Advertisement

Journal of Biomolecular NMR

, Volume 55, Issue 3, pp 267–277 | Cite as

Peakmatch: a simple and robust method for peak list matching

  • Lena Buchner
  • Elena Schmidt
  • Peter Güntert
Article

Abstract

Peak lists are commonly used in NMR as input data for various software tools such as automatic assignment and structure calculation programs. Inconsistencies of chemical shift referencing among different peak lists or between peak and chemical shift lists can cause severe problems during peak assignment. Here we present a simple and robust tool to achieve self-consistency of the chemical shift referencing among a set of peak lists. The Peakmatch algorithm matches a set of peak lists to a specified reference peak list, neither of which have to be assigned. The chemical shift referencing offset between two peak lists is determined by optimizing an assignment-free match score function using either a complete grid search or downhill simplex optimization. It is shown that peak lists from many different types of spectra can be matched reliably as long as they contain at least two corresponding dimensions. Using a simulated peak list, the Peakmatch algorithm can also be used to obtain the optimal agreement between a chemical shift list and experimental peak lists. Combining these features makes Peakmatch a useful tool that can be applied routinely before automatic assignment or structure calculation in order to obtain an optimized input data set.

Keywords

Automated assignment Peak list Peak alignment Spectrum referencing CYANA 

Notes

Acknowledgments

We thank Dr. T. Ikeya, Dr. M. Takeda, and Prof. M. Kainosho for the DsbA peak lists. We gratefully acknowledge financial support by the Lichtenberg program of the Volkswagen Foundation, the Deutsche Forschungsgemeinschaft (DFG), and the Bio-NMR project of the European Commission.

Supplementary material

10858_2013_9708_MOESM1_ESM.pdf (7.9 mb)
Supplementary material 1 (PDF 8111 kb)

References

  1. Aeschbacher T, Schubert M, Allain FHT (2012) A procedure to validate and correct the 13C chemical shift calibration of RNA datasets. J Biomol NMR 52:179–190CrossRefGoogle Scholar
  2. Baran MC, Huang YJ, Moseley HNB, Montelione GT (2004) Automated analysis of protein NMR assignments and structures. Chem Rev 104:3541–3555CrossRefGoogle Scholar
  3. Bartels C, Xia TH, Billeter M, Güntert P, Wüthrich K (1995) The program XEASY for computer-supported NMR spectral analysis of biological macromolecules. J Biomol NMR 6:1–10CrossRefGoogle Scholar
  4. Bartels C, Güntert P, Billeter M, Wüthrich K (1997) GARANT—a general algorithm for resonance assignment of multidimensional nuclear magnetic resonance spectra. J Comput Chem 18:139–149CrossRefGoogle Scholar
  5. Ginzinger SW, Gerick F, Coles M, Heun V (2007) CheckShift: automatic correction of inconsistent chemical shift referencing. J Biomol NMR 39:223–227CrossRefGoogle Scholar
  6. Guerry P, Herrmann T (2011) Advances in automated NMR protein structure determination. Q Rev Biophys 44:257–309CrossRefGoogle Scholar
  7. Güntert P (2009) Automated structure determination from NMR spectra. Eur Biophys J 38:129–143CrossRefGoogle Scholar
  8. Güntert P, Mumenthaler C, Wüthrich K (1997) Torsion angle dynamics for NMR structure calculation with the new program DYANA. J Mol Biol 273:283–298CrossRefGoogle Scholar
  9. Herrmann T, Güntert P, Wüthrich K (2002) Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS. J Biomol NMR 24:171–189CrossRefGoogle Scholar
  10. Ikeya T, Takeda M, Yoshida H, Terauchi T, Jee J, Kainosho M, Güntert P (2009) Automated NMR structure determination of stereo-array isotope labeled ubiquitin from minimal sets of spectra using the SAIL-FLYA system. J Biomol NMR 44:261–272CrossRefGoogle Scholar
  11. Johnson BA (2004) Using NMRView to visualize and analyze the NMR spectra of macromolecules. Meth Mol Biol 278:313–352Google Scholar
  12. Kainosho M, Güntert P (2009) SAIL—stereo-array isotope labeling. Q Rev Biophys 42:247–300CrossRefGoogle Scholar
  13. Kainosho M, Torizawa T, Iwashita Y, Terauchi T, Ono AM, Güntert P (2006) Optimal isotope labelling for NMR protein structure determinations. Nature 440:52–57ADSCrossRefGoogle Scholar
  14. López-Méndez B, Güntert P (2006) Automated protein structure determination from NMR spectra. J Am Chem Soc 128:13112–13122CrossRefGoogle Scholar
  15. López-Méndez B, Pantoja-Uceda D, Tomizawa T, Koshiba S, Kigawa T, Shirouzu M, Terada T, Inoue M, Yabuki T, Aoki M, Seki E, Matsuda T, Hirota H, Yoshida M, Tanaka A, Osanai T, Seki M, Shinozaki K, Yokoyama S, Güntert P (2004) NMR assignment of the hypothetical ENTH-VHS domain At3g16270 from Arabidopsis thaliana. J Biomol NMR 29:205–206CrossRefGoogle Scholar
  16. Nelder JA, Mead R (1965) A simplex method for function minimization. Comput J 7:308–313MATHCrossRefGoogle Scholar
  17. Pantoja-Uceda D, López-Méndez B, Koshiba S, Kigawa T, Shirouzu M, Terada T, Inoue M, Yabuki T, Aoki M, Seki E, Matsuda T, Hirota H, Yoshida M, Tanaka A, Osanai T, Seki M, Shinozaki K, Yokoyama S, Güntert P (2004) NMR assignment of the hypothetical rhodanese domain At4g01050 from Arabidopsis thaliana. J Biomol NMR 29:207–208CrossRefGoogle Scholar
  18. Pantoja-Uceda D, López-Méndez B, Koshiba S, Inoue M, Kigawa T, Terada T, Shirouzu M, Tanaka A, Seki M, Shinozaki K, Yokoyama S, Güntert P (2005) Solution structure of the rhodanese homology domain At4g01050(175–295) from Arabidopsis thaliana. Protein Sci 14:224–230CrossRefGoogle Scholar
  19. Schmidt E, Güntert P (2012) A new algorithm for reliable and general NMR resonance assignment. J Am Chem Soc 134:12817–12829CrossRefGoogle Scholar
  20. Schmucki R, Yokoyama S, Güntert P (2009) Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the DYNASSIGN algorithm. J Biomol NMR 43:97–109CrossRefGoogle Scholar
  21. Scott A, Pantoja-Uceda D, Koshiba S, Inoue M, Kigawa T, Terada T, Shirouzu M, Tanaka A, Sugano S, Yokoyama S, Güntert P (2004) NMR assignment of the SH2 domain from the human feline sarcoma oncogene FES. J Biomol NMR 30:463–464CrossRefGoogle Scholar
  22. Scott A, Pantoja-Uceda D, Koshiba S, Inoue M, Kigawa T, Terada T, Shirouzu M, Tanaka A, Sugano S, Yokoyama S, Güntert P (2005) Solution structure of the Src homology 2 domain from the human feline sarcoma oncogene Fes. J Biomol NMR 31:357–361CrossRefGoogle Scholar
  23. Wang YJ, Wishart DS (2005) A simple method to adjust inconsistently referenced 13C and 15N chemical shift assignments of proteins. J Biomol NMR 31:143–148MATHCrossRefGoogle Scholar
  24. Wang LY, Eghbalnia HR, Bahrami A, Markley JL (2005) Linear analysis of carbon-13 chemical shift differences and its application to the detection and correction of errors in referencing and spin system identifications. J Biomol NMR 32:13–22CrossRefGoogle Scholar
  25. Williamson MP, Craven CJ (2009) Automated protein structure calculation from NMR data. J Biomol NMR 43:131–143CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, and Frankfurt Institute for Advanced StudiesGoethe University Frankfurt am MainFrankfurt am MainGermany

Personalised recommendations