Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.

MOTIVATION: Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information. RESULTS: An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases. AVAILABILITY AND IMPLEMENTATION: The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/).

BACKGROUND: Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists. METHODS: Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the "objective" difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software. RESULTS: Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. CONCLUSIONS: Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics.

SUMMARY: The open access comprehensive GlycoCD database application is for representation and retrieval of carbohydrate-related clusters of differentiation (CDs). The main objective of this database platform is to provide information about interactions of carbohydrate moieties with proteins that are important for identification of specific cell surface molecule with a focus on the integration of data from carbohydrate microarray databases. GlycoCD database comprises two sections: the carbohydrate recognition CD and glycan CD. It allows easy access through a user-friendly web interface to all carbohydrate-defined CDs and those that interact with carbohydrates along with other relevant information. AVAILABILITY: The database is freely available at http://glycosciences.de/glycocd/index.php CONTACT: [email protected].

BACKGROUND: Carbohydrates are involved in a variety of fundamental biological processes and pathological situations. They therefore have a large pharmaceutical and diagnostic potential. Knowledge of the 3D structure of glycans is a prerequisite for a complete understanding of their biological functions. The largest source of biomolecular 3D structures is the Protein Data Bank. However, about 30% of all 1663 PDB entries (version September 2003) containing carbohydrates comprise errors in glycan description. Unfortunately, no software is currently available which aligns the 3D information with the reported assignments. It is the aim of this work to fill this gap. RESULTS: The pdb-care program http://www.glycosciences.de/tools/pdb-care/ is able to identify and assign carbohydrate structures using only atom types and their 3D atom coordinates given in PDB-files. Looking up a translation table where systematic names and the respective PDB residue codes are listed, both assignments are compared and inconsistencies are reported. Additionally, the reliability of reported and calculated connectivities for molecules listed within the HETATOM records is checked and unusual values are reported. CONCLUSION: Frequent use of pdb-care will help to improve the quality of carbohydrate data contained in the PDB. Automatic assignment of carbohydrate structures contained in PDB entries will enable the cross-linking of glycobiology resources with genomic and proteomic data collections.

SUMMARY: Lipoxygenases are a family of enzymes involved in a variety of human diseases like inflammation, asthma, artherosclerosis and cancer. The lipoxygenases database (LOX-DB) aims to be a web accessible compendium of information in particular on the mammalian members of this multigene family. This resource includes molecular structures, reference data, tools for structural and computational analysis as well as links to related information maintained by others. The data can be retrieved by the use of various search options and analyzed applying publicly available visualization tools. AVAILABILITY: LOX-DB is available at http://www.dkfz-heidelberg.de/spec/lox-db/