GlycoMapsDB: a database of the accessible conformational space of glycosidic linkages

Conformational energy maps of the glycosidic linkages are a valuable resource to gain information about preferred conformations and flexibility of carbohydrates. Here we present GlycoMapsDB, a new database containing more than 2500 calculated conformational maps for a variety of di- to pentasaccharide fragments contained in N- and O-glycans. Oligosaccharides representing branchpoints of N-glycans are included in the set of fragments, thus the influence of neighbouring residues is reflected in the conformational maps. During refinement of new crystal structures, maps contained in GlycoMapsDB can serve as a valuable resource to check whether the torsion values of a glycosidic linkage are located in an ‘allowed’ region similar to the Ramachandran plot analysis for proteins. This might help to improve the structural quality of the glycan data contained in the Protein Data Bank (PDB). A link between GlycoMapsDB and the PDB has been established so that the glycosidic torsions of all glycans contained in the PDB can be retrieved and compared to calculated data. The service is available at

Plasticity of the β-Trefoil Protein Fold in the Recognition and Control of Invertebrate Predators and Parasites by a Fungal Defence System

Discrimination between self and non-self is a prerequisite for any defence mechanism; in innate defence, this discrimination is often mediated by lectins recognizing non-self carbohydrate structures and so relies on an arsenal of host lectins with different specificities towards target organism carbohydrate structures. Recently, cytoplasmic lectins isolated from fungal fruiting bodies have been shown to play a role in the defence of multicellular fungi against predators and parasites. Here, we present a novel fruiting body lectin, CCL2, from the ink cap mushroom Coprinopsis cinerea. We demonstrate the toxicity of the lectin towards Caenorhabditis elegans and Drosophila melanogaster and present its NMR solution structure in complex with the trisaccharide, GlcNAcβ1,4[Fucα1,3]GlcNAc, to which it binds with high specificity and affinity in vitro. The structure reveals that the monomeric CCL2 adopts a β-trefoil fold and recognizes the trisaccharide by a single, topologically novel carbohydrate-binding site. Site-directed mutagenesis of CCL2 and identification of C. elegans mutants resistant to this lectin show that its nematotoxicity is mediated by binding to α1,3-fucosylated N-glycan core structures of nematode glycoproteins; feeding with fluorescently labeled CCL2 demonstrates that these target glycoproteins localize to the C. elegans intestine. Since the identified glycoepitope is characteristic for invertebrates but absent from fungi, our data show that the defence function of fruiting body lectins is based on the specific recognition of non-self carbohydrate structures. The trisaccharide specifically recognized by CCL2 is a key carbohydrate determinant of pollen and insect venom allergens implying this particular glycoepitope is targeted by both fungal defence and mammalian immune systems. In summary, our results demonstrate how the plasticity of a common protein fold can contribute to the recognition and control of antagonists by an innate defence mechanism, whereby the monovalency of the lectin for its ligand implies a novel mechanism of lectin-mediated toxicity

Homology modelling and spectroscopy, a never-ending love story

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research