Advertisement

Journal of Biomolecular NMR

, Volume 43, Issue 4, pp 197–210 | Cite as

Chemical shift optimization in multidimensional NMR spectra by AUREMOL-SHIFTOPT

  • Kumaran Baskaran
  • Renate Kirchhöfer
  • Fritz Huber
  • Jochen Trenner
  • Konrad Brunner
  • Wolfram Gronwald
  • Klaus-Peter Neidig
  • Hans Robert Kalbitzer
Article

Abstract

A problem often encountered in multidimensional NMR-spectroscopy is that an existing chemical shift list of a protein has to be used to assign an experimental spectrum but does not fit sufficiently well for a safe assignment. A similar problem occurs when temperature or pressure series of n-dimensional spectra are to be evaluated automatically. We have developed two different algorithms, AUREMOL-SHIFTOPT1 and AUREMOL-SHIFTOPT2 that fulfill this task. In the present contribution their performance is analyzed employing a set of simulated and experimental two-dimensional and three-dimensional spectra obtained from three different proteins. A new z-score based on atom and amino acid specific chemical shift distributions is introduced to weight the chemical shift contributions in different dimensions properly.

Keywords

Chemical shift Peak assignment Multidimensional NMR spectra AUREMOL 

Notes

Acknowledgements

This work was supported by the European Union (SPINE-2), the Fonds der Chemischen Industrie, the Deutsche Forschungsgemeinschaft (DFG), and the Bundesministerium für Bildung und Forschung (BMBF).

References

  1. Antz C, Neidig K-P, Kalbitzer HR (1995) A general Bayesian method for an automated signal class recognition in 2D NMR spectra combined with a multivariate discriminant analysis. J Biomol NMR 5:287–296CrossRefGoogle Scholar
  2. Box GEP, Muller ME (1958) A note on the generation of random normal deviates. The Annals of Mathematical Statistics 29(2):610–611MATHCrossRefGoogle Scholar
  3. Catasti P, Carrara E, Nicolini C (1990) Pepto: an expert system for automatic peak assignment of two-dimensional nuclear magnetic resonance spectra of proteins. J Comput Chem 11(7):805–818CrossRefGoogle Scholar
  4. Geyer M, Neidig K-P, Kalbitzer HR (1995) Automated peak integration in multidimensional NMR spectra by an optimized iterative segmentation procedure. J Magn Reson B 109:31–38CrossRefGoogle Scholar
  5. Glaser S, Kalbitzer HR (1987) Automated recognition and assessment of cross peaks in two-dimensional NMR spectra of macromolecules. J Magn Reson 74:450–463Google Scholar
  6. Görler A, Kalbitzer HR (1997) RELAX: a flexible program for the analysis of NOESY-Spectra by back calculation based on the complete relaxation matrix formalism. J Magn Reson 124:177–188CrossRefGoogle Scholar
  7. Görler A, Hengstenberg W, Kravanja M, Beneicke W, Maurer T, Kalbitzer HR (1999a) Solution structure of histidine containing phosphocarrier protein (HPr) from Staphylococcus carnosus. Appl Magn Reson 17:465–480CrossRefGoogle Scholar
  8. Görler A, Gronwald W, Neidig K-P, Kalbitzer HR (1999b) Computer assisted assignment of 13C or 15N edited 3D-NOESY-HSQC spectra using back calculated and experimental spectra. J Magn Reson 137:39–45CrossRefADSGoogle Scholar
  9. Gronwald W, Kalbitzer HR (2004) Automated structure determination of proteins by NMR spectroscopy. Prog NMR Spectrosc 44:33–96CrossRefGoogle Scholar
  10. Gronwald W, Kirchhöfer R, Görler A, Kremer W, Ganslmeier B, Neidig K-P, Kalbitzer HR (2000) RFAC, a programme for automated NMR-R-factor estimation. J Biomol NMR 17:137–151CrossRefGoogle Scholar
  11. Gronwald W, Moussa S, Elsner R, Jung A, Ganslmeier B, Trenner J, Kremer W, Neidig K-P, Kalbitzer HR (2002) Automated assignment of NOESY NMR spectra using a knowledge based method (KNOWNOE). J Biomol NMR 23:271–287CrossRefGoogle Scholar
  12. Gronwald W, Bombke J, Maurer T, Domogalla B, Huber F, Schumann F, Kremer W, Fink F, Rysiok T, Frech M, Kalbitzer HR (2008) Structure of the Leech protein Saratin and characterisation of its binding to collagen. J Mol Biol 381:913–927CrossRefGoogle Scholar
  13. Hare BJ, Prestegard JH (1994) Application of neural networks to automated assignment of NMR spectra of proteins. J Biomol NMR 4:35–46CrossRefGoogle Scholar
  14. Herrmann T, Güntert P, Wthrich K (2002) Protein NMR structure determination with automated NOE assignment using the new software CANDID and the torsion angle dynamics algorithm DYANA. J Mol Biol 319:209–227CrossRefGoogle Scholar
  15. Kalbitzer HR, Görler A, Li H, Dubovskii P, Hengstenberg W, Kowolik C, Yamada H, Akasaka K (2000) 15N and 1H NMR study of histidine containing protein (HPr) from Staphylococcus carnosus at high pressure. Prot Sci 9:693–703Google Scholar
  16. Maurer T, Meier S, Kachel K, Munte CE, Hasenbein S, Koch B, Hengstenberg W, Kalbitzer HR (2004) High resolution structure of the histidine containing phosphocarrier protein (HPr) from Staphylococcus aureus and characterisation of its interaction with the bifunctional HPrKinase/phosphorylase. J Bacteriol 186:5906–5918CrossRefGoogle Scholar
  17. Neidig P, Bodenmüller H, Kalbitzer HR (1984) Computer aided evaluation of two-dimensional NMR spectra of proteins. Biochem Biophys Res Commun 125:1143–1150CrossRefGoogle Scholar
  18. Press W, Teukolsky S, Vetterling W, Flannery B (1992). §3.1 Polynomial interpolation and extrapolation. In: numerical recipes in C. The art of scientific computing, 3rd edn. Cambridge University Press, CambridgeGoogle Scholar
  19. Ried A, Gronwald W, Trenner JM, Brunner K, Neidig K-P, Kalbitzer HR (2004) Improved simulation of NOESY spectra by RELAX-JT2 including effects of J-coupling, transverse relaxation, and chemical shift anisotropy. J Biomol NMR 30:121–131CrossRefGoogle Scholar
  20. Schulte AC, Görler A, Antz C, Neidig K-P, Kalbitzer HR (1997) Use of global symmetries in automated signal class recognition by a Bayesian method. J Magn Reson 129:165–172CrossRefADSGoogle Scholar
  21. Schumann FH, Riepl H, Maurer T, Gronwald W, Neidig K.-P., Kalbitzer HR (2007) Combined chemical shift changes and amino acid specific chemical shift mapping of protein–protein interactions. J Biomol NMR 39:275–289CrossRefGoogle Scholar
  22. Xu Y, Jablonsky MJ, Jackson PL, Braun W, Rama Krishna N (2001) Automatic assignment of NOESY cross peaks and determination of the protein structure of a new world scorpion using NOAH/DIAMOD. J Magn Reson 148:35–46CrossRefADSGoogle Scholar
  23. Zimmerman DE, Kulikowski CA, Huang Y, Feng W, Tashiro M, Shimotakahara S, Chien C-y, Powers R, Montelione GT (1997) Automated analysis of protein NMR assignments using methods from artificial intelligence. J Mol Biol 269:592–610CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Kumaran Baskaran
    • 1
  • Renate Kirchhöfer
    • 1
    • 3
  • Fritz Huber
    • 1
    • 3
  • Jochen Trenner
    • 1
  • Konrad Brunner
    • 1
  • Wolfram Gronwald
    • 1
    • 4
  • Klaus-Peter Neidig
    • 2
  • Hans Robert Kalbitzer
    • 1
  1. 1.Department of Biophysics and Physical BiochemistryUniversity of RegensburgRegensburgFederal Republic of Germany
  2. 2.Software DepartmentBruker BioSpin GmbHRheinstettenFederal Republic of Germany
  3. 3.LipoFIT Analytic GmbHRegensburgFederal Republic of Germany
  4. 4.Institute of Functional GenomicsUniversity of RegensburgRegensburgFederal Republic of Germany

Personalised recommendations