The UniCarb KnowledgeBase (UniCarbKB; http://unicarbkb.org) offers public access to a growing, curated database of information on the glycan structures of glycoproteins. UniCarbKB is an international effort that aims to further our understanding of structures, pathways and networks involved in glycosylation and glyco-mediated processes by integrating structural, experimental and functional glycoscience information. This initiative builds upon the success of the glycan structure database GlycoSuiteDB, together with the informatic standards introduced by EUROCarbDB, to provide a high-quality and updated resource to support glycomics and glycoproteomics research. UniCarbKB provides comprehensive information concerning glycan structures, and published glycoprotein information including global and site-specific attachment information. For the first release over 890 references, 3740 glycan structure entries and 400 glycoproteins have been curated. Further, 598 protein glycosylation sites have been annotated with experimentally confirmed glycan structures from the literature. Among these are 35 glycoproteins, 502 structures and 60 publications previously not included in GlycoSuiteDB. This article provides an update on the transformation of GlycoSuiteDB (featured in previous NAR Database issues and hosted by ExPASy since 2009) to UniCarbKB and its integration with UniProtKB and GlycoMod. Here, we introduce a refactored database, supported by substantial new curated data collections and intuitive user-interfaces that improve database searching.

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UniCarbKB: building a knowledge platform for glycoproteomics.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a popular chemical information resource that serves a wide range of use cases. In the past two years, a number of changes were made to PubChem. Data from more than 120 data sources was added to PubChem. Some major highlights include: the integration of Google Patents data into PubChem, which greatly expanded the coverage of the PubChem Patent data collection; the creation of the Cell Line and Taxonomy data collections, which provide quick and easy access to chemical information for a given cell line and taxon, respectively; and the update of the bioassay data model. In addition, new functionalities were added to the PubChem programmatic access protocols, PUG-REST and PUG-View, including support for target-centric data download for a given protein, gene, pathway, cell line, and taxon and the addition of the 'standardize' option to PUG-REST, which returns the standardized form of an input chemical structure. A significant update was also made to PubChemRDF. The present paper provides an overview of these changes.

https://academic.oup.com/nar/article-pdf/51/D1/D1373/48441598/gkac956.pdf

PubChem 2023 update.

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. 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. Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. 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.

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Toolboxes for a standardised and systematic study of glycans

This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics—for example in Genome Wide Association Studies—to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

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High-Throughput Analysis and Automation for Glycomics Studies

Glycan or carbohydrate structures can be pictorially represented using symbolic nomenclatures. The symbol nomenclature for glycans (SNFG) contains 67 different monosaccharides represented using various colors and geometric shapes. A simple tool to convert International Union of Pure and Applied Chemistry (IUPAC) format text to SNFG will be useful for sketching glycans and glycopeptides. Such code can also enable the development of more sophisticated applications, where the visual representation of carbohydrate structures is necessary. To address this need, the current manuscript describes DrawGlycan-SNFG, a freely available, platform-independent, open-source tool. It allows: i. the display of glycans and glycopeptides from IUPAC-condensed text inputs and ii. the depiction of glycan and glycopeptide fragments. The online version of this program is provided with a user-friendly web interface at www.virtualglycome.org/DrawGlycan. Downloadable, stand-alone GUI (Graphical User Interface) version and the program source code are also available from this repository. DrawGlycan-SNFG will be useful for experimentalists looking for a ready to use, simple program for sketching carbohydrates and for software developers interested in incorporating SNFG into their program suite.

/pdf/drawglycan-snfg-a-robust-tool-to-render-glycans-and-5e70c7tzq3.pdf

DrawGlycan-SNFG: a robust tool to render glycans and glycopeptides with fragmentation information.

To the Editor — We present the GlyCosmos Glycoscience Portal (https://glycosmos.org), an integrated web resource for accessing glycoscience data derived from a variety of disparate web resources. The field of glycoscience deals with the study of carbohydrate structures and their functions in biology, energy, agriculture and medicine1. These structures, often called glycans, are attached to proteins and lipids, and modulate their functions in various biological processes, including metabolism, signaling and diseases. Alterations in glycans and glycoconjugates can convey disease-diagnostic information; these molecules are thus of increasing importance as drug targets and in biopharmaceutical drug development. In agriculture and energy, carbohydrates such as cellulose are the focus of novel biofuels. The history of glycan databases began in the mid-late 1990’s with CarbBank in the United States, followed by Glycosciences. de in Germany. In the early 2000s, the Consortium for Functional Glycomics (CFG) project began concurrently with the KEGG (Kyoto Encyclopedia of Genes and Genomes) GLYCAN database. In Europe, the EuroCarbDB project produced the MonosaccharideDB and GlycomeDB databases, while the JCGGDB database was developed to integrate glycan-related databases in Japan1. As a result of these activities in different parts of the world, glycobiologists and researchers have many resources technically available to them, but these are often hard to find. Therefore, we have developed the GlyCosmos Glycoscience Portal, where all such resources can be accessed from a single website. A user-friendly web interface allows non-specialists to browse the available information, including glycan-related genes, proteins, lipids, glycomes, pathways and diseases. Note that we use “database” for a single, structured set of data named as a database, whereas a “dataset” may be a collection of data of the same data type present across various databases. The term “repository” refers to a specialized database where users can add data, in turn receiving an accession code, whereas a “database” is closed such that only the developer can add or modify data. GlyCosmos provides a section for repositories, and a section for data resources, which includes the various glycan-related databases and integrated datasets.

The GlyCosmos Portal: a unified and comprehensive web resource for the glycosciences.

In the bioinformatics field, many computer algorithmic and data mining technologies have been developed for gene prediction, protein–protein interaction analysis, sequence analysis, and protein folding predictions, to name a few. This kind of research has branched off from the genomics field, creating the transcriptomics, proteomics, metabolomics, and glycomics research areas in the postgenomic age. In the glycomics field, given the complexity of glycan structures with their branches of monosaccharides in various conformations, new data mining and algorithmic methods have been developed in an attempt to gain a better understanding of glycans. However, these methods have not all been implemented as tools such that the glycobiology community may utilize them in their research. Thus, we have developed RINGS (Resource for INformatics of Glycomes at Soka) as a freely available Web resource for glycobiologists to analyze their data using the latest data mining and algorithmic techniques. It provides a ...

The RINGS resource for glycome informatics analysis and data mining on the Web.

MCAW-DB: A glycan profile database capturing the ambiguity of glycan recognition patterns.

Motivation: A glycan consists of monosaccharides linked by glycosidic bonds, has branches and forms complex molecular structures. Databases have been developed to store large amounts of glycan-binding experiments, including glycan arrays with glycan-binding proteins. However, there are few bioinformatics techniques to analyze large amounts of data for glycans because there are few tools that can handle the complexity of glycan structures. Thus, we have developed the MCAW (Multiple Carbohydrate Alignment with Weights) tool that can align multiple glycan structures, to aid in the understanding of their function as binding recognition molecules. Results: We have described in detail the first algorithm to perform multiple glycan alignments by modeling glycans as trees. To test our tool, we prepared several data sets, and as a result, we found that the glycan motif could be successfully aligned without any prior knowledge applied to the tool, and the known recognition binding sites of glycans could be aligned at a high rate amongst all our datasets tested. We thus claim that our tool is able to find meaningful glycan recognition and binding patterns using data obtained by glycan-binding experiments. The development and availability of an effective multiple glycan alignment tool opens possibilities for many other glycoinformatics analysis, making this work a big step towards furthering glycomics analysis. Availability and Implementation: http://www.rings.t.soka.ac.jp Contact: kkiyoko@soka.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

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Development and application of an algorithm to compute weighted multiple glycan alignments.

The purpose of our research is the elucidation of glycan recognition patterns. Glycans are composed of monosaccharides and have complex structures with branches due to the fact that monosaccharides have multiple potential binding positions compared to amino acids. Each monosaccharide can potentially be bound by up to five other monosaccharides, compared to two for any amino acid. Glycans are often bound to proteins and lipids on the cell surface and play important roles in biological processes. Lectins in particular are proteins that recognize and bind to glycans. In general, lectins bind to the terminal monosaccharides of glycans on glycoconjugates. However, it is suggested that some lectins recognize not only terminal monosaccharides, but also internal monosaccharides, possibly influencing the binding affinity. Such analyses are difficult without novel bioinformatics techniques. Thus, in order to better understand the glycan recognition mechanism of such biomolecules, we have implemented a novel algorithm for aligning glycan tree structures, which we provide as a web tool called MCAW (Multiple Carbohydrate Alignment with Weights). From our web tool, we have analyzed several different lectins, and our results could confirm the existence of well-known glycan motifs. Our work can now be used in several other analyses of glycan structures, such as in the development of glycan score matrices as well as in state model determination of probabilistic tree models. Therefore, this work is a fundamental step in glycan pattern analysis to progress glycobiology research.

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Masae Hosoda

Papers

The GlyCosmos Portal: a unified and comprehensive web resource for the glycosciences.

The RINGS resource for glycome informatics analysis and data mining on the Web.

MCAW-DB: A glycan profile database capturing the ambiguity of glycan recognition patterns.

Development and application of an algorithm to compute weighted multiple glycan alignments.

Multiple tree alignment with weights applied to carbohydrates to extract binding recognition patterns