Sharing of worldwide distributed carbohydrate-related digital resources: online connection of the Bacterial Carbohydrate Structure DataBase and GLYCOSCIENCES.de

Functional glycomics, the scientific attempt to identify and assign functions to all glycan molecules synthesized by an organism, is an emerging field of science. In recent years, several databases have been started, all aiming to support deciphering the biological function of carbohydrates. However, diverse encoding and storage schemes are in use amongst these databases, significantly hampering the interchange of data. The mutual online access between the Bacterial Carbohydrate Structure DataBase (BCSDB) and the GLYCOSCIENCES.de portal, as a first reported attempt of a structure-based direct interconnection of two glyco-related databases is described. In this approach, users have to learn only one interface, will always have access to the latest data of both services, and will have the results of both searches presented in a consistent way. The establishment of this connection helped to find shortcomings and inconsistencies in the database design and functionality related to underlying data concepts and structural representations. For the maintenance of the databases, duplication of work can be easily avoided, and will hopefully lead to a better worldwide acceptance of both services within the community of glycoscienists. BCSDB is available at and the GLYCOSCIENCES.de portal a

Statistical analysis of the Bacterial Carbohydrate Structure Data Base (BCSDB): Characteristics and diversity of bacterial carbohydrates in comparison with mammalian glycans

<p>Abstract</p> <p>Background</p> <p>There are considerable differences between bacterial and mammalian glycans. In contrast to most eukaryotic carbohydrates, bacterial glycans are often composed of repeating units with diverse functions ranging from structural reinforcement to adhesion, colonization and camouflage. Since bacterial glycans are typically displayed at the cell surface, they can interact with the environment and, therefore, have significant biomedical importance.</p> <p>Results</p> <p>The sequence characteristics of glycans (monosaccharide composition, modifications, and linkage patterns) for the higher bacterial taxonomic classes have been examined and compared with the data for mammals, with both similarities and unique features becoming evident. Compared to mammalian glycans, the bacterial glycans deposited in the current databases have a more than ten-fold greater diversity at the monosaccharide level, and the disaccharide pattern space is approximately nine times larger. Specific bacterial subclasses exhibit characteristic glycans which can be distinguished on the basis of distinctive structural features or sequence properties.</p> <p>Conclusion</p> <p>For the first time a systematic database analysis of the bacterial glycome has been performed. This study summarizes the current knowledge of bacterial glycan architecture and diversity and reveals putative targets for the rational design and development of therapeutic intervention strategies by comparing bacterial and mammalian glycans.</p

Symbol Nomenclature for Graphical Representations of Glycans

ISSN:0959-665

BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed

Simulation of 2D NMR Spectra of Carbohydrates Using GODESS Software

Glycan Optimized Dual Empirical Spectrum Simulation (GODESS) is a web service, which has been recently shown to be one of the most accurate tools for simulation of ¹H and ¹³C 1D NMR spectra of natural carbohydrates and their derivatives. The new version of GODESS supports visualization of the simulated ¹H and ¹³C chemical shifts in the form of most 2D spin correlation spectra commonly used in carbohydrate research, such as ¹H–¹H TOCSY, COSY/COSY-DQF/COSY-RCT, and ¹H–¹³C edHSQC, HSQC–COSY, HSQC–TOCSY, and HMBC. Peaks in the simulated 2D spectra are color-coded and labeled according to the signal assignment and can be exported in JCAMP-DX format. Peak widths are estimated empirically from the structural features. GODESS is available free of charge via the Internet at the platform of the Carbohydrate Structure Database project (http://csdb.glycoscience.ru)

Improved Carbohydrate Structure Generalization Scheme for ¹H and ¹³C NMR Simulations

The improved Carbohydrate Structure Generalization Scheme has been developed for the simulation of ¹³C and ¹H NMR spectra of oligo- and polysaccharides and their derivatives, including those containing noncarbohydrate constituents found in natural glycans. Besides adding the ¹H NMR calculations, we improved the accuracy and performance of prediction and optimized the mathematical model of the precision estimation. This new approach outperformed other methods of chemical shift simulation, including database-driven, neural net-based, and purely empirical methods and quantum-mechanical calculations at high theory levels. It can process structures with rarely occurring and noncarbohydrate constituents unsupported by the other methods. The algorithm is transparent to users and allows tracking used reference NMR data to original publications. It was implemented in the Glycan-Optimized Dual Empirical Spectrum Simulation (GODESS) web service, which is freely available at the platform of the Carbohydrate Structure Database (CSDB) project (http://csdb.glycoscience.ru)

Carbohydrate Structure Generalization Scheme for Database-Driven Simulation of Experimental Observables, Such as NMR Chemical Shifts

Carbohydrates play an immense role in different aspects of life. NMR spectroscopy is the most powerful tool for investigation of these compounds. Nowadays, progress in computational procedures has opened up novel opportunities giving an impulse to the development of new instruments intended to make the research simpler and more efficient. In this paper, we present a new approach for simulating ¹³C NMR chemical shifts of carbohydrates. The approach is suitable for any atomic observables, which could be stored in a database. The method is based on sequential generalization of the chemical surroundings of the atom under prediction and heuristic averaging of database data. Unlike existing applications, the generalization scheme is tuned for carbohydrates, including those containing phosphates, amino acids, alditols, and other non-carbohydrate constituents. It was implemented in the Glycan-Optimized Dual Empirical Spectrum Simulation (GODESS) software, which is freely available on the Internet. In the field of carbohydrates, our approach was shown to outperform all other existing methods of NMR spectrum prediction (including quantum-mechanical calculations) in accuracy. Only this approach supports NMR spectrum simulation for a number of structural features in polymeric structures