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Determination of the Disaccharide Composition of Glycosaminoglycans: Comparison of Chemical and Enzymatic Scission

  • Malcolm Lyon
Part of the BioMethods book series (BIOMETHODS)

Abstract

The glycosaminoglycans (GAGs) are a family of complex linear polysaccharides characterized by a repeating core disaccharide structure comprising of an N-substituted hexosamine and, usually, a uronic acid. They can be usefully categorized into four structural groups: hyaluronate (HA); chondroitin sulphate (CS)/dermatan sulphate (DS); heparan sulphate (HS)/heparin and keratan sulphate (KS). HA possesses a completely invariant repeat sequence and is therefore not considered further. KS is somewhat unusual in containing a neutral sugar rather than a uronate residue. It may also possess a small proportion of branched fucose residues as well as terminal capping sialic acids. The structural analysis of KS is comprehensively discussed in chapter 9. This article will concentrate on disaccharide analyses of the remaining two complex groups: CS/DS and HS/heparin. The N-acetylated galactosaminoglycans CS and DS differ in the exclusive presence of glucuronate (GlcA) in CS, whilst in DS a variable proportion of the G1cA residues are epimerized to iduronate (IdoA). Potential O-sulphations at C-4/C-6 of GalNAc and C-2 of IdoA provide for a further level of complexity. However, the most complex GAGs are undoubtedly the glucosaminoglycans HS and heparin, which experience postpolymeric modifications of both the monosaccharide constituents of the original disaccharide repeat (for review see ref.1). G1cA residues can be epimerized to IdoA, whilst GlcNAc residues can be simultaneously de-N-acetylated/re-N-sulphated yielding N-sulphoglucosamine (GlcNSO3). Both these conversions occur to a greater extent in heparin than in HS.

Keywords

Heparan Sulphate Chondroitin Sulphate Dermatan Sulphate Keratan Sulphate Hydrazine Sulphate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Birkhäuser Verlag Basel 1997

Authors and Affiliations

  • Malcolm Lyon

There are no affiliations available

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