Chapter 20. Synergy of Computational and Experimental Methods in Carbohydrate 3D Structure Determination and Validation

  1. Claus-Wilhelm von der Lieth1,
  2. Thomas Lütteke2 and
  3. Martin Frank1
  1. Thomas Lütteke2 and
  2. Martin Frank1

Published Online: 13 NOV 2009

DOI: 10.1002/9780470029619.ch20

Bioinformatics for Glycobiology and Glycomics: An Introduction

Bioinformatics for Glycobiology and Glycomics: An Introduction

How to Cite

Lütteke, T. and Frank, M. (2009) Synergy of Computational and Experimental Methods in Carbohydrate 3D Structure Determination and Validation, in Bioinformatics for Glycobiology and Glycomics: An Introduction (eds C.-W. von der Lieth, T. Lütteke and M. Frank), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470029619.ch20

Editor Information

  1. 1

    Molecular Structure Analysis Core Facility, Deutsches Krebsforschungszentrum (German Cancer Research Center), Heidelberg, Germany

  2. 2

    Faculty of Veterinary Medicine, Institute of Biochemistry and Endocrinology, Justus-Liebig University Gießen, Gießen, Germany

Author Information

  1. 1

    Molecular Structure Analysis Core Facility, Deutsches Krebsforschungszentrum (German Cancer Research Center), Heidelberg, Germany

  2. 2

    Faculty of Veterinary Medicine, Institute of Biochemistry and Endocrinology, Justus-Liebig University Gießen, Gießen, Germany

Publication History

  1. Published Online: 13 NOV 2009
  2. Published Print: 11 DEC 2009

ISBN Information

Print ISBN: 9780470016671

Online ISBN: 9780470029619

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Keywords:

  • X-ray crystallography;
  • Protein Data Bank (PDB);
  • Nuclear magnetic resonance (NMR);
  • Carbohydrate conformation;
  • 3D Structure;
  • Data mining;
  • Torsion angles;
  • Phi/psi plot;
  • Validation

Summary

The foremost experimental techniques to resolve the 3D structures of carbohydrates are NMR spectroscopy and X-ray crystallography. The Protein Data Bank (PDB) is the largest publicly available resource of such 3D structures. About 7% of its entries contain carbohydrate residues, most of which are covalently linked to glycoproteins or non-covalently bound in protein–carbohydrate complexes. From these data, information about preferred torsion angles or similar properties of the carbohydrates can be determined. This information forms the basis of several computational methods such as modeling studies, or can be used to validate calculated data. In NMR studies, the application of theoretical methods aids researchers in interpreting the primary experimental data. Unfortunately, a rather high rate of errors is present within the carbohydrate residues in the PDB. Recently software tools have become available to identify such errors automatically, which can help experimentalists to find problems before submission of their data to public databases and also users of the data to filter out erroneous structures.