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Journal of Biomolecular NMR

, Volume 62, Issue 1, pp 81–95 | Cite as

Systematic evaluation of combined automated NOE assignment and structure calculation with CYANA

  • Lena Buchner
  • Peter GüntertEmail author
Article

Abstract

The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but a systematic evaluation of its performance has not yet been reported. In this paper we systematically analyze the reliability of combined automated NOESY assignment and structure calculation with CYANA under a variety of conditions on the basis of the experimental NMR data sets of ten proteins. To evaluate the robustness of the algorithm, the original high-quality experimental data sets were modified in different ways to simulate the effect of data imperfections, i.e. incomplete or erroneous chemical shift assignments, missing NOESY cross peaks, inaccurate peak positions, inaccurate peak intensities, lower dimensionality NOESY spectra, and higher tolerances for the matching of chemical shifts and peak positions. The results show that the algorithm is remarkably robust with regard to imperfections of the NOESY peak lists and the chemical shift tolerances but susceptible to lacking or erroneous resonance assignments, in particular for nuclei that are involved in many NOESY cross peaks.

Keywords

Automated assignment NOESY Distance restraints Structure calculation CYANA 

Notes

Acknowledgments

We gratefully acknowledge financial support by the Lichtenberg program of the Volkswagen Foundation and a Grant-in-Aid for Scientific Research of the Japan Society for the Promotion of Science (JSPS).

Supplementary material

10858_2015_9921_MOESM1_ESM.docx (2.1 mb)
Supplementary material 1 (DOCX 2146 kb)

References

  1. Altieri AS, Byrd RA (2004) Automation of NMR structure determination of proteins. Curr Opin Struct Biol 14:547–553CrossRefGoogle Scholar
  2. Antuch W, Güntert P, Wüthrich K (1996) Ancestral bg-crystallin precursor structure in a yeast killer toxin. Nat Struct Biol 3:662–665CrossRefGoogle Scholar
  3. Baran MC, Huang YJ, Moseley HNB, Montelione GT (2004) Automated analysis of protein NMR assignments and structures. Chem Rev 104:3541–3555CrossRefGoogle 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. Billeter M, Wagner G, Wüthrich K (2008) Solution NMR structure determination of proteins revisited. J Biomol NMR 42:155–158CrossRefGoogle Scholar
  6. Calzolai L, Lysek DA, Perez DR, Güntert P, Wüthrich K (2005) Prion protein NMR structures of chickens, turtles, and frogs. Proc Natl Acad Sci USA 102:651–655CrossRefADSGoogle Scholar
  7. Cornilescu G, Delaglio F, Bax A (1999) Protein backbone angle restraints from searching a database for chemical shift and sequence homology. J Biomol NMR 13:289–302CrossRefGoogle Scholar
  8. Duggan BM, Legge GB, Dyson HJ, Wright PE (2001) SANE (Structure assisted NOE evaluation): an automated model-based approach for NOE assignment. J Biomol NMR 19:321–329CrossRefGoogle Scholar
  9. Gronwald W, Kalbitzer HR (2004) Automated structure determination of proteins by NMR spectroscopy. Prog Nucl Magn Reson Spectrosc 44:33–96CrossRefGoogle Scholar
  10. Gronwald W, Moussa S, Elsner R, Jung A, Ganslmeier B, Trenner J, Kremer W, Neidig KP, Kalbitzer HR (2002) Automated assignment of NOESY NMR spectra using a knowledge based method (KNOWNOE). J Biomol NMR 23:271–287CrossRefGoogle Scholar
  11. Guerry P, Herrmann T (2011) Advances in automated NMR protein structure determination. Q Rev Biophys 44:257–309CrossRefGoogle Scholar
  12. Güntert P (1998) Structure calculation of biological macromolecules from NMR data. Q Rev Biophys 31:145–237CrossRefGoogle Scholar
  13. Güntert P (2003) Automated NMR protein structure calculation. Prog Nucl Magn Reson Spectrosc 43:105–125CrossRefGoogle Scholar
  14. Güntert P (2004) Automated NMR structure calculation with CYANA. Meth Mol Biol 278:353–378Google Scholar
  15. Güntert P (2009) Automated structure determination from NMR spectra. Eur Biophys J 38:129–143CrossRefGoogle Scholar
  16. Güntert P, Berndt KD, Wüthrich K (1993) The program ASNO for computer-supported collection of NOE upper distance constraints as input for protein structure determination. J Biomol NMR 3:601–606CrossRefGoogle Scholar
  17. Güntert P, Mumenthaler C, Wüthrich K (1997) Torsion angle dynamics for NMR structure calculation with the new program DYANA. J Mol Biol 273:283–298Google Scholar
  18. Herrmann T, Güntert P, Wüthrich K (2002a) 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
  19. Herrmann T, Güntert P, Wüthrich K (2002b) Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS. J Biomol NMR 24:171–189CrossRefGoogle Scholar
  20. Horst R, Damberger F, Luginbühl P, Güntert P, Peng G, Nikonova L, Leal WS, Wüthrich K (2001) NMR structure reveals intramolecular regulation mechanism for pheromone binding and release. Proc Natl Acad Sci USA 98:14374–14379CrossRefADSGoogle Scholar
  21. Huang YJ, Tejero R, Powers R, Montelione GT (2006) A topology-constrained distance network algorithm for protein structure determination from NOESY data. Proteins 62:587–603CrossRefGoogle Scholar
  22. Hung LH, Samudrala R (2006) An automated assignment-free Bayesian approach for accurately identifying proton contacts from NOESY data. J Biomol NMR 36:189–198CrossRefGoogle Scholar
  23. Ikeya T, Jee J-G, Shigemitsu Y, Hamatsu J, Mishima M, Ito Y, Kainosho M, Güntert P (2011) Exclusively NOESY-based automated NMR assignment and structure determination of proteins. J Biomol NMR 50:137–146CrossRefGoogle Scholar
  24. Jee J, Güntert P (2003) Influence of the completeness of chemical shift assignments on NMR structures obtained with automated NOE assignment. J Struct Funct Genom 4:179–189CrossRefGoogle Scholar
  25. Kainosho M, Torizawa T, Iwashita Y, Terauchi T, Ono AM, Güntert P (2006) Optimal isotope labelling for NMR protein structure determinations. Nature 440:52–57CrossRefADSGoogle Scholar
  26. Kirchner DK, Güntert P (2011) Objective identification of residue ranges for the superposition of protein structures. BMC Bioinformatics 12:170Google Scholar
  27. Kuszewski J, Schwieters CD, Garrett DS, Byrd RA, Tjandra N, Clore GM (2004) Completely automated, highly error-tolerant macromolecular structure determination from multidimensional nuclear overhauser enhancement spectra and chemical shift assignments. J Am Chem Soc 126:6258–6273CrossRefGoogle Scholar
  28. López-Méndez B, Güntert P (2006) Automated protein structure determination from NMR spectra. J Am Chem Soc 128:13112–13122CrossRefGoogle Scholar
  29. 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
  30. Luginbühl P, Szyperski T, Wüthrich K (1995) Statistical basis for the use of 13Ca chemical shifts in protein structure determination. J Magn Reson B 109:229–233CrossRefGoogle Scholar
  31. Meadows RP, Olejniczak ET, Fesik SW (1994) A computer-based protocol for semiautomated assignments and 3D structure determination of proteins. J Biomol NMR 4:79–96CrossRefGoogle Scholar
  32. Moseley HNB, Montelione GT (1999) Automated analysis of NMR assignments and structures for proteins. Curr Opin Struct Biol 9:635–642CrossRefGoogle Scholar
  33. Mumenthaler C, Braun W (1995) Automated assignment of simulated and experimental NOESY spectra of proteins by feedback filtering and self-correcting distance geometry. J Mol Biol 254:465–480CrossRefGoogle Scholar
  34. Mumenthaler C, Güntert P, Braun W, Wüthrich K (1997) Automated combined assignment of NOESY spectra and three-dimensional protein structure determination. J Biomol NMR 10:351–362CrossRefGoogle Scholar
  35. Nabuurs SB, Spronk CAEM, Vuister GW, Vriend G (2006) Traditional biomolecular structure determination by NMR spectroscopy allows for major errors. PLoS Comp Biol 2:71–79CrossRefGoogle Scholar
  36. Nilges M (1995) Calculation of protein structures with ambiguous distance restraints—automated assignment of ambiguous NOE crosspeaks and disulfide connectivities. J Mol Biol 245:645–660CrossRefGoogle Scholar
  37. Nilges M, Macias MJ, ODonoghue SI, Oschkinat H (1997) Automated NOESY interpretation with ambiguous distance restraints: the refined NMR solution structure of the pleckstrin homology domain from beta-spectrin. J Mol Biol 269:408–422CrossRefGoogle Scholar
  38. Ohnishi S, Güntert P, Koshiba S, Tomizawa T, Akasaka R, Tochio N, Sato M, Inoue M, Harada T, Watanabe S, Tanaka A, Shirouzu M, Kigawa T, Yokoyama S (2007) Solution structure of an atypical WW domain in a novel b-clam-like dimeric form. FEBS Lett 581:462–468CrossRefGoogle Scholar
  39. Pääkkönen K, Tossavainen H, Permi P, Rakkolainen H, Rauvala H, Raulo E, Kilpeläinen I, Güntert P (2006) Solution structures of the first and fourth TSR domains of F-spondin. Proteins 64:665–672CrossRefGoogle Scholar
  40. 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
  41. 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
  42. Rieping W, Habeck M, Bardiaux B, Bernard A, Malliavin TE, Nilges M (2007) ARIA2: automated NOE assignment and data integration in NMR structure calculation. Bioinformatics 23:381–382CrossRefGoogle Scholar
  43. Rosato A, Bagaria A, Baker D, Bardiaux B, Cavalli A, Doreleijers JF, Giachetti A, Guerry P, Güntert P, Herrmann T, Huang YJ, Jonker HRA, Mao B, Malliavin TE, Montelione GT, Nilges M, Raman S, van der Schot G, Vranken WF, Vuister GW, Bonvin AMJJ (2009) CASD-NMR: critical assessment of automated structure determination by NMR. Nat Methods 6:625–626CrossRefGoogle Scholar
  44. Rosato A, Aramini JM, Arrowsmith C, Bagaria A, Baker D, Cavalli A, Doreleijers JF, Eletsky A, Giachetti A, Guerry P, Gutmanas A, Güntert P, He YF, Herrmann T, Huang YPJ, Jaravine V, Jonker HRA, Kennedy MA, Lange OF, Liu GH, Malliavin TE, Mani R, Mao BC, Montelione GT, Nilges M, Rossi P, van der Schot G, Schwalbe H, Szyperski TA, Vendruscolo M, Vernon R, Vranken WF, de Vries S, Vuister GW, Wu B, Yang YH, Bonvin AMJJ (2012) Blind testing of routine, fully automated determination of protein structures from NMR data. Structure 20:227–236CrossRefGoogle Scholar
  45. Schmidt E, Güntert P (2012) A new algorithm for reliable and general NMR resonance assignment. J Am Chem Soc 134:12817–12829CrossRefGoogle Scholar
  46. Schmidt E, Güntert P (2013) Reliability of exclusively NOESY-based automated resonance assignment and structure determination of proteins. J Biomol NMR 57:193–204CrossRefGoogle Scholar
  47. 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
  48. 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
  49. Vögeli B, Segawa TF, Leitz D, Sobol A, Choutko A, Trzesniak D, van Gunsteren W, Riek R (2009) Exact distances and internal dynamics of perdeuterated ubiquitin from NOE buildups. J Am Chem Soc 131:17215–17225CrossRefGoogle Scholar
  50. Vögeli B, Kazemi S, Güntert P, Riek R (2012) Spatial elucidation of motion in proteins by ensemble-based structure calculation using exact NOEs. Nat Struct Mol Biol 19:1053–1057CrossRefGoogle Scholar
  51. Williamson MP, Craven CJ (2009) Automated protein structure calculation from NMR data. J Biomol NMR 43:131–143CrossRefGoogle Scholar
  52. Wimmer R, Herrmann T, Solioz M, Wüthrich K (1999) NMR structure and metal interactions of the CopZ copper chaperone. J Biol Chem 274:22597–22603CrossRefGoogle Scholar
  53. Zhang Z, Porter J, Tripsianes K, Lange OF (2014) Robust and highly accurate automatic NOESY assignment and structure determination with Rosetta. J Biomol NMR 59:135–145CrossRefGoogle Scholar
  54. Zwahlen C, Legault P, Vincent SJF, Greenblatt J, Konrat R, Kay LE (1997) Methods for measurement of intermolecular NOEs by multinuclear NMR spectroscopy: application to a bacteriophage l N-peptide/boxB RNA complex. J Am Chem Soc 119:6711–6721CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, and Frankfurt Institute of Advanced StudiesGoethe University Frankfurt am MainFrankfurt am MainGermany
  2. 2.Laboratory of Physical ChemistryETH ZürichZurichSwitzerland
  3. 3.Graduate School of ScienceTokyo Metropolitan UniversityHachiojiJapan

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