Journal of Biomolecular NMR

, Volume 20, Issue 3, pp 223–231 | Cite as

A novel interactive tool for rigid-body modeling of multi-domain macromolecules using residual dipolar couplings

  • Patrice Dosset
  • Jean-Christophe Hus
  • Dominique Marion
  • Martin Blackledge

Abstract

Residual dipolar couplings (RDC), measured by dissolving proteins in dilute liquid crystal media, or by studying naturally paramagnetic molecules, have rapidly become established as routine measurements in the investigation of the structure of macromolecules by NMR. One of the most obvious applications of the previously inaccessible long-range angular information afforded by RDC is the accurate definition of domain orientation in multi-module macromolecules or complexes. In this paper we describe a novel program developed to allow the determination of alignment tensor parameters for individual or multiple domains in macromolecules from residual dipolar couplings and to facilitate their manipulation to construct low-resolution models of macromolecular structure. For multi-domain systems the program determines the relative orientation of individual structured domains, and provides graphical user-driven rigid-body modeling of the different modules relative to the common tensorial frame. Translational freedom in the common frame, and equivalent rotations about the diagonalized (x,y,z) axes are used to position the different modules in the common frame to find a model in best agreement with experimentally measured couplings alone or in combination with additional experimental or covalent information.

alignment tensor liquid crystal modular domains partial alignment residual dipolar coupling rigid body modeling 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Al-Hashimi, H., Valafar, H., Terrell, M., Zartler, M., Eidsness, M. and Prestegard, J.H. (2000) J. Magn. Reson., 143, 402-406.Google Scholar
  2. Annila, A., Aitio, H., Thulin, E. and Drakenberg, T. (1999) J. Biomol. NMR, 14, 223-230.Google Scholar
  3. Brüschweiler, R., Liao, X. and Wright, P. (1995) Science, 268, 886-889.Google Scholar
  4. Cai, M., Huang, Y., Zheng, R., Wei, S., Ghirlando, R., Lee, M., Craigie, R., Gronenborn, A.M. and Clore, G.M. (1998) Nat. Struct. Biol., 5, 903-909.Google Scholar
  5. Clore, G.M. (2000) Proc. Natl. Acad. Sci. USA, 97, 9021-9025.Google Scholar
  6. Clore, G.M. and Gronenborn, A.M. (1998) Proc. Natl. Acad. Sci. USA, 95, 5891-5898.Google Scholar
  7. Clore, G.M., Gronenborn, A.M. and Tjandra, N. (1998) J. Magn. Reson., 131, 159-162.Google Scholar
  8. Delaglio, F., Kontaxis, G. and Bax, A. (2000) J. Am. Chem. Soc., 122, 2142-2143.Google Scholar
  9. Dosset, P., Hus, J.-C., Blackledge, M. and Marion, D. (2000) J. Biomol. NMR, 16, 23-28.Google Scholar
  10. Fischer, M.W.F., Losonczi, J.A., Weaver, J.L. and Prestegard, J.H. (1999) Biochemistry, 38, 9013-9022.Google Scholar
  11. Fushman, D., Xu, R. and Cowburn, D. (1999) Biochemistry, 38, 10225-10230.Google Scholar
  12. Gardner, K. and Kay, L. (1998) Annu. Rev. Biophys. Biomol. Struct., 27, 357-406.Google Scholar
  13. Hus, J.-C., Marion, D. and Blackledge, M. (1999) J. Am. Chem. Soc., 121, 2311-2312.Google Scholar
  14. Hus, J.-C., Marion, D. and Blackledge, M. (2000) J. Mol. Biol., 298, 927-936.Google Scholar
  15. Hus, J.-C., Marion, D. and Blackledge, M. (2001) J. Am. Chem. Soc., 123, 2311-2312.Google Scholar
  16. Jones, D.T. (2000) Curr. Opin. Struct. Biol., 10, 371-379.Google Scholar
  17. Leondes, C.T. (1997) Fuzzy Logic and Expert Systems Applications, Academic Press, San Diego, CA.Google Scholar
  18. Lubkowski, J., Hennecke, F., Pluckthun, A. and Wlodawer, A. (1999) Structure, 7, 711-722.Google Scholar
  19. Meiler, J., Peti, W. and Griesinger, C. (2000) J. Biomol. NMR, 17, 283-294.Google Scholar
  20. Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A. and Teller, E. (1953) J. Chem. Phys., 21, 1087-1094.Google Scholar
  21. Mollova, E.T., Hansen, M.R. and Pardi, A. (2000) J. Am. Chem. Soc., 122, 11561-11562.Google Scholar
  22. Olejniczak, E.T., Meadows, R.P., Wang, H., Cai, M., Nettesheim, D.G. and Fesik, S. (1999) J. Am. Chem. Soc., 121, 9249-9251.Google Scholar
  23. Pley, H.W., Flaherty, K.M. and McKay, D.B. (1994) Science, 372, 68-74.Google Scholar
  24. Press, W.H., Flannery, B.P., Teukolsky, S.A. and Vetterling, W.T. (1988) Numerical Recipes in C, The Art of Scientific Computing, Cambridge University Press, Cambridge.Google Scholar
  25. Saenger, W. (1984) Principles of Nucleic Acid Structure, Springer-Verlag, New York, NY.Google Scholar
  26. Simmerling, C., Lee, M.R., Ortiz, A.R., Kolinski, A., Skilnick, J. and Kollman, P. (2000) J. Am. Chem. Soc., 122, 8392-8402.Google Scholar
  27. Skrynnikov, N., Goto, N.K., Yang, D., Choy, W.-Y., Tolman, J.R., Mueller, G.A. and Kay, L. (2000) J. Mol. Biol., 295, 1265-1273.Google Scholar
  28. Tjandra, N. (1999) Structure, 7, R205-R211.Google Scholar
  29. Tjandra, N. and Bax, A. (1997) Science, 278, 1111-1114.Google Scholar
  30. Tjandra, N., Garrett, D.S., Gronenborn, A.M., Bax, G.M. and Clore, G.M. (1997) Nat. Struct. Biol., 4, 443-449.Google Scholar
  31. Tolman, J.R., Flanagan, J.M., Kennedy, M.A. and Prestegard, J.H. (1995) Proc. Natl. Acad. Sci. USA, 92, 9279-9283.Google Scholar
  32. Tsui, V., Zhu, L., Huang, T.-H., Wright, P.E. and Case, D.A. (2000) J. Biomol. NMR, 16, 9-21.Google Scholar
  33. Weaver, J.L. and Prestegard, J.H. (1998) Biochemistry, 37, 116-128.Google Scholar
  34. Wüthrich, K. (1986) NMR of Proteins and Nucleic Acids, Wiley, New York, NY.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Patrice Dosset
    • 1
  • Jean-Christophe Hus
    • 1
  • Dominique Marion
    • 1
  • Martin Blackledge
    • 1
  1. 1.Institut de Biologie Structurale-Jean-Pierre EbelC.N.R.S.-C.E.A.Grenoble CedexFrance

Personalised recommendations