Entropic sampling of freely-rotating polymer chains

Authors

  • A.A. Yurchenko
  • P.N. Vorontsov-Velyaminov

Keywords:

Монте-Карло
моделирование
алгоритм Ванга-Ландау
полимеры
полипептиды
термодинамика

Abstract

In this paper we discuss some simulation results of freely-rotating models for polymer chains. Computer modeling was carried out by Monte Carlo methods within the Wang-Landau algorithm. For models of n-alkanes and polypeptides (polyglycines), distribution energy functions were obtained. They allowed us to calculate canonical values of internal energy, heat capacity and excess entropy, average radius of inertia, and end-to-end distance. For n-alkanes we used parameters of the OPLS force field, whereas for polyglycines we used parameters of the CHARMM force field.

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Published

2006-11-29

Issue

Vol. 7 (2006): Issue 4.

Section

Section 1. Numerical methods and applications

Author Biographies

A.A. Yurchenko

St Petersburg University,
Faculty of Physics

P.N. Vorontsov-Velyaminov

St Petersburg University,
Faculty of Physics

References

  1. Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., Teller E. Equation of state calculations by fast computing machines // J. Chem. Phys. 1953. 21. 1087-1092.
  2. Binder K. Monte Carlo methods in statistical physics. Berlin: Springer-Verlag, 1979.
  3. Allen M.P., Tildesley D.J. Computer simulation of liquids. Oxford: Clarendon, 1987.
  4. Iba Y. Extended ensemble Monte Carlo // Int. J. Mod. Phys. C. 2001. 12. 623-656.
  5. Mitsutake A., Sugita Y., Okamoto Y. Generalized-ensemble algorithms for molecular simulations of biopolymers // Biopolymers. 2001. 60. 96-123.
  6. Lyubartsev A.P., Martsinovskii A.A., Shevkunov S.V., Vorontsov-Velyaminov P.N. New approach to Monte Carlo calculation of the free energy: Method of expanded ensembles // J. Chem. Phys. 1992. 96. 1776-1783.
  7. Marinari E., Parisi G. Simulated tempering: A new Monte Carlo scheme // Europhys. Lett. 1992. 19. 451-458.
  8. Berg B.A., Neuhaus T. Multicanonical ensemble: A new approach to simulate first-order phase transitions // Phys. Rev. Lett. 1992. 68. 9-12.
  9. Lee J. New Monte Carlo algorithm: Entropic sampling // Phys. Rev. Lett. 1993. 71. 211-214.
  10. Wang F., Landau D.P. Efficient, multiple-range random walk algorithm to calculate the density of states // Phys. Rev. Lett. 2001. 86. 2050-2053.
  11. Vorontsov-Velyaminov P.N., Volkov N.A., Yurchenko A.A. Entropic sampling of simple polymer models within Wang- Landau algorithm // J. Phys. A: Math. Gen. 2004. 37. 1573-1588.
  12. Volkov N.A., Yurchenko A.A., Lyubartsev A.P., Vorontsov-Velyaminov P.N. Entropic sampling of free and ring polymer chains // Macromol. Theory Simul. 2005. 14. 491-504.
  13. Ландау Л.Д., Лифшиц Е.М. Статистическая физика. М.: Наука, 1964.
  14. Jorgensen W.L., Madura J.D., Swenson C. J. Optimized intermolecular potential functions for liquid hydrocarbons // J. Am. Chem. Soc. 1984. 106. 6638-6646.
  15. Goldstein H. Classical mechanics. Cambridge: Addison-Wesley Press, 1950.
  16. Brooks C.L., Bruccoleri R.E., Olafson B.D., States D.J., Swamiathas S., Karplus M. CHARMM: A program for macromolecular energy, minimization and dynamic calculation // J. Comput. Chem. 1983. 4, N 1. 187-217.

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