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Computational Study of Human Calcitonin (hCT) Oligomer

  • Published : 2009.12.20

Abstract

We have performed long time REMD simulation on 15-19 residues of human calcitonin hormone (DFNKF) which is known to form highly ordered amyloid fibril. The simulation started from randomly oriented multiple DFNKF strand. Using all-atom level simulations with the generalized Born solvation (GB) model (param99MOD3), we observed spontaneous formation of ${\beta}$-sheet for tetramer. Interestingly, the current simulation gives anti-parallel sheet as a major conformation, consistent with experiments. The major interaction stabilizing the anti-parallel sheet seems to be the inter-strand hydrogen bond.

Keywords

References

  1. Kelly, J. W. Current Opinion in Structural Biology 1998, 8, 101 https://doi.org/10.1016/S0959-440X(98)80016-X
  2. Hardy, J.; Selkoe, D. J. Science 2002, 297, 353 https://doi.org/10.1126/science.1072994
  3. Chiti, F.; Dobson, C. M. Annual Review of Biochemistry 2006, 75, 333 https://doi.org/10.1146/annurev.biochem.75.101304.123901
  4. Westermark, P. Amyloidosis and Amyloid Proteins: Brief History and Definaitions; WILEY-VHC: 2005; Vol. 1
  5. Nelson, R.; Sawaya, M. R.; Balbirnie, M.; Madsen, A. O.; Riekel, C.; Grothe, R.; Eisenberg, D. Nature 2005, 435, 773 https://doi.org/10.1038/nature03680
  6. Tycko, R. Biochemistry 2003, 42, 3151 https://doi.org/10.1021/bi027378p
  7. Zheng, J.; Ma, B. Y.; Nussinov, R. Physical Biology 2006, 3, P1 https://doi.org/10.1088/1478-3975/3/1/001
  8. Caflisch, A. Current Opinion in Chemical Biology 2006, 10, 437 https://doi.org/10.1016/j.cbpa.2006.07.009
  9. Lee, S.; Kim, Y. Bulletin of the Korean Chemical Society 2004, 25, 838 https://doi.org/10.5012/bkcs.2004.25.6.838
  10. Zaidi, M.; Inzerillo, A. M.; Moonga, B. S.; Bevis, P. J. R.; Huang, C. L. H. Bone 2002, 30, 655 https://doi.org/10.1016/S8756-3282(02)00688-9
  11. Reches, M.; Porat, Y.; Gazit, E. Journal of Biological Chemistry 2002, 277, 35475 https://doi.org/10.1074/jbc.M206039200
  12. Naito, A.; Kamihira, M.; Inoue, R.; Saito, H. Magnetic Resonance in Chemistry 2004, 42, 247 https://doi.org/10.1002/mrc.1323
  13. Tsai, H. H. G.; Tsai, C. J.; Ma, B.; Gunasekaran, K.; Zanuy, D.; Nussinov, R. Biophysical Journal 2004, 86, 412A
  14. Tsai, H. H.; Reches, M.; Tsai, C. J.; Gunasekaran, K.; Gazit, E.; Nussinov, R. Proceedings of the National Academy of Sciences of the United States of America 2005, 102, 8174 https://doi.org/10.1073/pnas.0408653102
  15. Tsai, H. H.; Zanuy, D.; Haspel, N.; Gunasekaran, K.; Ma, B. Y.; Tsai, C. J.; Nussinov, R. Biophysical Journal 2004, 87, 146 https://doi.org/10.1529/biophysj.104.040352
  16. Haspel, N.; Zanuy, D.; Ma, B. Y.; Wolfson, H.; Nussinov, R. Journal of Molecular Biology 2005, 345, 1213 https://doi.org/10.1016/j.jmb.2004.11.002
  17. Sugita, Y.; Okamoto, Y. Chem. Phys. Lett. 1999, 314, 141 https://doi.org/10.1016/S0009-2614(99)01123-9
  18. Swendsen, R. H.; Wang, J. S. Phys. Rev. Lett. 1986, 57, 2607 https://doi.org/10.1103/PhysRevLett.57.2607
  19. Walsh, D. M.; Klyubin, I.; Fadeeva, J. V.; Cullen, W. K.; Anwyl, R.; Wolfe, M. S.; Rowan, M. J.; Selkoe, D. J. Nature 2002, 416, 535 https://doi.org/10.1038/416535a
  20. Klein, W. L.; Krafft, G. A.; Finch, C. E. Trends in Neurosciences 2001, 24, 219 https://doi.org/10.1016/S0166-2236(00)01749-5
  21. Gsponer, J.; Haberthur, U.; Caflisch, A. Proceedings of the National Academy of Sciences of the United States of America 2003, 100, 5154 https://doi.org/10.1073/pnas.0835307100
  22. Beglov, D.; Roux, B. Journal of Chemical Physics 1994, 100, 9050 https://doi.org/10.1063/1.466711
  23. Jang, S.; Kim, E.; Pak, Y. Proteins-Structure Function and Bioinformatics 2006, 62, 663 https://doi.org/10.1002/prot.20771
  24. Onufriev, A.; Bashford, D.; Case, D. A. Proteins-Structure Function and Bioinformatics 2004, 55, 383 https://doi.org/10.1002/prot.20033
  25. Jang, S.; Kim, E.; Pak, Y. Proteins-Structure Function and Bioinformatics 2007, 66, 53 https://doi.org/10.1002/prot.21173
  26. Ponder, J. W. TINKER 4.2 : software tools for molecular design; Washington University, 2004
  27. Zagrovic, B.; Sorin, E. J.; Pande, V. Journal of Molecular Biology 2001, 313, 151 https://doi.org/10.1006/jmbi.2001.5033
  28. Hornak, V.; Okur, A.; Rizzo, R. C.; Simmerling, C. Proceedings of the National Academy of Sciences of the United States of America 2006, 103, 915 https://doi.org/10.1073/pnas.0508452103
  29. Palmer, B. J. Journal of Computational Physics 1993, 104, 470 https://doi.org/10.1006/jcph.1993.1045
  30. Rao, F.; Caflisch, A. Journal of Chemical Physics 2003, 119, 4035 https://doi.org/10.1063/1.1591721
  31. Periole, X.; Mark, A. E. Journal of Chemical Physics 2007, 126
  32. Daura, X.; Gademann, K.; Jaun, B.; Seebach, D.; van Gunsteren, W. F.; Mark, A. E. Angewandte Chemie-International Edition 1999, 38, 236 https://doi.org/10.1002/(SICI)1521-3773(19990115)38:1/2<236::AID-ANIE236>3.0.CO;2-M
  33. Affentranger, R.; Tavernelli, I.; Di Iorio, E. E. Journal of Chemical Theory and Computation 2006, 2, 217 https://doi.org/10.1021/ct050250b

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