Skip to main content
SpringerLink
Log in

Bacterial, Plant, and Fungal Carbohydrate Structure Databases: Daily Usage

  • Protocol
  • First Online:
Glycoinformatics

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

Abstract

Natural carbohydrates play important roles in living systems and therefore are used as diagnostic and therapeutic targets. The main goal of glycomics is systematization of carbohydrates and elucidation of their role in human health and disease. The amount of information on natural carbohydrates accumulates rapidly, but scientists still lack databases and computer-assisted tools needed for orientation in the glycomic information space. Therefore, freely available, regularly updated, and cross-linked databases are demanded.

Bacterial Carbohydrate Structure Database (Bacterial CSDB) was developed for provision of structural, bibliographic, taxonomic, NMR spectroscopic, and other related information on bacterial and archaeal carbohydrate structures. Its main features are (1) coverage above 90 %, (2) high data consistence (above 90 % of error-free records), and (3) presence of manually verified bibliographic, NMR spectroscopic, and taxonomic annotations. Recently, CSDB has been expanded to cover carbohydrates of plant and fungal origin. The achievement of full coverage in the plant and fungal domains is expected in the future. CSDB is freely available on the Internet as a web service at http://csdb.glycoscience.ru. This chapter aims at showing how to use CSDB in your daily scientific practice.

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. Shriver Z, Raguram S, Sasisekharan K (2004) Glycomics: a pathway to a class of new and improved therapeutics. Nat Rev Drug Discov 3:863–873

    Article  CAS  PubMed  Google Scholar 

  2. Slovin SF et al (2005) A bivalent conjugate vaccine in the treatment of biochemically relapsed prostate cancer: a study of glycosylated MUC-2-KLH and Globo H-KLH conjugate vaccines given with the new semi-synthetic saponin immunological adjuvant GPI-0100 OR QS-21. Vaccine 23:3114–3122

    Article  CAS  PubMed  Google Scholar 

  3. Pantophlet R, Wilson IA, Burton DR (2003) Hyperglycosylated mutants of human immunodeficiency virus (HIV) type 1 monomeric gp120 as novel antigens for HIV vaccine design. J Virol 77:5889–5901

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Jones C (2005) Vaccines based on the cell surface carbohydrates of pathogenic bacteria. An Acad Bras Cienc 77:293–324

    Article  CAS  PubMed  Google Scholar 

  5. Gornik O et al (2006) Glycoscience – a new frontier in rational drug design. Acta Pharm 56:19–30

    CAS  PubMed  Google Scholar 

  6. Ernst B, Magnani JL (2009) From carbohydrate leads to glycomimetic drugs. Nat Rev Drug Discov 8:661–677

    Article  CAS  PubMed  Google Scholar 

  7. Astronomo RD, Burton DR (2010) Carbohydrate vaccines: developing sweet solutions to sticky situations? Nat Rev Drug Discov 9:308–324

    Article  CAS  PubMed  Google Scholar 

  8. Boltje TJ, Buskas T, Boons G-J (2009) Opportunities and challenges in synthetic oligosaccharide and glycoconjugate research. Nat Chem 1:611–622

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  9. von der Lieth C-W, Lütteke T, Frank M (2006) The role of informatics in glycobiology research with special emphasis on automatic interpretation of MS spectra. Biochim Biophys Acta 1760:568–577

    Article  PubMed  Google Scholar 

  10. Beattie GA, Lindow SE (1999) Bacterial colonization of leaves: a spectrum of strategies. Phytopathology 89:353–359

    Article  CAS  PubMed  Google Scholar 

  11. Duus J, Gotfredsen CH, Bock K (2000) Carbohydrate structural determination by NMR spectroscopy: modern methods and limitations. Chem Rev 100:4589–4614

    Article  CAS  PubMed  Google Scholar 

  12. Hricovini M (2004) Structural aspects of carbohydrates and the relation with their biological properties. Curr Med Chem 11:2565–2583

    Article  CAS  PubMed  Google Scholar 

  13. Harvey D (2005) Proteomic analysis of glycosylation: structural determination of N- and O-linked glycans by mass spectrometry. Expert Rev Proteomics 2:87–101

    Article  CAS  PubMed  Google Scholar 

  14. Toukach P et al (2007) Sharing of worldwide distributed carbohydrate-related digital resources: online connection of the bacterial carbohydrate structure DataBase and GLYCOSCIENCES.de. Nucl Acids Res 35(Database):D280–D286

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Ranzinger R et al (2009) Glycome-DB.org: a portal for querying across the digital world of carbohydrate sequences. Glycobiology 19:1563–1567

    Article  CAS  PubMed  Google Scholar 

  16. Herget S et al (2008) Statistical analysis of the bacterial carbohydrate structure data base (BCSDB): characteristics and diversity of bacterial carbohydrates in comparison with mammalian glycans. BMC Struct Biol 8:35

    Article  PubMed Central  PubMed  Google Scholar 

  17. Doubet S et al (1989) The complex carbohydrate structure database. Trends Biochem Sci 14:475–477

    Article  CAS  PubMed  Google Scholar 

  18. Doubet S, Albersheim P (1992) CarbBank. Glycobiology 2:505

    Article  CAS  PubMed  Google Scholar 

  19. Lütteke T et al (2006) GLYCOSCIENCES.de: an Internet portal to support glycomics and glycobiology research. Glycobiology 16:71R–81R

    Article  PubMed  Google Scholar 

  20. Cooper CA et al (2003) GlycoSuiteDB: a curated relational database of glycoprotein glycan structures and their biological sources. 2003 Update. Nucleic Acids Res 31:511–513

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Raman R et al (2006) Advancing glycomics: implementation strategies at the consortium for functional glycomics. Glycobiology 16:82R–90R

    Article  CAS  PubMed  Google Scholar 

  22. Hashimoto K et al (2006) KEGG as a glycome informatics resource. Glycobiology 16:63R–70R

    Article  CAS  PubMed  Google Scholar 

  23. Campbell MP et al (2008) GlycoBase and autoGU: tools for HPLC-based glycan analysis. Bioinformatics 24:1214–1216

    Article  CAS  PubMed  Google Scholar 

  24. Maes E et al (2009) SOACS index: an easy NMR-based query for glycan retrieval. Carbohydr Res 344:322–330

    Article  CAS  PubMed  Google Scholar 

  25. Stenutz R, Weintraub A, Widmalm G (2006) The structures of Escherichia coli O-polysaccharide antigens. FEMS Microbiol Rev 30:382–403

    Article  CAS  PubMed  Google Scholar 

  26. von der Lieth C-W et al (2011) EUROCarbDB: an open-access platform for glycoinformatics. Glycobiology 21:493–502

    Article  PubMed Central  PubMed  Google Scholar 

  27. Campbell MP et al (2011) UniCarbKB: putting the pieces together for glycomics research. Proteomics 11:4117–4121

    Article  CAS  PubMed  Google Scholar 

  28. Egorova KS, Toukach PV (2012) Critical analysis of CCSD data quality. J Chem Inf Model 52:2812–2814

    Article  CAS  PubMed  Google Scholar 

  29. Egorova KS, Toukach PV (2014) Expansion of coverage of carbohydrate structure database (CSDB). Carbohydr Res 389:112–114

    Article  CAS  PubMed  Google Scholar 

  30. Toukach PV (2011) Bacterial carbohydrate structure database 3: principles and realization. J Chem Inf Model 51:159–170

    Article  CAS  PubMed  Google Scholar 

  31. Aoki-Kinoshita KF et al (2013) Introducing glycomics data into the semantic Web. J Biomed Semantics 4:39

    Article  PubMed Central  PubMed  Google Scholar 

  32. Ceroni A, Dell A, Haslam SM (2007) The GlycanBuilder: a fast, intuitive and flexible software tool for building and displaying glycan structures. Source Code Biol Med 2:3

    Article  PubMed Central  PubMed  Google Scholar 

  33. Herget S et al (2008) GlycoCT – a unifying sequence format for carbohydrates. Carbohydr Res 343:2162–2171

    Article  CAS  PubMed  Google Scholar 

  34. Kirschner KN et al (2008) GLYCAM06: a generalizable biomolecular force field. Carbohydrates. J Comput Chem 29:622–655

    Article  CAS  PubMed  Google Scholar 

  35. Sayers EW et al (2011) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 39:D38–D51

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  36. Loss A et al (2002) SWEET-DB: an attempt to create annotated data collections for carbohydrates. Nucleic Acids Res 30:405–408

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  37. Sharon N (1988) Nomenclature of glycoproteins, glycopeptides and peptidoglycans. Pure Appl Chem 60:1389–1394

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  40. Toukach FV, Ananikov VP (2013) Recent advances in computational predictions of NMR parameters for the structure elucidation of carbohydrates: methods and limitations. Chem Soc Rev 42:8376–8415

    Article  CAS  PubMed  Google Scholar 

  41. Kapaev RR, Egorova KS, Toukach PV (2014) Carbohydrate structure generalization scheme for database-driven simulation of experimental observables, such as NMR chemical shifts. J Chem Inf Model 54:2594–2611 http://www.lcme.org/standard.htm

    Google Scholar 

Download references

Acknowledgments

The Bacterial CSDB was supported by the International Science and Technology Center grant 1197p and the Russian Foundation for Basic Research grant 05-07-90099. The Plant and Fungal CSDB was supported by the Russian Foundation for Basic Research grant 12-04-00324. The lists of project participants are available at http://csdb.glycoscience.ru/bacterial/index.html?help=credits and http://csdb.glycoscience.ru/plant_fungal/index.html?help=credits.

Author information

Authors and Affiliations

  1. N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospekt 47, Moscow, 119991, Russia

    Philip V. Toukach & Ksenia S. Egorova

Authors
  1. Philip V. Toukach
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ksenia S. Egorova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Philip V. Toukach .

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

Toukach, P.V., Egorova, K.S. (2015). Bacterial, Plant, and Fungal Carbohydrate Structure Databases: Daily Usage. 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_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2343-4_5

  • 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