Journal of Biomolecular NMR

, Volume 18, Issue 2, pp 83–100 | Cite as

Lipari–Szabo mapping: A graphical approach to Lipari–Szabo analysis of NMR relaxation data using reduced spectral density mapping

  • Michael Andrec
  • Gaetano T. Montelione
  • Ronald M. Levy


In this paper, we explore connections between the Lipari–Szabo formalism and reduced spectral density mapping, and show how spectral density estimates can be associated with Lipari–Szabo parameters via a simple geometric construction which we call Lipari–Szabo mapping. This relationship can be used to estimate Lipari–Szabo parameters from spectral density estimates without the need for nonlinear optimization, and to perform `model selection' in a graphical manner. The Lipari–Szabo map also provides insight into the Lipari–Szabo model, and allows us to determine when a given set of experimental spectral densities are inconsistent with the Lipari–Szabo formalism. Practical applications of Lipari–Szabo mapping in conjunction with more traditional analysis methods are discussed.

cold-shock protein A CspA protein dynamics 


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  1. Andrec, M., Inman, K.G., Weber, D.J., Levy, R.M. and Montelione, G.T. (2000) J. Magn. Reson., in press.Google Scholar
  2. Andrec, M., Montelione, G.T. and Levy, R.M. (1999) J. Magn.Reson., 139, 408–421.Google Scholar
  3. Bevington, P.R. (1969) Data Reduction and Error Analysis in the Physical Sciences, McGraw-Hill, New York, NY.Google Scholar
  4. Brooks, C.L., Karplus, M. and Pettit, B.M. (1988) Proteins: A Theoretical Perspective of Dynamics, Structure, and Thermodynamics, John Wiley & Sons, New York, NY.Google Scholar
  5. Brüschweiler, R., Liao, X. and Wright, P.E. (1995) Science, 268, 886–889.Google Scholar
  6. Cavanagh, J., Fairbrother, W.J., Palmer, A.G. and Skelton, N.J. (1996) Protein NMR Spectroscopy: Principles and Practice, Academic Press, San Diego, CA.Google Scholar
  7. Clore, G.M., Gronenborn, A.M., Szabo, A. and Tjandra, N. (1998) J. Am. Chem. Soc., 120, 4889–4890.Google Scholar
  8. Clore, G.M., Szabo, A., Bax, A., Kay, L.E., Driscoll, P.C. and Gronenborn, A.M. (1990) J. Am. Chem. Soc., 112, 4989–4991.Google Scholar
  9. Craig, C.C. (1936) Ann. Math. Stat., 7, 1–15.Google Scholar
  10. Daragan, V.A. and Mayo, K.H. (1997) Prog. NMR Spectrosc., 31, 63–105.Google Scholar
  11. Farrow, N.A., Zhang, O., Szabo, A., Torchia, D.A. and Kay, L.E. (1995) J. Biomol. NMR, 6, 153–162.Google Scholar
  12. Feng, W., Tejero, R., Zimmerman, D.E., Inouye, M. and Montelione, G.T. (1998) Biochemistry, 37, 10881–10896.Google Scholar
  13. Fischer, M.W.F. Majumdar, A. and Zuiderweg, E.R.P. (1998) Prog. NMR Spectrosc., 33, 207–272.Google Scholar
  14. Fushman, D., Weisemann, R., Thüring, H. and Rüterjans, H. (1994) J. Biomol. NMR, 4, 61–78.Google Scholar
  15. Guenneugues, M., Gilquin, B., Wolff, N., Ménez, A. and Zinn-Justin, S. (1999) J. Biomol. NMR, 14, 47–66.Google Scholar
  16. Ishima, R. and Nagayama, K. (1995) J. Magn. Reson., B108, 73–76.Google Scholar
  17. Ishima, R., Yamasaki, K. and Nagayama, K. (1995) J. Biomol. NMR, 6, 423–426.Google Scholar
  18. Jardetzky, O. (1996) Prog. Biophys. Mol. Biol., 65, 171–219.Google Scholar
  19. Jin, D., Andrec, M., Montelione, G.T. and Levy, R.M. (1998) J. Biomol. NMR, 12, 471–492.Google Scholar
  20. Jin, D., Figueirido, F., Montelione, G.T. and Levy, R.M. (1997) J. Am. Chem. Soc., 119, 6923–6924.Google Scholar
  21. Lee, L.K., Rance, M., Chazin, W.J. and Palmer, A.G., III (1997) J. Biomol. NMR, 9, 287–298.Google Scholar
  22. Lefèvre, J.-F., Dayie, K.T., Peng, J.W. and Wagner, G. (1996) Biochemistry, 35, 2674–2686.Google Scholar
  23. Levy, R.M. and Keepers, J. (1986) Commun. Mol. Cell. Biophys., 3, 273–295.Google Scholar
  24. Lipari, G. and Szabo, A. (1982) J. Am. Chem. Soc., 104, 4546–4559.Google Scholar
  25. Losonczi, J.A. and Prestegard, J.H. (1998) Biochemistry, 37, 706–716.Google Scholar
  26. Mandel, A.M., Akke, M. and Palmer, A.G., III (1995) J. Mol. Biol., 246, 144–163.Google Scholar
  27. McCammon, J.A. and Harvey, S. (1987) Dynamics of Proteins and Nucleic Acids, Cambridge University Press, Cambridge.Google Scholar
  28. Ó Ruanaidh, J.J.K. and Fitzgerald, W.J. (1996) Numerical Bayesian Methods Applied to Signal Processing, Springer-Verlag, New York, NY.Google Scholar
  29. Palmer, A.G., III (1997) Curr. Opin. Struct. Biol., 7, 732–737.Google Scholar
  30. Peng, J.W. and Wagner, G. (1992a) Biochemistry, 31, 8571–8586.Google Scholar
  31. Peng, J.W. and Wagner, G. (1992b) J. Magn. Reson., 98, 308–332.Google Scholar
  32. Peng, J.W. and Wagner, G. (1995) Biochemistry, 34, 16733–16752.Google Scholar
  33. Press, W.H., Teukolsky, S.A., Vetterling, W.T. and Flannery, B.P. (1992) Numerical Recipes in C: The Art of Scientific Computing, Cambridge University Press, Cambridge.Google Scholar
  34. Schurr, J.M., Babcock, H.P. and Fujimoto, B.S. (1994) J. Magn.Reson., B105, 211–224.Google Scholar
  35. Sivia, D.S. (1996) Data Analysis: A Bayesian Tutorial, Oxford University Press, Oxford.Google Scholar
  36. Stephenson, D.S. (1988) Prog. NMR Spectrosc., 20, 515–626.Google Scholar
  37. Tarantola, A. (1987) Inverse Problem Theory: Methods for Data Fitting and Model Parameter Estimation, Elsevier, Amsterdam.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Michael Andrec
    • 1
  • Gaetano T. Montelione
    • 1
  • Ronald M. Levy
    • 2
  1. 1.Center for Advanced Biotechnology and MedicineUSA
  2. 2.Department of Chemistry, Wright-Rieman LaboratoriesUSA

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