Journal of Biomolecular NMR

, Volume 42, Issue 1, pp 11–21 | Cite as

Graphical interpretation of Boolean operators for protein NMR assignments

  • Dries Verdegem
  • Klaas Dijkstra
  • Xavier Hanoulle
  • Guy LippensEmail author


We have developed a graphics based algorithm for semi-automated protein NMR assignments. Using the basic sequential triple resonance assignment strategy, the method is inspired by the Boolean operators as it applies “AND”-, “OR”- and “NOT”-like operations on planes pulled out of the classical three-dimensional spectra to obtain its functionality. The method’s strength lies in the continuous graphical presentation of the spectra, allowing both a semi-automatic peaklist construction and sequential assignment. We demonstrate here its general use for the case of a folded protein with a well-dispersed spectrum, but equally for a natively unfolded protein where spectral resolution is minimal.


Computer-aided sequential assignment Graphical semi-automatic protein assignment method Boolean operators in NMR Assignment of structured proteins Assignment of unfolded proteins 



We thank Dr. I. Landrieu for sample preparation, Dr. J.-M. Wieruszeski for collecting the NMR spectra and Dr. T. Stevens and W. Boucher of the University of Cambridge, Department of Biochemistry for implementing our protein NMR assignment tools in the CcpNmr software suite. The 600 MHz facility used in this study was funded by the Région Nord—Pas de Calais (France), the CNRS and the Institut Pasteur de Lille. Part of this work was funded by a grant of the Agence National de la Recherche (ANR 05 BLAN 0320-0; Tau:Tubulin). D.V. received a predoctoral grant of the French Ministère de la Recherche.


  1. Andrec M, Levy RM (2002) Protein sequential resonance assignments by combinatorial enumeration using 13Cα chemical shifts and their (i,i − 1) sequential connectivities. J Biomol NMR 23:263–270CrossRefGoogle Scholar
  2. Atreya H, Chary K, Govil G (2000) Automated NMR assignments of proteins for high throughput structure determination: TATAPRO II. Curr Sci 83:1372–1376Google Scholar
  3. Atreya H, Sahu S, Chary K, Govil G (2000) A tracked approach for automated NMR assignments in proteins (TATAPRO). J Biomol NMR 17:125–136CrossRefGoogle Scholar
  4. Bailey-Kellogg C, Widge A, Kelley JJ, Berardi MJ, Bushweller JH, Donald BR (2000) The NOESY jigsaw: automated protein secondary structure and main-chain assignment from sparce unassigned NMR data. J Comput Biol 7:537–558CrossRefGoogle Scholar
  5. Bailey-Kellogg C, Chainraj S, Pandurangan G (2005) A random graph approach to NMR sequential assignment. J Comput Biol 12:569–583CrossRefGoogle Scholar
  6. Bartels C, Billeter M, Güntert P, Wüthrich K (1996) Automated sequence-specific NMR assignment of homologous proteins using the program GARANT. J Biomol NMR 7:207–213CrossRefGoogle Scholar
  7. 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
  8. Bernstein R, Cieslar C, Ross A, Oschkinat H, Freund J, Holak TA (1993) Computer-assisted assignment of multidimensional NMR spectra of proteins: application to 3D NOESY-HMQC and TOCSY-HMQC spectra. J Biomol NMR 3:245–251CrossRefGoogle Scholar
  9. Buchler NE, Zuiderweg ER, Wang H, Goldstein RA (1997) Protein heteronuclear NMR assignments using mean-field simulated annealing. J Magn Reson 125:34–42CrossRefADSGoogle Scholar
  10. Choy W, BC S, Zhu G (1997) Using neural network predicted secondary structure information in automatic protein NMR assignment. J Chem Inf Comput Sci 37:1086–1094CrossRefGoogle Scholar
  11. Coggins BE, Zhou P (2003) PACES: protein sequential assignment by computer-assisted exhaustive search. J Biomol NMR 26:93–111CrossRefGoogle Scholar
  12. Croft D, Kemmink J, Neidig KP, Oschkinat H (1997) Tools for the automated assignment of high-resolution three-dimensional protein NMR spectra based on pattern recognition techniques. J Biomol NMR 10:207–219CrossRefGoogle Scholar
  13. Eads C, Kuntz I (1989) Programs for computer-assisted sequential assignment of proteins. J Magn Reson 82:467–482Google Scholar
  14. Eccles C, Güntert P, Billeter M, Wüthrich K (1991) Efficient analysis of protein 2D NMR spectra using the software package EASY. J Biomol NMR 1:111–130CrossRefGoogle Scholar
  15. Eghbalnia HR, Bahrami A, Wang L, Assadi A, Markley JL (2005) Probabilistic identification of spin systems and their assignments including coil-helix inference as output (PISTACHIO). J Biomol NMR 32:219–233CrossRefGoogle Scholar
  16. Friedrichs M, Mueller L, Wittekind M (1994) An automated procedure for the assignment of protein 1HN, 15N, 13C alpha, 1H alpha, 13C beta and 1H beta resonances. J Biomol NMR 4:703–726CrossRefGoogle Scholar
  17. Goddard T, Kneller D (1989) Sparky 3. University of California, San FranciscoGoogle Scholar
  18. Görler A, Gronwald W, Neidig KP, Kalbitzer HR (1999) Computer assisted assignment of 13C and 15N edited 3D-NOESY-HSQC spectra using back calculated and experimental spectra. J Magn Reson 137:39–45CrossRefADSGoogle Scholar
  19. Grishaev A, Llinás M (2004) BACUS: a Bayesian protocol for the identification of protein NOESY spectra via unassigned spin systems. J Biomol NMR 28:1–10CrossRefGoogle Scholar
  20. Gronwald W, Willard L, Jellard T, Boyko RF, Rajarathnam K, Wishart DS, Sönnichsen FD, Sykes BD (1998) CAMRA: chemical shift based computer aided protein NMR assignments. J Biomol NMR 12:395–405CrossRefGoogle Scholar
  21. 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
  22. Güntert P, Salzmann M, Braun D, Wüthrich K (2000) Sequence-specific NMR assignment of proteins by global fragment mapping with the program MAPPER. J Biomol NMR 18:129–137CrossRefGoogle Scholar
  23. Hanoulle X, Melchior A, Sibille N, Parent B, Denys A, Wieruszeski JM, Horvath D, Allain F, Lippens G, Landrieu I (2007) Structural and functional characterisation of the interaction between cyclophilin B and a heparin derived oligosaccharide. J Biol Chem 282:34148–134158Google Scholar
  24. Hare BJ, Prestegard JH (1994) Application of neural networks to automated assignment of NMR spectra in proteins. J Biomol NMR 4:35–46CrossRefGoogle Scholar
  25. Helgstrand M, Kraulis P, Allard P, Härd T (2000) Ansig for Windows: an interactive computer program for semiautomatic assignment of protein NMR spectra. J Biomol NMR 18:329–336CrossRefGoogle Scholar
  26. 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 Biomol NMR 319:209–227Google Scholar
  27. 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
  28. Hitchens T, Lukin JA, Zhan YP, McCallum SA, Rule GS (2003) MONTE: an automated Monte Carlo based approach to nuclear magnetic resonance assignment of proteins. J Biomol NMR 25:1–9CrossRefGoogle Scholar
  29. Hyberts SG, Wagner G (2003) IBIS—A tool for automated sequential assignment of proteins spectra from triple resonance experiments. J Biomol NMR 26:335–344CrossRefGoogle Scholar
  30. Ikura M, Kay LE, Bax A (1990) A novel approach for sequential assignment of 1H, 13C, and 15N spectra of larger proteins: heteronuclear triple-resonance three-dimensional NMR spectroscopy. Application to calmodulin. Biochemistry 29:4659–4667CrossRefGoogle Scholar
  31. Johnson BA, Blevins RA (1994) NMR view: a computer program for the visualization and analysis of NMR data. J Biomol NMR 4:603–614CrossRefGoogle Scholar
  32. Jung YS, Zweckstetter M (2004) Mars—robust automatic backbone assignment of proteins. J Biomol NMR 30:11–23CrossRefGoogle Scholar
  33. Kay LE, Ikura M, Tschudin R, Bax A (1990) Three-dimensional triple-resonance NMR spectroscopy of isotopically enriched proteins. J Magn Reson 89:496–514Google Scholar
  34. Kjaer M, Andersen K, Poulsen F (1994) Automated and semiautomated analysis of homo- and heteronuclear multidimensional nuclear magnetic resonance spectra of proteins: the program PRONTO. Methods Enzymol 239:288–308CrossRefGoogle Scholar
  35. Kleywegt GJ, Boelens R, Cox M, Llinás M, Kaptein R (1991) Computer-assisted assignment of 2D 1H NMR spectra of proteins: basic algorithms and application to phoratoxin B. J Biomol NMR 1:23–47CrossRefGoogle Scholar
  36. Kobayashi N, Iwahara J, Koshiba S, Tomizawa T, Tochio N, Güntert P, Kigawa T, Yokoyama S (2007) KUJIRA, a package of integrated modules for systematic and interactive analysis of NMR data directed to high-throughput NMR studies. J Biomol NMR 39:31–52CrossRefGoogle Scholar
  37. Kraulis P (1989) ANSIG: a computer program for the assignment of 1H NMR spectra by interactive computer graphics. J Magn Reson 84:627–633Google Scholar
  38. Kraulis P (1994) Protein three-dimensional structure determination and sequence-specific assignment of 13C and 15N-separated NOE data. A novel real-space ab initio approach. J Mol Biol 243:696–718CrossRefGoogle Scholar
  39. Langmead CJ, Donald BR (2004) An expectation/maximization nuclear vector replacement algorithm for automated NMR assignments. J Biomol NMR 29:111–138Google Scholar
  40. Langmead CJ, Yan A, Lilien R, Wang L, Donald BR (2004) A polynomial-time nuclear vector replacement algorithm for automated NMR resonance assignments. J Comput Biol 11:277–298CrossRefGoogle Scholar
  41. Leutner M, Gschwind RM, Liermann J, Schwarz C, Gemmecker G, Kessler H (1998) Automated backbone assignment of labeled proteins using the threshold accepting algorithm. J Biomol NMR 11:31–43CrossRefGoogle Scholar
  42. Li KB, Sanctuary B (1996) Automated extracting of amino acid spin systems in proteins using 3D HCCH-COSY/TOCSY spectroscopy and constrained partioning algorithm. J Chem Inf Comput Sci 36:585–593CrossRefGoogle Scholar
  43. Li KB, Sanctuary B (1997a) Automated resonance assignment of proteins using heteronuclear 3D NMR. 1. Backbone spin systems extraction and creation of polypeptides. J Chem Inf Comput Sci 37:359–366CrossRefGoogle Scholar
  44. Li KB, Sanctuary B (1997b) Automated resonance assignment of proteins using heteronuclear 3D NMR. 2. Side chain and sequence-specific assignment. J Chem Inf Comput Sci 37:467–477CrossRefGoogle Scholar
  45. Lin G, Xiang W, Tegos T, Li Y (2006) Statistical evaluation of NMR backbone resonance assignment. Int J Bioinform Res Appl 2:147–160Google Scholar
  46. Lin G, Xu D, Chen ZZ, Jiang T, Wen J, Xu Y (2003) Computational assignment of protein backbone NMR peaks by efficient bounding and filtering. J Bioinform Comput Biol 1:387–409CrossRefGoogle Scholar
  47. Lin HN, Wu KP, Chang JM, Hsu WL (2005) GANA—a genetic algorithm for NMR backbone resonance assignment. Nucleic Acids Res 33:4593–4601CrossRefGoogle Scholar
  48. Lukin JA, Gove AP, Talukdar SN, Ho C (1997) Automated probabilistic method for assigning backbone resonances of (13C, 15N)-labeled proteins). J Biomol NMR 9:151–166CrossRefGoogle Scholar
  49. Malliavin T, Pons J, Delsuc M (1998) An NMR assignment module implemented in the Gifa NMR processing program. Bioinformatics 14:624–631CrossRefGoogle Scholar
  50. Malmodin D, Papavoine CH, Billeter M (2003) Fully automated sequence-specific resonance assignments of heteronuclear protein spectra. J Biomol NMR 27:69–79CrossRefGoogle Scholar
  51. Masse JE, Keller R (2005) AutoLink: automated sequential resonance assignment of biopolymers from NMR data by relative-hypothesis-prioritization-based simulated logic. J Magn Reson 174:133–151CrossRefADSGoogle Scholar
  52. Masse JE, Keller R, Pervushin K (2006) SideLink: automated side-chain assignment of biopolymers from NMR data by relative-hypothesis-prioritization-based simulated logic. J Magn Reson 181:45–67CrossRefADSGoogle Scholar
  53. 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
  54. Montelione GT, Wagner G (1990) Conformation-independent sequential NMR connections in isotope-enriched polypeptides by 1H-13C-15N triple resonance experiments. J Magn Reson 87:183–188Google Scholar
  55. Morelle N, Brutscher B, Simorre JP, Marion D (1995) Computer assignment of the backbone resonances of labelled proteins using two-dimensional correlation experiments. J Biomol NMR 5:154–160CrossRefGoogle Scholar
  56. Morris LC, Valafar H, Prestegard JH (2004) Assignment of protein backbone resonances using connectivity, torsion angles and 13Cα chemical shifts. J Biomol NMR 29:1–9CrossRefGoogle Scholar
  57. Moseley H, Montelione G (1999) Automated analysis of NMR assignments and structures for proteins. Curr Opin Struct Biol 9:635–642CrossRefGoogle Scholar
  58. Moseley H, Monleon D, Montelione G (2001) Automatic determination of protein backbone resonance assignments from triple resonance nuclear magnetic resonance data. Methods Enzymol 339:91–108CrossRefGoogle Scholar
  59. 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
  60. Mumenthaler C, Güntert P, Braun W, Wüthrich K (1997) Automated combined assignment of NOESY and three-dimensional protein structure determination. J Biomol NMR 10:351–362CrossRefGoogle Scholar
  61. Neidig KP, Geyer M, Görler A, Antz C, Saffrich R, Beneicke W, Kalbitzer HR (1995) AURELIA, a program for computer-aided analysis of multidimensional NMR spectra. J Biomol NMR 6:255–270CrossRefGoogle Scholar
  62. Oezguen N, Adamian L, Xu Y, Rajarathnam K, Braun W (2002) Automated assignment and 3D structure calculations using combinations of 2D homonuclear and 3D heteronuclear NOESY spectra. J Biomol NMR 22:249–263CrossRefGoogle Scholar
  63. Olson JB, Markley JL (1994) Evaluation of an algorithm for the automated sequential assignment of protein backbone resonances: a demonstration of the connectivity tracing assignment tools (CONTRAST) software package. J Biomol NMR 4:385–410CrossRefGoogle Scholar
  64. Orekhov VY, Ibraghimov V, Billeter M (2001) MUNIN: a new approach to multi-dimensional NMR spectra interpretation. J Biomol NMR 20:49–60CrossRefGoogle Scholar
  65. Oschkinat H, Croft D (1994) Automated assignment of multidimensional nuclear magnetic resonance spectra. Methods Enzymol 239:308–318CrossRefGoogle Scholar
  66. Oschkinat H, Holak T, Cieslar C (1991) Assignment of protein NMR spectra in the light of homonuclear 3D spectroscopy: an automatable procedure based on 3D TOCSY-TOCSY and 3D TOCSY-NOESY. Biopolymers 31:699–712CrossRefGoogle Scholar
  67. Ou HD, Lai HC, Serber Z, Dötsch V (2001) Efficient indentification of amino acid types for fast protein backbone assignments. J Biomol NMR 21:269–273CrossRefGoogle Scholar
  68. Pons J, Delsuc M (1999) RESCUE: an artificial neural network tool for the NMR spectral assignment of proteins. J Biomol NMR 15:15–26CrossRefGoogle Scholar
  69. Pristovšek P, Rüterjans H, Jerala R (2002) Semiautomatic sequence-specific assignment of proteins based on the tertiary structure–the program st2nmr. J Comput Chem 23:335–340Google Scholar
  70. Schubert M, Smalla M, Schmieder P, Oschkinat H (1999) MUSIC in triple-resonance experiments: amino acid type-selective 1H,15N correlations. J Magn Reson 141:34–43CrossRefADSGoogle Scholar
  71. Schubert M, Oschkinat H, Schmieder P (2001a) MUSIC and aromatic residues: amino acid type-selective 1H,15N correlations, III. J Magn Reson 153:186–192CrossRefADSGoogle Scholar
  72. Schubert M, Oschkinat H, Schmieder P (2001b) MUSIC, selective pulses, and tuned delays: amino acid type-selective 1H,15N correlations, II. J Magn Reson 148:61–72CrossRefADSGoogle Scholar
  73. Slupsky CM, Boyko RF, Booth VK, Sykes BD (2003) Smartnotebook: a semi-automated approach to protein sequential NMR resonance assignments. J Biomol NMR 27:313–321Google Scholar
  74. Szyperski T, Banecki B, Braun D, Glaser RW (1998) Sequential resonance assignment of medium-sized 15N/13C-labeled proteins with projected 4D triple resonance NMR experiments. J Biomol NMR 11:387–405CrossRefGoogle Scholar
  75. Szyperski T, Yeh DC, Sukumaran DK, Moseley HN, Montelione GT (2002) Reduced-dimensionality NMR spectroscopy for high-throughput protein resonance assignment. Proc Natl Acad Sci USA 99:8009–8014CrossRefADSGoogle Scholar
  76. Tian F, Valafar H, Prestegard J (2001) A dipolar coupling based strategy for simultaneous resonance assignment and structure determination of protein backbones. J Am Chem Soc 123:11791–11796Google Scholar
  77. van de Ven FJ (1990) PROSPECT, a program for automated interpretation of 2D NMR spectra of proteins. J Magn Reson 86:633–644Google Scholar
  78. Vitek O, Bailey-Kellogg C, Craig B, Kuliniewicz P, Vitek J (2005) Reconsidering complete search algorithms for protein backbone NMR assignment. Bioinformatics 21:230–236CrossRefGoogle Scholar
  79. Vitek O, Bailey-Kellogg C, Craig B, Vitek J (2006) Interential backbone assignment for sparse data. J Biomol NMR 35:187–208CrossRefGoogle Scholar
  80. Vranken WF, Boucher W, Stevens TJ, Fogh RH, Pajon A, Llinás M, Ulrich EL, Markley JL, Ionides J, Laue ED (2005) The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins 59:687–696CrossRefGoogle Scholar
  81. Wan X, Lin G (2006) A graph-based automated NMR backbone resonance sequential assignment. In: Computational systems bioinformatics 2006 conference proceedings, vol 4, pp 55–66Google Scholar
  82. Wan X, Xu D, Slupsky CM, Lin G (2003) Automated protein NMR resonance assignments. In: Proceedings of the IEEE computer society conference on bioinformatics, vol 2, pp 197–208Google Scholar
  83. Wang J, Wang T, Zuiderweg ER, Crippen GM (2005) CASA: an efficient automated assignment of protein mainchain NMR data using an ordered tree search algorithm. J Biomol NMR 33:261–279CrossRefGoogle Scholar
  84. Wehrens R, Buydens L, Kateman G (1991) Validation and refinement of expert systems—interpretation of NMR-spectra as an application in analytical-chemistry. Chemometr Intell Lab Syst 12:57–67CrossRefGoogle Scholar
  85. Wehrens R, Lucasius C, Buydens L, Kateman G (1993a) HIPS, a hybrid self-adapting expert system for nuclear magnetic resonance spectrum interpretation using genetic algorithms. Anal Chim Acta 277:313–324CrossRefGoogle Scholar
  86. Wehrens R, Lucasius C, Buydens L, Kateman G (1993b) Sequential assignment of 2D-NMR spectra of proteins using genetic algorithms. J Chem Inf Comput Sci 33:245–251Google Scholar
  87. Wishart DS, Bigam CG, Holm A, Hodges RS, Sykes BD (1995) 1H, 13C and 15N random coil NMR chemical shifts of the common amino acids. I. Investigation of nearest-neighbour effects. J Biomol NMR 5:67–81CrossRefGoogle Scholar
  88. Wu KP, Chang JM, Chen JB, Chang CF, Wu WJ, Huang TH, Sung TY, Hsu WL (2006) RIBRA—an error-tolerant algorithm for the NMR backbone assignment problem. J Comput Biol 13:229–244CrossRefMathSciNetGoogle Scholar
  89. Xu J, Sanctuary B (1993) CPA: constrained partitioning algorithm for initial assignment of protein 1H resonances from MQF-COSY. J Chem Inf Comput Sci 33:490–500CrossRefGoogle Scholar
  90. Xu J, Strauss S, Sanctuary B, Trimble L (1994) Use of fuzzy mathematics for complete automated assignment of peptide 1H 2D NMR spectra. J Magn Reson B103:53–58Google Scholar
  91. Xu Y, Xu D, Kim D, Olman V, Razumovskaya J, Jiang T (2002) Automated assignment of backbone NMR peaks using constrained bipartite matching. Comput Sci Eng 4:50–62Google Scholar
  92. Xu Y, Wang X, Yang J, Vaynberg J, Qin J (2006) PASA—a program for automated protein NMR backbone signal assignment by pattern-filtering approach. J Biomol NMR 34:41–56CrossRefGoogle Scholar
  93. Zimmerman DE, Montelione GT (1995) Automated analysis of nuclear magnetic resonance assignments for proteins. Curr Opin Struct Biol 5:664–673CrossRefGoogle Scholar
  94. Zimmerman D, Kulikowski C, Wang L, Lyons B, Montelione GT (1994) Automated sequencing of amino acid spin systems in proteins using multidimensional HCC(CO)NH-TOCSY spectroscopy and constraint propagation methods from artificial intelligence. J Biomol NMR 4:241–256CrossRefGoogle Scholar
  95. Zimmerman DE, Kulikowski CA, Huang Y, Feng W, Tashiro M, Shimotakahara S, Chien Cy, 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. 2008

Authors and Affiliations

  • Dries Verdegem
    • 1
  • Klaas Dijkstra
    • 2
  • Xavier Hanoulle
    • 1
  • Guy Lippens
    • 1
    Email author
  1. 1.Unité de Glycobiologie Structurale et Fonctionelle, UMR 8576 CNRS, IFR 147Université des Sciences et Technologies de LilleVilleneuve d’AscqFrance
  2. 2.Department of Biophysical ChemistryUniversity of GroningenGroningenThe Netherlands

Personalised recommendations