Bulletin of the Korean Chemical Society

  • 제33권3호
  • /
  • Pages.770-774
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  • 2012
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  • 0253-2964(pISSN)
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  • 1229-5949(eISSN)
대한화학회 (Korean Chemical Society)
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Conformational Sampling of Flexible Ligand-binding Protein Loops

  • Lee, Gyu-Rie (Department of Chemistry, Seoul National University) ;
  • Shin, Woong-Hee (Department of Chemistry, Seoul National University) ;
  • Park, Hahn-Beom (Department of Chemistry, Seoul National University) ;
  • Shin, Seok-Min (Department of Chemistry, Seoul National University) ;
  • Seok, Cha-Ok (Department of Chemistry, Seoul National University)
  • 투고 : 2011.09.30
  • 심사 : 2011.11.10
  • 발행 : 2012.03.20
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초록

Protein loops are often involved in diverse biological functions, and some functional loops show conformational changes upon ligand binding. Since this conformational change is directly related to ligand binding pose and protein function, there have been numerous attempts to predict this change accurately. In this study, we show that it is plausible to obtain meaningful ensembles of loop conformations for flexible, ligand-binding protein loops efficiently by applying a loop modeling method. The loop modeling method employs triaxial loop closure algorithm for trial conformation generation and conformational space annealing for global energy optimization. When loop modeling was performed on the framework of ligand-free structure, loop structures within $3\AA$ RMSD from the crystal loop structure for the ligand-bound state were sampled in 4 out of 6 cases. This result is encouraging considering that no information on the ligand-bound state was used during the loop modeling process. We therefore expect that the present loop modeling method will be useful for future developments of flexible protein-ligand docking methods.

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참고문헌

  1. Rohl, C. A.; Strauss, C. E.; Chivian, D.; Baker, D. Proteins 2004, 55, 656. https://doi.org/10.1002/prot.10629
  2. Soto, C. S.; Fasnacht, M.; Zhu, J.; Forrest, L.; Honig, B. Proteins 2008, 70, 834. https://doi.org/10.1002/prot.21612
  3. Zhu, K.; Pincus, D. L.; Zhao, S.; Friesner, R. A. Proteins 2006, 65, 438. https://doi.org/10.1002/prot.21040
  4. Lee, J.; Lee, D.; Park, H.; Coutsias, E. A.; Seok, C. Proteins 2010, 78, 3428. https://doi.org/10.1002/prot.22849
  5. Fiser, A.; Do, R. K.; Sali, A. Protein Science: A Publication of the Protein Society 2000, 9, 1753. https://doi.org/10.1110/ps.9.9.1753
  6. Martí-Renom, M. A.; Stuart, A. C.; Fiser, A.; Sánchez, R.; Melo, F.; Sali, A. Annual Review of Biophysics and Biomolecular Structure 2000, 29, 291. https://doi.org/10.1146/annurev.biophys.29.1.291
  7. Fernandez-Fuentes, N.; Zhai, J.; Fiser, A. Nucleic Acids Research 2006, 34, W173. https://doi.org/10.1093/nar/gkl113
  8. Fernandez-Fuentes, N.; Oliva, B.; Fiser, A. Nucleic Acids Research 2006, 34, 2085. https://doi.org/10.1093/nar/gkl156
  9. Daga, P. R.; Patel, R. Y.; Doerksen, R. J. Current Topics in Medicinal Chemistry 2010, 10, 84. https://doi.org/10.2174/156802610790232314
  10. Taylor, J. C.; Takusagawa, F.; Markham, G. D. Biochemistry 2002, 41, 9358 https://doi.org/10.1021/bi025851t
  11. Murre, C.; McCaw, P. S.; Vaessin, H.; Caudy, M.; Jan, L. Y.; Jan, Y. N.; Cabrera, C. V.; Buskin, J. N.; Hauschka, S. D.; Lassar, A. B. et al. Cell 1989, 58, 537. https://doi.org/10.1016/0092-8674(89)90434-0
  12. Auffinger, P.; Bielecki, L.; Westhof, E. Chemistry & Biology 2003, 10, 551. https://doi.org/10.1016/S1074-5521(03)00121-2
  13. Weliky, D. P.; Bennett, A. E.; Zvi, A.; Anglister, J.; Steinbach, P. J.; Tycko, R. Nature Structural Biology 1999, 6, 141. https://doi.org/10.1038/5827
  14. Mendieta, J.; Ramírez, G.; Gago, F. Proteins 2001, 44, 460. https://doi.org/10.1002/prot.1111
  15. Ragona, L.; Fogolari, F.; Catalano, M.; Ugolini, R.; Zetta, L.; Molinari, H. The Journal of Biological Chemistry 2003, 278, 38840. https://doi.org/10.1074/jbc.M306269200
  16. Carlson, H. A.; McCammon, J. A. Molecular Pharmacology 2000, 57, 213.
  17. Teague, S. J. Nature Reviews Drug Discovery 2003, 2, 527. https://doi.org/10.1038/nrd1129
  18. Cavasotto, C. N.; Kovacs, J. A.; Abagyan, R. A. Journal of the American Chemical Society 2005, 127, 9632. https://doi.org/10.1021/ja042260c
  19. Guallar, V.; Jacobson, M.; McDermott, A.; Friesner, R. A. Journal of Molecular Biology 2004, 337, 227. https://doi.org/10.1016/j.jmb.2003.11.016
  20. Shehu, A.; Clementi, C.; Kavraki, L. E. Proteins 2006, 65, 164. https://doi.org/10.1002/prot.21060
  21. Murphy, P. M.; Bolduc, J. M.; Gallaher, J. L.; Stoddard, B. L.; Baker, D. Proceedings of the National Academy of Sciences of the United States of America 2009, 106, 9215. https://doi.org/10.1073/pnas.0811070106
  22. Park, H.; Seok, C. in revision. (Modeling of Unreliable Local Regions in Template-based Protein Models)
  23. Lee, J.; Scheraga, H. A.; Rackovsky, S. Journal of Computational Chemistry 1997, 18, 1222. https://doi.org/10.1002/(SICI)1096-987X(19970715)18:9<1222::AID-JCC10>3.0.CO;2-7
  24. Coutsias, E. A.; Seok, C.; Jacobson, M. P.; Dill, K. A. Journal of Computational Chemistry 2004, 25, 510. https://doi.org/10.1002/jcc.10416
  25. Wong, S.; Jacobson, M. P. Proteins 2008, 71, 153. https://doi.org/10.1002/prot.21666
  26. Yang, Y.; Zhou, Y. Proteins 2008, 72, 793. https://doi.org/10.1002/prot.21968
  27. Zhao, S.; Zhu, K.; Li, J.; Friesner, R. A. 2011, in press.
  28. Zhao, Y.; Sanner, M. F. Proteins 2007, 68, 726. https://doi.org/10.1002/prot.21423
  29. Wong, C. F.; Kua, J.; Zhang, Y.; Straatsma, T. P.; McCammon, J. A. Proteins 2005, 61, 850. https://doi.org/10.1002/prot.20688

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