang, W.C. Guida, J. Am. Chem. Soc. 112, 1419 (1990)

    Article  Google Scholar 

  29. T. Kawai, N. Tomioka, T. Ichinose, M. Takeda, A. Itai, Chem. Pharm. Bull. 42, 1315 (1994)

    Article  Google Scholar 

  30. I.T. Jørgensen, J. Comput. Aided Mol. Des. 11, 385 (1997)

    Article  ADS  Google Scholar 

  31. S.K. Schiferl, D.C. Wallace, J. Chem. Phys. 83, 5203 (1985)

    Article  ADS  Google Scholar 

  32. S.P. Brooks, A. Gelman, J. Comput. Graph. Stat. 7, 434 (1998)

    Google Scholar 

  33. W. Yang, R. Bitetti-Putzer, M. Karplus, J. Chem. Phys. 120, 2618 (2004)

    Article  ADS  Google Scholar 

  34. A. Grossfield, D.M. Zuckerman, Annu. Rep. Comput. Chem. 5, 23 (2009)

    Article  Google Scholar 

  35. T.D. Romo, A. Grossfield, J. Chem. Theory Comput. 7, 2464 (2011)

    Article  Google Scholar 

  36. H.B. Mann, Econometrica 13, 245 (1945)

    Article  MathSciNet  Google Scholar 

  37. M.G. Kendall, Rank correlation methods (C. Griffin, London, UK, 1975)

  38. J. Kstner, W. Thiel, J. Chem. Phys. 124, 234106 (2006)

    Article  ADS  Google Scholar 

  39. L.S. Caves, J.D. Evanseck, M. Karplus, Protein Sci. 7, 649 (1998)

    Article  Google Scholar 

  40. E. Chiessi, G. Paradossi, J. Phys. Chem. B 120, 3765 (2016)

    Article  Google Scholar 

  41. S.W.I. Siu, K. Pluhackova, R.A. Böckmann, J. Chem. Theory Comput. 8, 1459 (2012)

    Article  Google Scholar 

  42. G. Bussi, D. Donadio, M. Parrinello, J. Chem. Phys. 126, 014101 (2007)

    Article  ADS  Google Scholar 

  43. H.J.C. Berendsen, J.P.M. Postma, V.W.F. Gunsteren, A. DiNola, J.R. Haak, J. Chem. Phys. 81, 3684 (1984)

    Article  ADS  Google Scholar 

  44. M. Parrinello, A. Rahman, J. Appl. Phys. 52, 7182 (1981)

    Article  ADS  Google Scholar 

  45. T. Darden, D. York, L. Pedersen, J. Chem. Phys. 98, 10089 (1993)

    Article  ADS  Google Scholar 

  46. W.L. Jorgensen, D.S. Maxwell, J. Tirado-Rives, J. Am. Chem. Soc. 118, 11225 (1996)

    Article  Google Scholar 

  47. H.J.C. Berendsen, J.R. Grigera, T.P. Straatsma, J. Phys. Chem. 91, 6269 (1987)

    Article  Google Scholar 

  48. B. Hess, H. Bekker, H.J.C. Berendsen, J.G.E.M. Fraaije, J. Comput. Chem. 18, 1463 (1997)

    Article  Google Scholar 

  49. F.K. Anton, H. Berk, H.J.C. Berendsen, J. Comput. Chem. 20, 786 (1999)

    Article  Google Scholar 

  50. B. Loubet, W. Kopec, H. Khandelia, J. Chem. Theory Comput. 10, 5690 (2014)

    Article  Google Scholar 

  51. K. Olesen, N. Awasthi, D.S. Bruhn, W. Pezeshkian, H. Khandelia, J. Chem. Theory Comput. 14, 3342 (2018)

    Article  Google Scholar 

  52. D. Van Der Spoel, E. Lindahl, B. Hess, G. Groenhof, A.E. Mark, H.J.C. Berendsen, J. Comput. Chem. 26, 1701 (2005)

    Article  Google Scholar 

  53. M.J. Abraham, T. Murtola, R. Schulz, S. Páll, J.C. Smith, B. Hess, E. Lindahl, SoftwareX 1–2, 19 (2015)

    Article  ADS  Google Scholar 

  54. V. Palivec, D. Zadrazil, J. Heyda, arXiv:1806.05592, (2018)

  55. D. Mukherji, K. Kremer, Macromolecules 46, 9158 (2013)

    Article  ADS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratory of Engineering Thermodynamics (LTD), University of Kaiserslautern, Erwin-Schrödinger-Str. 44, 67663, Kaiserslautern, Germany

    Edder J. García & Hans Hasse

Authors
  1. Edder J. García
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hans Hasse
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Edder J. García.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

García, E.J., Hasse, H. Studying equilibria of polymers in solution by direct molecular dynamics simulations: poly(N-isopropylacrylamide) in water as a test case. Eur. Phys. J. Spec. Top. 227, 1547–1558 (2019). https://doi.org/10.1140/epjst/e2018-800171-y

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1140/epjst/e2018-800171-y

Search

Navigation