Glycosciences.DB: an annotated data collection linking glycomics and proteomics data (2018 update).

Glycosciences.DB, the glycan structure database of the Glycosciences.de portal, collects various kinds of data on glycan structures, including carbohydrate moieties from worldwide Protein Data Bank (wwPDB) structures. This way it forms a bridge between glycomics and proteomics resources. A major update of this database combines a redesigned web interface with a series of new functions. These include separate entry pages not only for glycan structures but also for literature references and wwPDB entries, improved substructure search options, a newly available keyword search covering all types of entries in one query, and new types of information that is added to glycan structures. These new features are described in detail in this article, and options how users can provide information to the database are discussed as well. Glycosciences.DB is available at http://www.glycosciences.de/database/ and can be freely accessed.

Using NMR data on GLYCOSCIENCES.de.

NMR spectroscopy is frequently used in structural characterization of carbohydrates. The GLYCOSCIENCES.de database contains more than 3,000 NMR spectra stored as lists of chemical shifts, which can be searched online by atom and residue names and by chemical shift values. This chapter describes how to use the different interfaces to get access to these data. The atom search allows querying the database for NMR spectra that contain a specific carbohydrate residue with an NMR shift in a given range assigned to a particular atom, whereas the peak search enables queries to find spectra with NMR shifts most similar to a list of given shifts. The shift estimation feature facilitates prediction of NMR shifts of glycans, for which no experimental data are available.

GlyNest and CASPER: two independent approaches to estimate 1H and 13C NMR shifts of glycans available through a common web-interface.

GlyNest and CASPER (www.casper.organ.su.se/casper/) are two independent services aiming to predict (1)H- and (13)C-NMR chemical shifts of glycans. GlyNest estimates chemical shifts of glycans based on a spherical environment encoding scheme for each atom. CASPER is an increment rule-based approach which uses chemical shifts of the free reducing monosaccharides which are altered according to attached residues of an oligo- or polysaccharide sequence. Both services, which are located on separate, distributed, servers are now available through a common interface of the GLYCOSCIENCES.de portal (www.glycosciences.de). The predictive ability of both techniques was evaluated for a test set of 155 (13)C and 181 (1)H spectra of assigned glycan structures. The standard deviations between experimental and estimated shifts ((1)H; 0.081/0.102; (13)C 0.763/0.794; GlyNest/CASPER) are comparable for both methods and significantly better than procedures where stereochemistry is not encoded. The predictive ability of both approaches is in most cases sufficiently precise to be used for an automatic assignment of NMR-spectra. Since both procedures work efficiently and require computation times in the millisecond range on standard computers, they are well suited for the assignment of NMR spectra in high-throughput glycomics projects. The service is available at www.glycosciences.de/sweetdb/start.php?action=form_shift_estimation.

GLYCOSCIENCES.de: an Internet portal to support glycomics and glycobiology research.

The development of glycan-related databases and bioinformatics applications is considerably lagging behind compared with the wealth of available data and software tools in genomics and proteomics. Because the encoding of glycan structures is more complex, most of the bioinformatics approaches cannot be applied to glycan structures. No standard procedures exist where glycan structures found in various species, organs, tissues or cells can be routinely deposited. In this article the concepts of the GLYCOSCIENCES.de portal are described. It is demonstrated how an efficient structure-based cross-linking of various glycan-related data originating from different resources can be accomplished using a single user interface. The structure oriented retrieval options-exact structure, substructure, motif, composition and sugar components-are discussed. The types of available data-references, composition, spatial structures, nuclear magnetic resonance (NMR) shifts (experimental and estimated), theoretically calculated fragments and Protein Database (PDB) entries-are exemplified for Man(3.) The free availability and unrestricted use of glycan-related data is an absolute prerequisite to efficiently share distributed resources. Additionally, there is an urgent need to agree to a generally accepted exchange format as well as to a common software interface. An open access repository for glyco-related experimental data will secure that the loss of primary data will be considerably reduced.

SWEET-DB: an attempt to create annotated data collections for carbohydrates.

Complex carbohydrates are known as mediators of complex cellular events. Concerning their structural diversity, their potential of information content is several orders of magnitude higher in a short sequence than any other biological macromolecule. SWEET-DB (http://www.dkfz.de/spec2/sweetdb/) is an attempt to use modern web techniques to annotate and/or cross-reference carbohydrate-related data collections which allow glycoscientists to find important data for compounds of interest in a compact and well-structured representation. Currently, reference data taken from three data sources can be retrieved for a given carbohydrate (sub)structure. The sources are CarbBank structures and literature references (linked to NCBI PubMed service), NMR data taken from SugaBase and 3D co-ordinates generated with SWEET-II. The main purpose of SWEET-DB is to enable an easy access to all data stored for one carbohydrate structure entering a complete sequence or parts thereof. Access to SWEET-DB contents is provided with the help of separate input spreadsheets for (sub)structures, bibliographic data, general structural data like molecular weight, NMR spectra and biological data. A detailed online tutorial is available at http://www.dkfz.de/spec2/sweetdb/nar/.