Skip to main content
SpringerLink
Log in

NMR Chemical Shift Prediction of Glycans: Application of the Computer Program CASPER in Structural Analysis

  • Protocol
  • First Online:
Glycoinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1273))

Abstract

Carbohydrate molecules have highly complex structures and the constituent monosaccharides and substituents are linked to each other in a large number of ways. NMR spectroscopy can be used to unravel these structures, but the process may be tedious and time-consuming. The computerized approach based on the CASPER program can facilitate rapid structural determination of glycans with little user intervention, which results in the most probable primary structure of the investigated carbohydrate material. Additionally, 1H and 13C NMR chemical shifts of a user-defined structure can be predicted, and this tool may thus be employed in many aspects where NMR spectroscopy plays an important part of a study.

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

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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. Bubb WA (2003) NMR spectroscopy in the study of carbohydrates: characterizing the structural complexity. Concepts Magn Reson 19A:1–19

    Article  CAS  Google Scholar 

  2. Jiménez-Barbero J, Peters T (eds) (2003) NMR spectroscopy of glycoconjugates. Wiley-VCH, Weinheim

    Google Scholar 

  3. Meiler J, Köck M (2004) Novel methods of automated structure elucidation based on 13C NMR spectroscopy. Magn Reson Chem 42:1042–1045

    Article  CAS  PubMed  Google Scholar 

  4. Satoh H, Koshino H, Uno T et al (2005) Effective consideration of ring structures in CAST/CNMR for highly accurate 13C NMR chemical shift prediction. Tetrahedron 61:7431–7437

    Article  CAS  Google Scholar 

  5. Lam SL (2007) DSHIFT: a web server for predicting DNA chemical shifts. Nucleic Acids Res 35:W713–W717

    Article  PubMed Central  PubMed  Google Scholar 

  6. Elyashberg ME, Williams AJ, Martin GE (2008) Computer-assisted structure verification and elucidation tools in NMR-based structure elucidation. Prog Nucl Magn Reson Spectr 53:1–104

    Article  CAS  Google Scholar 

  7. Blinov KA, Smurnyy YD, Churanova TS et al (2009) Development of a fast and accurate method of 13C NMR chemical shift prediction. Chemometr Intell Lab Syst 97:91–97

    Article  CAS  Google Scholar 

  8. Spanton SG, Whittern D (2009) The development of an NMR chemical shift prediction application with the accuracy necessary to grade proton NMR spectra for identity. Magn Reson Chem 47:1055–1061

    Article  CAS  PubMed  Google Scholar 

  9. Kohlhoff KJ, Robustelli P, Cavalli A et al (2009) Fast and accurate predictions of protein NMR chemical shifts from interatomic distances. J Am Chem Soc 131:13894–13895

    Article  CAS  PubMed  Google Scholar 

  10. Jakovkin I, Sternberg U, Ulrich AS (2010) Rapid computation of protein NMR properties – an optimal way to chemical shift driven protein structure refinement. Biochem Med Chem (Biomedch'10), Cambridge, Great Britain, February 23–25, pp 273-276

    Google Scholar 

  11. Jansson P-E, Kenne L, Widmalm G (1987) CASPER – a computerized approach to structure determination of polysaccharides using information from N.M.R. spectroscopy and simple chemical analyses. Carbohydr Res 168:67–77

    Article  CAS  Google Scholar 

  12. McIntyre MK, Small GW (1987) Carbon-13 nuclear magnetic resonance spectrum simulation methodology for the structure elucidation of carbohydrates. Anal Chem 59:1805–1811

    Article  CAS  PubMed  Google Scholar 

  13. Lipkind GM, Shashkov AS, Knirel YA et al (1988) A computer-assisted structural analysis of regular polysaccharides on the basis of 13C-N.M.R. data. Carbohydr Res 175:59–75

    Article  CAS  PubMed  Google Scholar 

  14. Cumming DA, Hellerqvist C, Touster O (1988) On the utility of 13C-N.M.R. spectroscopy in the identification of the primary structures of manno-oligosaccharides and glycopeptides. Carbohydr Res 179:369–380

    Article  CAS  PubMed  Google Scholar 

  15. Toukash FV, Shashkov AS (2001) Computer-assisted structural analysis of regular glycopolymers on the basis of 13C NMR data. Carbohydr Res 335:101–114

    Article  Google Scholar 

  16. Toukash FV (2011) Bacterial carbohydrate structure database 3: principles and realization. J Chem Inf Model 51:159–170

    Article  Google Scholar 

  17. Pereira F (2011) Prediction of the anomeric configuration, type of linkage, and residues in disaccharides from 1D 13C NMR data. Carbohydr Res 346:960–972

    Article  CAS  PubMed  Google Scholar 

  18. Loß A, Stenutz R, Schwarzer E et al (2006) GlyNest and CASPER: two independent approaches to estimate 1H and 13C NMR shifts of glycans available through a common web-interface. Nucleic Acids Res 34:W733–W737

    Article  PubMed Central  PubMed  Google Scholar 

  19. Maes E, Bonachera F, Strecker G et al (2009) SOACS index: an easy NMR-based query for glycan retrieval. Carbohydr Res 344:322–330

    Article  CAS  PubMed  Google Scholar 

  20. Jansson P-E, Kenne L, Widmalm G (1991) CASPER: a computer program used for structural analysis of carbohydrates. J Chem Inf Comput Sci 31:508–516

    Article  CAS  PubMed  Google Scholar 

  21. Aires-de-Sousa J, Hemmer MC, Gasteiger J (2002) Prediction of 1H NMR chemical shifts using neural networks. Anal Chem 74:80–90

    Article  CAS  PubMed  Google Scholar 

  22. Meiler J (2003) PROSHIFT: protein chemical shift prediction using artificial neural networks. J Biomol NMR 26:25–37

    Article  CAS  PubMed  Google Scholar 

  23. 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 48:13–22

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Meyer B, Hansen T, Nute D et al (1991) Identification of the 1H-NMR spectra of complex oligosaccharides with artificial neural networks. Science 251:542–544

    Article  CAS  PubMed  Google Scholar 

  25. Ball JW, Jurs PC (1993) Simulation of polysaccharide 13C nuclear magnetic resonance spectra using regression analysis and neural networks. Anal Chem 65:3615–3621

    Article  CAS  Google Scholar 

  26. Gerbst AG, Grachev AA, Ustuzhanina NE et al (2010) Application of artificial neural networks for analysis of 13C NMR spectra of fucoidans. J Carbohydr Chem 29:92–102

    Article  CAS  Google Scholar 

  27. Jansson P-E, Stenutz R, Widmalm G (2006) Sequence determination of oligosaccharides and regular polysaccharides using NMR spectroscopy and a novel Web-based version of the computer program CASPER. Carbohydr Res 341:1003–1010

    Article  CAS  PubMed  Google Scholar 

  28. Lundborg M, Widmalm G (2011) Structural analysis of glycans by NMR chemical shift prediction. Anal Chem 83:1514–1517

    Article  CAS  PubMed  Google Scholar 

  29. Lundborg M, Fontana C, Widmalm G (2011) Automatic structure determination of regular polysaccharides based solely on NMR spectroscopy. Biomacromolecules 12:3851–3855

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  30. Kuttel M, Widmalm G, Mao Y et al (2011) CarbBuilder: an adjustable tool for building 3D molecular structures of carbohydrates for molecular simulation. Proceedings of the 7th IEEE International Conference eScience, 5–8 Dec, Stockholm, pp 395–402

    Google Scholar 

  31. Vranken WV, Boucher W, Stevens TJ et al (2005) The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins Struct Funct Bioinf 59:687–696

    Article  CAS  Google Scholar 

  32. Pluschke G, Moll A, Kusecek B et al (1986) Sodium dodecyl sulfate-polyacrylamide gel electrophoresis and monoclonal antibodies as tools for the subgrouping of Escherichia coli lipopolysaccharides O18 and O23 antigens. Infect Immun 51:286–293

    PubMed Central  CAS  PubMed  Google Scholar 

  33. Jansson P-E, Kenne L, Widmalm G (1989) Structure of the O-antigen polysaccharide of Escherichia coli O18ac; a revision using computer-assisted structural analysis with the program CASPER. Carbohydr Res 193:322–325

    Article  CAS  PubMed  Google Scholar 

  34. Jann B, Shashkov AS, Gupta DS et al (1992) The O18 antigens (lipopolysaccharides) of Escherichia coli. Structural characterization of the O18A, O18A1, O18B and O18B1-specific polysaccharides. Eur J Biochem 210:241–248

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was funded by the sixth Research Framework Program of the European Union (Contract: RIDS Contract number 011952) as part of the EUROCarbDB project. It was furthermore supported by grants from the Swedish Research Council and The Knut and Alice Wallenberg Foundation. We thank Dr. Ralfh Wollin, SMI, Stockholm, Sweden, and Dr. Daniel Spencer, Ludger Ltd, Abingdon, UK, for kindly providing carbohydrate material used for spectral presentation in this study.

Author information

Authors and Affiliations

  1. Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, Hus A, Plan 6, Svante Arrhenius Väg 16C, Stockholm, 106 91, Sweden

    Göran Widmalm

  2. Stockholm Center for Biomembrane Research, Arrhenius Laboratory, Stockholm University, Stockholm, Sweden

    Göran Widmalm

  3. Magnus Lundborg, Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Solna, 171 21, Sweden

    Göran Widmalm

  4. Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Solna, 171 21, Sweden

    Magnus Lundborg

Authors
  1. Magnus Lundborg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Göran Widmalm
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Göran Widmalm .

Editor information

Editors and Affiliations

  1. Justus-Liebig-University, Giessen, Germany

    Thomas Lütteke

  2. Biognos AB, Göteborg, Sweden

    Martin Frank

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this protocol

Cite this protocol

Lundborg, M., Widmalm, G. (2015). NMR Chemical Shift Prediction of Glycans: Application of the Computer Program CASPER in Structural Analysis. In: Lütteke, T., Frank, M. (eds) Glycoinformatics. Methods in Molecular Biology, vol 1273. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2343-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2343-4_3

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-2342-7

  • Online ISBN: 978-1-4939-2343-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation