Bulletin of the Korean Chemical Society

Korean Chemical Society (대한화학회)
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Comparative Study of Implicit and Explicit Solvation Models for Probing Tryptophan Side Chain Packing in Proteins

  • Yang, Chang-Won (Department of Chemistry and Institute of Functional Materials, Pusan National University) ;
  • Pak, Young-Shang (Department of Chemistry and Institute of Functional Materials, Pusan National University)
  • Received : 2011.11.10
  • Accepted : 2011.12.29
  • Published : 2012.03.20
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Abstract

We performed replica exchange molecular dynamics (REMD) simulations of the tripzip2 peptide (betahairpin) using the GB implicit and TI3P explicit solvation models. By comparing the resulting free energy surfaces of these two solvation model, we found that the GB solvation model produced a distorted free energy map, but the explicit solvation model yielded a reasonable free energy landscape with a precise location of the native structure in its global free energy minimum state. Our result showed that in particular, the GB solvation model failed to describe the tryptophan packing of trpzip2, leading to a distorted free energy landscape. When the GB solvation model is replaced with the explicit solvation model, the distortion of free energy shape disappears with the native-like structure in the lowest free energy minimum state and the experimentally observed tryptophan packing is precisely recovered. This finding indicates that the main source of this problem is due to artifact of the GB solvation model. Therefore, further efforts to refine this model are needed for better predictions of various aromatic side chain packing forms in proteins.

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References

  1. Kim, E.; Jang, S.; Pak, Y. J. Chem. Phys. 2008, 128(17), 175014.
  2. Kim, E.; Jang, S.; Pak, Y. J. Chem. Phys. 2009, 131(19), 195102. https://doi.org/10.1063/1.3266510
  3. Kim, E.; Jang, S.; Lim, M.; Pak, Y. J. Phys. Chem. B 2010, 114(22), 7686-7691. https://doi.org/10.1021/jp102215j
  4. Bashford, D.; Case, D. A. Annu. Rev. Phys. Chem. 2000, 51, 129- 152. https://doi.org/10.1146/annurev.physchem.51.1.129
  5. Kim, E.; Jang, S.; Pak, Y. J. Chem. Phys. 2007, 127(14), 145104. https://doi.org/10.1063/1.2775450
  6. Wang, J. M.; Cieplak, P.; Kollman, P. A. J. Comput. Chem. 2000, 21(12), 1049-1074. https://doi.org/10.1002/1096-987X(200009)21:12<1049::AID-JCC3>3.0.CO;2-F
  7. Onufriev, A.; Bashford, D.; Case, D. A. Proteins 2004, 55(2), 383- 394. https://doi.org/10.1002/prot.20033
  8. Cochran, A. G.; Skelton, N. J.; Starovasnik, M. A. P Natl. Acad. Sci. USA 2001, 98(10), 5578-5583. https://doi.org/10.1073/pnas.091100898
  9. Guvench, O.; Brooks, C. L. J. Am. Chem. Soc. 2005, 127(13), 4668-4674. https://doi.org/10.1021/ja043492e
  10. Sugita, Y.; Okamoto, Y. Chem. Phys. Lett. 1999, 314(1-2), 141- 151 https://doi.org/10.1016/S0009-2614(99)01123-9
  11. Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. J. Chem. Phys. 1983, 79(2), 926-935. https://doi.org/10.1063/1.445869
  12. Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. J. Chem. Theory Comput. 2008, 4(3), 435-447. https://doi.org/10.1021/ct700301q
  13. Bussi, G.; Donadio, D.; Parrinello, M. J. Chem. Phys. 2007, 126(1), 014101. https://doi.org/10.1063/1.2408420
  14. Berendsen, H. J. C.; Postma, J. P. M.; Vangunsteren, W. F.; Dinola, A.; Haak, J. R. J. Chem. Phys. 1984, 81(8), 3684-3690. https://doi.org/10.1063/1.448118
  15. Rosta, E.; Buchete, N. V.; Hummer, G. J. Chem. Theory Comput. 2009, 5(5), 1393-1399. https://doi.org/10.1021/ct800557h
  16. Palmer, B. J. J. Comp. Phys. 2003, 104(2), 470-472. https://doi.org/10.1006/jcph.1993.1045
  17. Snow, C. D.; Qiu, L. L.; Du, D. G.; Gai, F.; Hagen, S. J.; Pande, V. S. P Natl. Acad. Sci. USA 2004, 101(12), 4077-4082. https://doi.org/10.1073/pnas.0305260101
  18. Hayre, N. R.; Singh, R. R. P.; Cox, D. L. J. Chem. Phys. 2011, 134(3), 035103.
  19. Zhang, C.; Ma, J. P. J. Chem. Phys. 2010, 132(24), 244101. https://doi.org/10.1063/1.3435332