Journal of Biomolecular NMR

, Volume 54, Issue 4, pp 377–387 | Cite as

Rapid prediction of multi-dimensional NMR data sets

  • Sabine Gradmann
  • Christian Ader
  • Ines Heinrich
  • Deepak Nand
  • Marc Dittmann
  • Abhishek Cukkemane
  • Marc van Dijk
  • Alexandre M. J. J. Bonvin
  • Martin Engelhard
  • Marc Baldus


We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such “in silico” data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (


NMR Software Chemical shift Membrane Protein Solid-state NMR 



This work was supported by the Netherlands Organization for Scientific Research (NWO) (grants 700.26.121 and 700.10.443 to M.B.) and by the European Community’s Seventh Framework Program, BioNMR project, contract number 211800, and the FP7 e-Infrastructure project WeNMR (contract no. 261572, We would like to thank Dieter Oesterhelt (Martinsried) for informing us that N. pharaonis can grow with acetate as sole carbon source. Initial work of J. Sauermann on the extraction of N. pharaonis lipids is gratefully acknowledged.

Supplementary material

10858_2012_9681_MOESM1_ESM.docx (21 kb)
Supplementary material 1 (DOCX 21 kb)


  1. Ader C, Frey S, Maas W, Schmidt HB, Goerlich D, Baldus M (2010) Amyloid-like interactions within nucleoporin FG hydrogels. Proc Natl Acad Sci 107:6281–6285ADSCrossRefGoogle Scholar
  2. Alber F, Forster F, Korkin D, Topf M, Sali A (2008) Integrating diverse data for structure determination of macromolecular assemblies. Annu Revi Biochem Palo Alto Annu Rev Palo Alto Annu Rev 77:443–477Google Scholar
  3. Baldus M, Petkova AT, Herzfeld J, Griffin RG (1998) Cross polarization in the tilted frame: assignment and spectral simplification in heteronuclear spin systems. Mol Phys 95:1197–1207ADSCrossRefGoogle Scholar
  4. Brothers MC, Nesbitt A, Hallock M, Rupansinghe S, Tang M, Harris J, Baudry J, Schuler M, Rienstra C (2012). VITAL NMR: using chemical shift derived secondary structure information for a limited set of amino acids to assess homology model accuracy. J Biomol NMR 52:41–56Google Scholar
  5. Castellani F, van Rossum B, Diehl A, Schubert M, Rehbein K, Oschkinat H (2002) Structure of a protein determined by solid-state magic-angle-spinning NMR spectroscopy. Nature 420:98–102ADSCrossRefGoogle Scholar
  6. Cukkemane A, Nand D, Gradmann S, Weingarth M, Kaupp B, Baldus M (2012) Solid-state NMR [13C, 15N] resonance assignments of the nucleotide-binding domain of a bacterial cyclic nucleotide-gated channel. Biomol NMR Assign 6:225Google Scholar
  7. de Vries SJ, van Dijk M, Bonvin AMJJ (2010) The HADDOCK web server for data-driven biomolecular docking. Nat Protoc 5:883–897CrossRefGoogle Scholar
  8. Dominguez C, Boelens R, Bonvin AMJJ (2003) HADDOCK: a protein–protein docking approach based on biochemical or biophysical information. J Am Chem Soc 125:1731–1737CrossRefGoogle Scholar
  9. Etzkorn M, Martell S, Andronesi OC, Seidel K, Engelhard M, Baldus M (2007) Secondary structure, dynamics, and topology of a seven-helix receptor in native membranes, studied by solid-state NMR spectroscopy. Angew Chem Int Ed 46:459–462CrossRefGoogle Scholar
  10. Etzkorn M, Seidel K, Li L, Martell S, Geyer M, Engelhard M, Baldus M (2010) Complex formation and light activation in membrane-embedded sensory rhodopsin II as seen by solid-state NMR spectroscopy. Structure 18:293–300CrossRefGoogle Scholar
  11. Fossi M, Castellani T, Nilges M, Oschkinat H, van Rossum BJ (2005) SOLARIA: a protocol for automated cross-peak assignment and structure calculation for solid-state magic-angle spinning NMR spectroscopy. Angew Chem Int Ed 44:6151–6154CrossRefGoogle Scholar
  12. Gelis I, Bonvin AMJJ, Keramisanou D, Koukaki M, Gouridis G, Karamanou S, Economou A, Kalodimos CG (2007) Structural basis for signal-sequence recognition by the translocase motor SecA as determined by NMR. Cell 131:756–769CrossRefGoogle Scholar
  13. Goddard TD, Kneller D (2006). SPARKY 3. University of California, CaliforniaGoogle Scholar
  14. Guerry P, Herrmann T (2011) Advances in automated NMR protein structure determination. Q Rev Biophys 44:257–309CrossRefGoogle Scholar
  15. Han B, Liu Y, Ginzinger S, Wishart D (2011) SHIFTX2: significantly improved protein chemical shift prediction. J Biomol NMR 50:43–57CrossRefGoogle Scholar
  16. Hefke F, Bagaria A, Reckel S, Ullrich S, Dötsch V, Glaubitz C, Güntert P (2011) Optimization of amino acid type-specific 13C and 15N labeling for the backbone assignment of membrane proteins by solution- and solid-state NMR with the UPLABEL algorithm. J Biomol NMR 49(2):75–84CrossRefGoogle Scholar
  17. Heise H, Hoyer W, Becker S, Andronesi OC, Riedel D, Baldus M (2005) Molecular-level secondary structure, polymorphism, and dynamics of full-length α-synuclein fibrils studied by solid-state NMR. Proc Natl Acad Sci USA 102(44):15871–15876ADSCrossRefGoogle Scholar
  18. Higman V, Flinders J, Hiller M, Jehle S, Markovic S, Fiedler S, van Rossum B-J, Oschkinat H (2009) Assigning large proteins in the solid state: a MAS NMR resonance assignment strategy using selectively and extensively 13C-labelled proteins. J Biomol NMR 44(4):245–260CrossRefGoogle Scholar
  19. Hohenfeld IP, Wegener AA, Engelhard M (1999). Purification of histidine tagged bacteriorhodopsin, pharaonis halorhodopsin and pharaonis sensory rhodopsin II functionally expressed in Escherichia coli. FEBS Lett 442:198–202Google Scholar
  20. Hong M, Jakes K (1999) Selective and extensive C-13 labeling of a membrane protein for solid-state NMR investigations. J Biomol NMR 14:71–74CrossRefGoogle Scholar
  21. Hu KN, Qiang W, Tycko R (2011) A general Monte Carlo/simulated annealing algorithm for resonance assignment in NMR of uniformly labeled biopolymers. J Biomol NMR 50:267–276CrossRefGoogle Scholar
  22. Jehle S, Vollmar BS, Bardiaux B, Dove KK, Rajagopal P, Gonen T, Oschkinat H, Klevit RE (2011) N-terminal domain of αB-crystallin provides a conformational switch for multimerization and structural heterogeneity. Proc Natl Acad Sci 108:6409–6414ADSCrossRefGoogle Scholar
  23. Kato H, van Ingen H, Zhou B-R, Feng H, Bustin M, Kay LE, Bai Y (2011) Architecture of the high mobility group nucleosomal protein 2-nucleosome complex as revealed by methyl-based NMR. Proc Natl Acad Sci 108:12283–12288CrossRefGoogle Scholar
  24. Klare JP, Bordignon E, Doebber M, Fitter J, Kriegsmann J, Chizhov I, Steinhoff HJ, Engelhard M (2006) Effects of solubilization on the structure and function of the sensory rhodopsin II/transducer complex. J Mol Biol 356:1207–1221CrossRefGoogle Scholar
  25. Lange A, Seidel K, Verdier L, Luca S, Baldus M (2003) Analysis of proton–proton transfer dynamics in rotating solids and their use for 3D structure determination. J Am Chem Soc 125:12640–12648CrossRefGoogle Scholar
  26. Lange A, Giller K, Hornig S, Martin-Eauclaire M-F, Pongs O, Becker S, Baldus M (2006) Toxin-induced conformational changes in a potassium channel revealed by solid-state NMR. Nature 440:959–962ADSCrossRefGoogle Scholar
  27. LeMaster DM, Kushlan DM (1996) Dynamical mapping of E. coli thioredoxin via C-13 NMR relaxation analysis. J Am Chem Soc 118:9255–9264CrossRefGoogle Scholar
  28. Linge JP, Habeck M, Rieping W, Nilges M (2003) ARIA: automated NOE assignment and NMR structure calculation. Bioinformatics 19:315–316CrossRefGoogle Scholar
  29. Loquet A, Bardiaux B, Gardiennet C, Blanchet C, Baldus M, Nilges M, Malliavin T, Bockmann A (2008) 3D structure determination of the Crh protein from highly ambiguous solid-state NMR restraints. J Am Chem Soc 130:3579–3589CrossRefGoogle Scholar
  30. Loquet A, Sgourakis NG, Gupta R, Giller K, Riedel D, Goosmann C, Griesinger C, Kolbe M, Baker D, Becker S, Lange A (2012) Atomic model of the type III secretion system needle. Nat Adv (online publication)Google Scholar
  31. Manolikas T, Herrmann T, Meier BH (2008) Protein structure determination from 13C spin-diffusion solid-state NMR spectroscopy. J Am Chem Soc 130:3959–3966CrossRefGoogle Scholar
  32. Melquiond ASJ, Karaca E, Kastritis PL, Bonvin AMJJ (2012) Next challenges in protein–protein docking: from proteome to interactome and beyond. WIREs Comput Mol Sci 2:642–651CrossRefGoogle Scholar
  33. Nand D, Cukkemane A, Becker S, Baldus M (2012) Fractional deuteration applied to biomolecular solid-state NMR spectroscopy. J Biomol NMR 52:91–101Google Scholar
  34. Neal S, Nip AM, Zhang HY, Wishart DS (2003) Rapid and accurate calculation of protein H-1, C-13 and N-15 chemical shifts. J Biomol NMR 26:215–240CrossRefGoogle Scholar
  35. Nelson SJ, Schneider DM, Wand AJ (1991) Implementation of the main chain directed assignment strategy—computer-assisted approach. Biophys J 59:1113–1122CrossRefGoogle Scholar
  36. Renault M, Cukkemane A, Baldus M (2010) Solid-state NMR spectroscopy on complex biomolecules. Angew Chem Int Ed 49:8346–8357CrossRefGoogle Scholar
  37. Renault M, Bos MP, Tommassen J, Baldus M (2011) Solid-state NMR on a large multidomain integral membrane protein: the outer membrane protein assembly factor BamA. J Am Chem Soc 133:4175–4177CrossRefGoogle Scholar
  38. Renault M, Pawsey S, Bos MP, Koers EJ, Nand D, Tommassen-van Boxtel R, Rosay M, Tommassen J, Maas WE, Baldus M (2012a) Solid-state NMR spectroscopy on cellular preparations enhanced by dynamic nuclear polarization. Angew Chem Int Ed 51:2998–3001CrossRefGoogle Scholar
  39. Renault M, Tommassen-van Boxtel R, Bos MP, Post JA, Tommassen J, Baldus M (2012b) Cellular solid-state nuclear magnetic resonance spectroscopy. Proc Natl Acad Sci 109:4863–4868ADSCrossRefGoogle Scholar
  40. Rosen MK, Gardner KH, Willis RC, Parris WE, Pawson T, Kay LE (1996) Selective methyl group protonation of perdeuterated proteins. J Mol Biol 263:627–636CrossRefGoogle Scholar
  41. Ruschak AM, Kay LE (2010) Methyl groups as probes of supra-molecular structure, dynamics and function. J Biomol NMR 46:75–87CrossRefGoogle Scholar
  42. Scholz I, Huber M, Manolikas T, Meier BH, Ernst M (2008) MIRROR recoupling and its application to spin diffusion under fast magic-angle spinning. Chem Phys Lett 460:278–283ADSCrossRefGoogle Scholar
  43. Schunke S, Stoldt M, Novak K, Kaupp UB, Willbold D (2009) Solution structure of the Mesorhizobium loti K1 channel cyclic nucleotide-binding domain in complex with cAMP. EMBO Rep 10:729–735CrossRefGoogle Scholar
  44. Seidel K, Etzkorn M, Heise H, Becker S, Baldus M (2005) High-resolution solid-state NMR studies on uniformly C-13, N-15 -labeled ubiquitin. Chem BioChem 6:1638–1647Google Scholar
  45. Seidel K, Etzkorn M, Schneider R, Ader C, Baldus M (2009) Comparative analysis of nmr chemical shift predictions for proteins in the solid phase. Solid State NMR 35:235–242CrossRefGoogle Scholar
  46. Shen Y, Bax A (2010) SPARTA+: a modest improvement in empirical NMR chemical shift prediction by means of an artificial neural network. J Biomol NMR 48:13–22CrossRefGoogle Scholar
  47. Stevens T, Fogh R, Boucher W, Higman V, Eisenmenger F, Bardiaux B, van Rossum B-J, Oschkinat H, Laue E (2011) A software framework for analysing solid-state MAS NMR data. J Biomol NMR 51:437–447CrossRefGoogle Scholar
  48. Vuister GW, Kim SJ, Wu C, Bax A (1994) 2d and 3d NMR-study of phenylalanine residues in proteins by reverse isotopic labeling. J Am Chem Soc 116:9206–9210CrossRefGoogle Scholar
  49. Wang Y, Jardetzky O (2002) Probability-based protein secondary structure identification using combined NMR chemical-shift data. Protein Sci 11:852–861Google Scholar
  50. Wegener AA, Klare JP, Engelhard M, Steinhoff HJ (2001) Structural insights into the early steps of receptor-transducer signal transfer in archaeal phototaxis. EMBO J 20:5312–5319CrossRefGoogle Scholar
  51. Zimmerman DE, Kulikowski CA, Huang YP, Feng WQ, Tashiro M, Shimotakahara S, Chien CY, 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 Dordrecht 2012

Authors and Affiliations

  • Sabine Gradmann
    • 1
  • Christian Ader
    • 1
  • Ines Heinrich
    • 2
  • Deepak Nand
    • 1
  • Marc Dittmann
    • 2
  • Abhishek Cukkemane
    • 1
  • Marc van Dijk
    • 1
  • Alexandre M. J. J. Bonvin
    • 1
  • Martin Engelhard
    • 2
  • Marc Baldus
    • 1
  1. 1.Faculty of Science, Bijvoet Center for Biomolecular ResearchUtrecht UniversityUtrechtThe Netherlands
  2. 2.Department of Physical BiochemistryMax Planck Institute for Molecular PhysiologyDortmundGermany

Personalised recommendations