Skip to main content
SpringerLink
Log in

Automated Structure Determination from NMR Spectra

  • Reference work entry
  • First Online:
Modern Magnetic Resonance

  • 362 Accesses

Abstract

The steps of an NMR protein structure determination that follow data acquisition can now be performed by automated computational methods. This overview of the computational methods for NMR protein structure analysis highlights recent automated methods for signal identification in multidimensional NMR spectra, sequence-specific resonance assignment, collection of conformational restraints, and structure calculation, as implemented in the CYANA software package.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 1,200.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 1,299.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Billeter M, Wagner G, Wüthrich K. Solution NMR structure determination of proteins revisited. J Biomol NMR. 2008;42:155–8.

    Article  CAS  Google Scholar 

  2. Gronwald W, Kalbitzer HR. Automated structure determination of proteins by NMR spectroscopy. Prog Nucl Magn Reson Spectrosc. 2004;44:33–96.

    Article  CAS  Google Scholar 

  3. Güntert P. Automated NMR protein structure calculation. Prog Nucl Magn Reson Spectrosc. 2003;43:105–25.

    Article  CAS  Google Scholar 

  4. Malmodin D, Billeter M. High-throughput analysis of protein NMR spectra. Prog Nucl Magn Reson Spectrosc. 2005;46:109–29.

    Article  CAS  Google Scholar 

  5. Kainosho M, Güntert P. SAIL – Stereo-array isotope labeling. Q Rev Biophys. 2009;42:247–300.

    Article  CAS  Google Scholar 

  6. Schmidt E, Güntert P. A new algorithm for reliable and general NMR resonance assignment. J Am Chem Soc. 2012;134:12817–29.

    Article  CAS  Google Scholar 

  7. Güntert P, Buchner L. Combined automated NOE assignment and structure calculation with CYANA. J Biomol NMR. 2015;62:453–71.

    Article  CAS  Google Scholar 

  8. Herrmann T, Güntert P, Wüthrich K. Protein NMR structure determination with automated NOE assignment using the new software CANDID and the torsion angle dynamics algorithm DYANA. J Mol Biol. 2002;319:209–27.

    Article  CAS  Google Scholar 

  9. Jee J, Güntert P. Influence of the completeness of chemical shift assignments on NMR structures obtained with automated NOE assignment. J Struct Funct Genom. 2003;4:179–89.

    Article  CAS  Google Scholar 

  10. Buchner L, Güntert P. Systematic evaluation of combined automated NOE assignment and structure calculation with CYANA. J Biomol NMR. 2015;62:81–95.

    Article  CAS  Google Scholar 

  11. Bartels C, Xia TH, Billeter M, Güntert P, Wüthrich K. The program XEASY for computer-supported NMR spectral analysis of biological macromolecules. J Biomol NMR. 1995;6:1–10.

    Article  CAS  Google Scholar 

  12. Goddard TD, Kneller DG. Sparky 3. San Francisco: University of California; 2001.

    Google Scholar 

  13. Johnson BA. Using NMRView to visualize and analyze the NMR spectra of macromolecules. Methods Mol Biol. 2004;278:313–52.

    CAS  Google Scholar 

  14. Johnson BA, Blevins RA. NMR View – a computer program for the visualization and analysis of NMR data. J Biomol NMR. 1994;4:603–14.

    Article  CAS  Google Scholar 

  15. Vranken WF, Boucher W, Stevens TJ, Fogh RH, Pajon A, Llinas M, et al. The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins. 2005;59:687–96.

    Article  CAS  Google Scholar 

  16. Skinner SP, Fogh RH, Boucher W, Ragan TJ, Mureddu LG, Vuister GW. CcpNmr AnalysisAssign: a flexible platform for integrated NMR analysis. J Biomol NMR. 2016;66(2):111–24.

    Article  CAS  Google Scholar 

  17. Liu Z, Abbas A, Jing BY, Gao X. WaVPeak: picking NMR peaks through wavelet-based smoothing and volume-based filtering. Bioinformatics. 2012;28:914–20.

    Article  CAS  Google Scholar 

  18. Alipanahi B, Gao X, Karakoc E, Donaldson L, Li M. PICKY: a novel SVD-based NMR spectra peak picking method. Bioinformatics. 2009;25:i268–i75.

    Article  CAS  Google Scholar 

  19. Klukowski P, Walczak MJ, Gonczarek A, Boudet J, Wider G. Computer vision-based automated peak picking applied to protein NMR spectra. Bioinformatics. 2015;31:2981–8.

    Article  CAS  Google Scholar 

  20. Koradi R, Billeter M, Engeli M, Güntert P, Wüthrich K. Automated peak picking and peak integration in macromolecular NMR spectra using AUTOPSY. J Magn Reson. 1998;135:288–97.

    Article  CAS  Google Scholar 

  21. Herrmann T, Güntert P, Wüthrich K. Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS. J Biomol NMR. 2002;24:171–89.

    Article  CAS  Google Scholar 

  22. Orekhov VY, Ibraghimov IV, Billeter M. MUNIN: a new approach to multi-dimensional NMR spectra interpretation. J Biomol NMR. 2001;20:49–60.

    Article  CAS  Google Scholar 

  23. Hiller S, Fiorito F, Wüthrich K, Wider G. Automated projection spectroscopy (APSY). Proc Natl Acad Sci U S A. 2005;102:10876–81.

    Article  CAS  Google Scholar 

  24. Garrett DS, Powers R, Gronenborn AM, Clore GM. A common sense approach to peak picking two-, three- and four-dimensional spectra using automatic computer analysis of contour diagrams. J Magn Reson. 1991;95:214–20.

    CAS  Google Scholar 

  25. Würz JM, Güntert P. Peak picking multidimensional NMR spectra with the contour geometry based algorithm CYPICK. J Biomol NMR. 2017;67:63–76.

    Article  CAS  Google Scholar 

  26. Güntert P, Mumenthaler C, Wüthrich K. Torsion angle dynamics for NMR structure calculation with the new program DYANA. J Mol Biol. 1997;273:283–98.

    Article  Google Scholar 

  27. Cavanagh J, Fairbrother WJ, Palmer III AG, Skelton NJ, Rance M. Protein NMR spectroscopy. Principles and practice. 2nd ed. San Diego: Academic; 2007.

    Google Scholar 

  28. Buchner L, Schmidt E, Güntert P. Peakmatch: a simple and robust method for peak list matching. J Biomol NMR. 2013;55:267–77.

    Article  CAS  Google Scholar 

  29. Wüthrich K, Wider G, Wagner G, Braun W. Sequential resonance assignments as a basis for determination of spatial protein structures by high-resolution proton nuclear magnetic resonance. J Mol Biol. 1982;155:311–9.

    Article  Google Scholar 

  30. Guerry P, Herrmann T. Advances in automated NMR protein structure determination. Q Rev Biophys. 2011;44:257–309.

    Article  CAS  Google Scholar 

  31. Moseley HNB, Montelione GT. Automated analysis of NMR assignments and structures for proteins. Curr Opin Struct Biol. 1999;9:635–42.

    Article  CAS  Google Scholar 

  32. Bartels C, Güntert P, Billeter M, Wüthrich K. GARANT - A general algorithm for resonance assignment of multidimensional nuclear magnetic resonance spectra. J Comput Chem. 1997;18:139–49.

    Article  CAS  Google Scholar 

  33. Bartels C, Billeter M, Güntert P, Wüthrich K. Automated sequence-specific NMR assignment of homologous proteins using the program GARANT. J Biomol NMR. 1996;7:207–13.

    Article  CAS  Google Scholar 

  34. Bahrami A, Assadi AH, Markley JL, Eghbalnia HR. Probabilistic interaction network of evidence algorithm and its application to complete labeling of peak lists from protein NMR spectroscopy. PLoS Comp Biol. 2009;5:e1000307.

    Article  CAS  Google Scholar 

  35. Schmucki R, Yokoyama S, Güntert P. Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the DYNASSIGN algorithm. J Biomol NMR. 2009;43:97–109.

    Article  CAS  Google Scholar 

  36. Zimmerman DE, Kulikowski CA, Huang YP, Feng WQ, Tashiro M, Shimotakahara S, et al. Automated analysis of protein NMR assignments using methods from artificial intelligence. J Mol Biol. 1997;269:592–610.

    Article  CAS  Google Scholar 

  37. Güntert P, Salzmann M, Braun D, Wüthrich K. Sequence-specific NMR assignment of proteins by global fragment mapping with the program MAPPER. J Biomol NMR. 2000;18:129–37.

    Article  Google Scholar 

  38. Volk J, Herrmann T, Wüthrich K. Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH. J Biomol NMR. 2008;41:127–38.

    Article  CAS  Google Scholar 

  39. Jung YS, Zweckstetter M. Mars – robust automatic backbone assignment of proteins. J Biomol NMR. 2004;30:11–23.

    Article  CAS  Google Scholar 

  40. Güntert P. Automated structure determination from NMR spectra. Eur Biophys J. 2009;38:129–43.

    Article  CAS  Google Scholar 

  41. Schmidt E, Güntert P. Reliability of exclusively NOESY-based automated resonance assignment and structure determination of proteins. J Biomol NMR. 2013;57:193–204.

    Article  CAS  Google Scholar 

  42. Schmidt E, Gath J, Habenstein B, Ravotti F, Székely K, Huber M, et al. Automated solid-state NMR resonance assignment of protein microcrystals and amyloids. J Biomol NMR. 2013;56:243–54.

    Article  CAS  Google Scholar 

  43. Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, et al. BioMagResBank. Nucleic Acids Res. 2008;36:D402–D8.

    Article  CAS  Google Scholar 

  44. Aeschbacher T, Schmidt E, Blatter M, Maris C, Duss O, Allain FH-T, et al. Automated and assisted RNA resonance assignment using NMR chemical shift statistics. Nucleic Acids Res. 2013;41:e172.

    Article  CAS  Google Scholar 

  45. Malmodin D, Papavoine CHM, Billeter M. Fully automated sequence-specific resonance assignments of heteronuclear protein spectra. J Biomol NMR. 2003;27:69–79.

    Article  CAS  Google Scholar 

  46. López-Méndez B, Güntert P. Automated protein structure determination from NMR spectra. J Am Chem Soc. 2006;128:13112–22.

    Article  CAS  Google Scholar 

  47. Vögeli B, Kazemi S, Güntert P, Riek R. Spatial elucidation of motion in proteins by ensemble-based structure calculation using exact NOEs. Nat Struct Mol Biol. 2012;19:1053–7.

    Article  CAS  Google Scholar 

  48. Güntert P, Berndt KD, Wüthrich K. The program ASNO for computer-supported collection of NOE upper distance constraints as input for protein structure determination. J Biomol NMR. 1993;3:601–6.

    Article  Google Scholar 

  49. Skinner SP, Goult BT, Fogh RH, Boucher W, Stevens TJ, Laue ED, et al. Structure calculation, refinement and validation using CcpNmr analysis. Acta Crystallogr D. 2015;71:154–61.

    Article  CAS  Google Scholar 

  50. Kobayashi N, Iwahara J, Koshiba S, Tomizawa T, Tochio N, Güntert P, et al. KUJIRA, a package of integrated modules for systematic and interactive analysis of NMR data directed to high-throughput NMR structure studies. J Biomol NMR. 2007;39:31–52.

    Article  CAS  Google Scholar 

  51. Mumenthaler C, Braun W. Automated assignment of simulated and experimental NOESY spectra of proteins by feedback filtering and self-correcting distance geometry. J Mol Biol. 1995;254:465–80.

    Article  CAS  Google Scholar 

  52. Mumenthaler C, Güntert P, Braun W, Wüthrich K. Automated combined assignment of NOESY spectra and three-dimensional protein structure determination. J Biomol NMR. 1997;10:351–62.

    Article  CAS  Google Scholar 

  53. Nilges M, Macias MJ, ODonoghue SI, Oschkinat H. Automated NOESY interpretation with ambiguous distance restraints: the refined NMR solution structure of the pleckstrin homology domain from beta-spectrin. J Mol Biol. 1997;269:408–22.

    Article  CAS  Google Scholar 

  54. Rieping W, Habeck M, Bardiaux B, Bernard A, Malliavin TE, Nilges M. ARIA2: Automated NOE assignment and data integration in NMR structure calculation. Bioinformatics. 2007;23:381–2.

    Article  CAS  Google Scholar 

  55. Huang YJ, Tejero R, Powers R, Montelione GT. A topology-constrained distance network algorithm for protein structure determination from NOESY data. Proteins. 2006;62:587–603.

    Article  CAS  Google Scholar 

  56. Zhang Z, Porter J, Tripsianes K, Lange OF. Robust and highly accurate automatic NOESY assignment and structure determination with Rosetta. J Biomol NMR. 2014;59:135–45.

    Article  CAS  Google Scholar 

  57. Nilges M. Calculation of protein structures with ambiguous distance restraints – automated assignment of ambiguous NOE crosspeaks and disulfide connectivities. J Mol Biol. 1995;245:645–60.

    Article  CAS  Google Scholar 

  58. Rosato A, Bagaria A, Baker D, Bardiaux B, Cavalli A, Doreleijers JF, et al. CASD-NMR: critical assessment of automated structure determination by NMR. Nat Methods. 2009;6:625–6.

    Article  CAS  Google Scholar 

  59. Rosato A, Aramini JM, Arrowsmith C, Bagaria A, Baker D, Cavalli A, et al. Blind testing of routine, fully automated determination of protein structures from NMR data. Structure. 2012;20:227–36.

    Article  CAS  Google Scholar 

  60. Rosato A, Vranken W, Fogh RH, Ragan TJ, Tejero R, Pederson K, et al. The second round of Critical Assessment of Automated Structure Determination of Proteins by NMR: CASD-NMR-2013. J Biomol NMR. 2015;62:413–24.

    Article  CAS  Google Scholar 

  61. Nabuurs SB, Spronk CAEM, Vuister GW, Vriend G. Traditional biomolecular structure determination by NMR spectroscopy allows for major errors. PLoS Comp Biol. 2006;2:71–9.

    Article  CAS  Google Scholar 

  62. Buchner L, Güntert P. Increased reliability of nuclear magnetic resonance protein structures by consensus structure bundles. Structure. 2015;23:425–34.

    Article  CAS  Google Scholar 

  63. López-Méndez B, Pantoja-Uceda D, Tomizawa T, Koshiba S, Kigawa T, Shirouzu M, et al. NMR assignment of the hypothetical ENTH-VHS domain At3g16270 from Arabidopsis thaliana. J Biomol NMR. 2004;29:205–6.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, Goethe University Frankfurt am Main, Max-von-Laue-Str. 9, 60438, Frankfurt am Main, Germany

    Sina Kazemi, Julia Maren Würz, Elena Schmidt, Anurag Bagaria & Peter Güntert

  2. Frankfurt Institute for Advanced Studies, Goethe University Frankfurt am Main, Ruth-Moufang-Str. 1, 60438, Frankfurt am Main, Germany

    Sina Kazemi

  3. Laboratory of Physical Chemistry, ETH Zürich, 8093, Zürich, Switzerland

    Peter Güntert

  4. Department of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0373, Japan

    Peter Güntert

Authors
  1. Sina Kazemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julia Maren Würz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elena Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anurag Bagaria
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Peter Güntert
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Güntert .

Editor information

Editors and Affiliations

  1. Royal Society of Chemistry, London, United Kingdom

    Graham A. Webb

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Kazemi, S., Würz, J.M., Schmidt, E., Bagaria, A., Güntert, P. (2018). Automated Structure Determination from NMR Spectra. In: Webb, G. (eds) Modern Magnetic Resonance. Springer, Cham. https://doi.org/10.1007/978-3-319-28388-3_32

Download citation

Publish with us

Policies and ethics

Search

Navigation