Symbol Nomenclature Research Articles

Glycoscience data content in the NCBI Glycans and PubChem.

Studying glycans and their functions in the body aids in the understanding of disease mechanisms and developing new treatments. This necessitates resources that provide comprehensive glycan data integrated with relevant information from other scientific fields such as genomics, genetics, proteomics, metabolomics, and chemistry. The present paper describes two resources at the U.S. National Center for Biotechnology Information (NCBI), the NCBI Glycans and PubChem, which provide glycan-related information useful for the glycoscience research community. The NCBI Glycans ( https://www.ncbi.nlm.nih.gov/glycans/ ) is a dedicated website for glycobiology data content at NCBI and provides quick access to glycan-related information scattered across multiple NCBI databases as well as other information resources external to NCBI. Importantly, the NCBI Glycans hosts the official web page for the symbol nomenclature for glycans (SNFG), which is the standard graphical representation of glycan structures recommended for scientific publication. On the other hand, PubChem ( https://pubchem.ncbi.nlm.nih.gov ) is a research-focused, large-scale public chemical database, containing a substantial number of glycan-containing records and is integrated with important glycoscience resources like GlyTouCan, GlyCosmos, and GlyGen. PubChem organizes glycan-related information within multiple data collections (i.e., Substance, Compound, Protein, Gene, Pathway, and Taxonomy) and provides various tools and services that allow users to access them both interactively through a web browser and programmatically through a REST-ful interface, including PUG-View. The NCBI Glycans and PubChem highlight glycan-related data and improve their accessibility, helping scientists exploit these data in their research.

GlycoDraw: a python implementation for generating high-quality glycan figures.

Glycans are essential to all scales of biology, with their intricate structures being crucial for their biological functions. The structural complexity of glycans is communicated through simplified and unified visual representations according to the Symbol Nomenclature for Glycans (SNFGs) guidelines adopted by the community. Here, we introduce GlycoDraw, a Python-native implementation for high-throughput generation of high-quality, SNFG-compliant glycan figures with flexible display options. GlycoDraw is released as part of our glycan analysis ecosystem, glycowork, facilitating integration into existing workflows by enabling fully automated annotation of glycan-related figures and thus assisting the analysis of e.g. differential abundance data or glycomics mass spectra.

GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES

Glycans are important polysaccharides on cellular surfaces that are bound to glycoproteins and glycolipids. These are one of the most common post-translational modifications of proteins in eukaryotic cells. They play important roles in protein folding, cell-cell interactions, and other extracellular processes. Changes in glycan structures may influence the course of different diseases, such as infections or cancer. Glycans are commonly represented using the IUPAC-condensed notation. IUPAC-condensed is a textual representation of glycans operating on the same topological level as the Symbol Nomenclature for Glycans (SNFG) that assigns colored, geometrical shapes to the main monomers. These symbols are then connected in tree-like structures, visualizing the glycan structure on a topological level. Yet for a representation on the atomic level, notations such as SMILES should be used. To our knowledge, there is no easy-to-use, general, open-source, and offline tool to convert the IUPAC-condensed notation to SMILES. Here, we present the open-access Python package GlyLES for the generalizable generation of SMILES representations out of IUPAC-condensed representations. GlyLES uses a grammar to read in the monomer tree from the IUPAC-condensed notation. From this tree, the tool can compute the atomic structures of each monomer based on their IUPAC-condensed descriptions. In the last step, it merges all monomers into the atomic structure of a glycan in the SMILES notation. GlyLES is the first package that allows conversion from the IUPAC-condensed notation of glycans to SMILES strings. This may have multiple applications, including straightforward visualization, substructure search, molecular modeling and docking, and a new featurization strategy for machine-learning algorithms. GlyLES is available at https://github.com/kalininalab/GlyLES.

Cataloging natural sialic acids and other nonulosonic acids (NulOs), and their representation using the Symbol Nomenclature for Glycans.

Nonulosonic acids or non-2-ulosonic acids (NulOs) are an ancient family of 2-ketoaldonic acids (α-ketoaldonic acids) with a 9-carbon backbone. In nature, these monosaccharides occur either in a 3-deoxy form (referred to as "sialic acids") or in a 3,9-dideoxy "sialic-acid-like" form. The former sialic acids are most common in the deuterostome lineage, including vertebrates, and mimicked by some of their pathogens. The latter sialic-acid-like molecules are found in bacteria and archaea. NulOs are often prominently positioned at the outermost tips of cell surface glycans, and have many key roles in evolution, biology and disease. The diversity of stereochemistry and structural modifications among the NulOs contributes to more than 90 sialic acid forms and 50 sialic-acid-like variants described thus far in nature. This paper reports the curation of these diverse naturally occurring NulOs at the NCBI sialic acid page (https://www.ncbi.nlm.nih.gov/glycans/sialic.html) as part of the NCBI-Glycans initiative. This includes external links to relevant Carbohydrate Structure Databases. As the amino and hydroxyl groups of these monosaccharides are extensively derivatized by various substituents in nature, the Symbol Nomenclature For Glycans (SNFG) rules have been expanded to represent this natural diversity. These developments help illustrate the natural diversity of sialic acids and related NulOs, and enable their systematic representation in publications and online resources.

Representation of polysaccharide molecules by SNFG and 3D-SNFG methods——Take Potentilla anserina L polysaccharide molecule as an example

With the continuous deepening of international research in the field of biology, more and more studies have found that polysaccharides have multiple biological functions, so that polysaccharides have gradually become the research objects of more and more scientists in the world, and a large number of relevant researchers have carried out Glycobiology research, most of the current research is on the separation, extraction, structural characterization and activity experiments of polysaccharides. However, at this stage, research on the structure-activity relationship of various polysaccharides extracted from plants is relatively rare, and the representation method of polysaccharide structures is not perfect, not unified, complicated in drawing, and not beautiful and convenient to read. The SNFG (Symbol Nomenclature For Glycans) method, which is the symbolic nomenclature of polysaccharides and the 3D-SNFG method, can solve the above problems well, and can use unified rules to describe and describe the molecular structure of polysaccharides, and the painting process is more convenient and more convenient. It is beautiful and makes it easier for readers to read. In this paper, the fern hemp polysaccharide molecule is taken as an example. After drawing it with chemoffice, SNFG and 3D-SNFG are used to describe it, and then compared. It is clear at a glance that the use of SNFG and 3D-SNFG methods has been widely recognized and accepted internationally, which can provide great convenience for sugar-related research and information exchange.

SugarDrawer: A Web-Based Database Search Tool with Editing Glycan Structures.

In life science fields, database integration is progressing and contributing to collaboration between different research fields, including the glycosciences. The integration of glycan databases has greatly progressed collaboration worldwide with the development of the international glycan structure repository, GlyTouCan. This trend has increased the need for a tool by which researchers in various fields can easily search glycan structures from integrated databases. We have developed a web-based glycan structure search tool, SugarDrawer, which supports the depiction of glycans including ambiguity, such as glycan fragments which contain underdetermined linkages, and a database search for glycans drawn on the canvas. This tool provides an easy editing feature for various glycan structures in just a few steps using template structures and pop-up windows which allow users to select specific information for each structure element. This tool has a unique feature for selecting possible attachment sites, which is defined in the Symbol Nomenclature for Glycans (SNFG). In addition, this tool can input and output glycans in WURCS and GlycoCT formats, which are the most commonly-used text formats for glycan structures.

CSDB/SNFG Structure Editor: An Online Glycan Builder with 2D and 3D Structure Visualization.

This article describes features, usage, and application of an CSDB/SNFG Structure Editor, a new online tool for quick and intuitive input of carbohydrate and derivative structures using Symbol Nomenclature for Glycans (SNFG). The Editor is built on a platform of the Carbohydrate Structure Database (CSDB) and relies on its online services via the dedicated web-API. The Editor allows building of oligo- and polymeric glycan structures and supports most features of natural glycans, such as underdetermined structures, alternative branches, repeating subunits, SMILES specification of atypical monomers, and others. The vocabulary of building blocks contains 600+ monomeric residues, including 327 monosaccharides. Support for SMILES allows input and visualization of chemical structures of virtually unlimited complexity. On the other hand, the interface follows the recognized GlycanBuilder style easy to novice users. The export feature includes support for CSDB Linear, GlycoCT, WURCS, SweetDB, and Glycam notations, SMILES codes, MOL/PDB atomic coordinate formats, raster and vector SNFG images, and on-the-fly visualization as 2D structural formulas and 3D molecular models. Integration of the Editor into any web-based glycoinformatics project is straightforward and simple, similarly to any other modern JavaScript application.

Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency

Massively parallel sequencing has markedly improved mendelian diagnostic rates. This study assessed the effects of custom alterations to a diagnostic genomic bioinformatic pipeline in response to clinical need and derived practice recommendations relative to diagnostic rates and efficiency. The Genomic Annotation and Interpretation Application (GAIA) bioinformatics pipeline was designed to detect panel, exome, and genome sample integrity and prioritize gene variants in mendelian disorders. Reanalysis of selected negative cases was performed after improvements to the pipeline. GAIA improvements and their effect on sensitivity are described, including addition of a PubMed search for gene-disease associations not in the Online Mendelian Inheritance of Man database, inclusion of a process for calling low-quality variants (known as QPatch), and gene symbol nomenclature consistency checking. The new pipeline increased the diagnostic rate and reduced staff costs, resulting in a saving of US$844.34 per additional diagnosis. Recommendations for genomic analysis pipeline requirements are summarized. Clinically responsive bioinformatics pipeline improvements increase diagnostic sensitivity and increase cost-effectiveness.

Enhanced validation of small-molecule ligands and carbohydrates in the Protein Data Bank

The Worldwide Protein Data Bank (wwPDB) has provided validation reports based on recommendations from community Validation Task Forces for structures in the PDB since 2013. To further enhance validation of small molecules as recommended from the 2016 Ligand Validation Workshop, wwPDB, Global Phasing Ltd., and the Noguchi Institute, recently formed a public/private partnership to incorporate some of their software tools into the wwPDB validation package. Augmented wwPDB validation report features include: two-dimensional (2D) diagrams of small-molecule ligands and carbohydrates, highlighting geometric validation outcomes; 2D topological diagrams of oligosaccharides present in branched entities generated using 2D Symbol Nomenclature for Glycan representation; and views of 3D electron density maps for ligands and carbohydrates, illustrating the goodness-of-fit between the atomic structure and experimental data (X-ray crystallographic structures only). These improvements will impact confidence in ligand conformation and ligand-macromolecular interactions that will aid in understanding biochemical function and contribute to small-molecule drug discovery.

DrawGlycan-SNFG & gpAnnotate: Rendering glycans and annotating glycopeptide mass spectra.

This manuscript describes an open-source program, DrawGlycan-SNFG (version 2), that accepts IUPAC (International Union of Pure & Applied Chemist)-condensed inputs to render Symbol Nomenclature For Glycans (SNFG) drawings. A wide range of local and global options enable display of various glycan/peptide modifications including bond breakages, adducts, repeat structures, ambiguous identifications, etc. These facilities make DrawGlycan-SNFG ideal for integration into various glycoinformatics software, including glycomics and glycoproteomics mass spectrometry applications. As a demonstration of such usage, we incorporated DrawGlycan-SNFG into gpAnnotate, a standalone application to score and annotate individual MS/MS glycopeptide spectrum in different fragmentation modes. DrawGlycan-SNFG and gpAnnotate are platform independent. While originally coded using MATLAB, compiled packages are also provided to enable DrawGlycan-SNFG implementation in Python and Java. All programs are available from https://virtualglycome.org/drawglycan; https://virtualglycome.org/gpAnnotate. Supplementary Material are available at Bioinformatics online.

Updates to the Symbol Nomenclature for Glycans guidelines

The Symbol Nomenclature for Glycans (SNFG) is a community-curated standard for the depiction of monosaccharides and complex glycans using various colored-coded, geometric shapes, along with defined text additions. It is hosted by the National Center for Biotechnology Information (NCBI) at the NCBI-Glycans Page (www.ncbi.nlm.nih.gov/glycans/snfg.html). Several changes have been made to the SNFG page in the past year to update the rules for depicting glycans using the SNFG, to include more examples of use, particularly for non-mammalian organisms, and to provide guidelines for the depiction of ambiguous glycan structures. This Glycoforum article summarizes these recent changes.

SugarSketcher: Quick and Intuitive Online Glycan Drawing.

SugarSketcher is an intuitive and fast JavaScript interface module for online drawing of glycan structures in the popular Symbol Nomenclature for Glycans (SNFG) notation and exporting them to various commonly used formats encoding carbohydrate sequences (e.g., GlycoCT) or quality images (e.g., svg). It does not require a backend server or any specific browser plugins and can be integrated in any web glycoinformatics project. SugarSketcher allows drawing glycans both for glycobiologists and non-expert users. The “quick mode” allows a newcomer to build up a glycan structure having only a limited knowledge in carbohydrate chemistry. The “normal mode” integrates advanced options which enable glycobiologists to tailor complex carbohydrate structures. The source code is freely available on GitHub and glycoinformaticians are encouraged to participate in the development process while users are invited to test a prototype available on the ExPASY web-site and send feedback.

MatrixDB: integration of new data with a focus on glycosaminoglycan interactions.

MatrixDB (http://matrixdb.univ-lyon1.fr/) is an interaction database focused on biomolecular interactions established by extracellular matrix (ECM) proteins and glycosaminoglycans (GAGs). It is an active member of the International Molecular Exchange (IMEx) consortium (https://www.imexconsortium.org/). It has adopted the HUPO Proteomics Standards Initiative standards for annotating and exchanging interaction data, either at the MIMIx (The Minimum Information about a Molecular Interaction eXperiment) or IMEx level. The following items related to GAGs have been added in the updated version of MatrixDB: (i) cross-references of GAG sequences to the GlyTouCan database, (ii) representation of GAG sequences in different formats (IUPAC and GlycoCT) and as SNFG (Symbol Nomenclature For Glycans) images and (iii) the GAG Builder online tool to build 3D models of GAG sequences from GlycoCT codes. The database schema has been improved to represent n-ary experiments. Gene expression data, imported from Expression Atlas (https://www.ebi.ac.uk/gxa/home), quantitative ECM proteomic datasets (http://matrisomeproject.mit.edu/ecm-atlas), and a new visualization tool of the 3D structures of biomolecules, based on the PDB Component Library and LiteMol, have also been added. A new advanced query interface now allows users to mine MatrixDB data using combinations of criteria, in order to build specific interaction networks related to diseases, biological processes, molecular functions or publications.

A pipeline to translate glycosaminoglycan sequences into 3D models. Application to the exploration of glycosaminoglycan conformational space.

Mammalian glycosaminoglycans are linear complex polysaccharides comprising heparan sulfate, heparin, dermatan sulfate, chondroitin sulfate, keratan sulfate and hyaluronic acid. They bind to numerous proteins and these interactions mediate their biological activities. GAG-protein interaction data reported in the literature are curated mostly in MatrixDB database (http://matrixdb.univ-lyon1.fr/). However, a standard nomenclature and a machine-readable format of GAGs together with bioinformatics tools for mining these interaction data are lacking. We report here the building of an automated pipeline to (i) standardize the format of GAG sequences interacting with proteins manually curated from the literature, (ii) translate them into the machine-readable GlycoCT format and into SNFG (Symbol Nomenclature For Glycan) images and (iii) convert their sequences into a format processed by a builder generating three-dimensional structures of polysaccharides based on a repertoire of conformations experimentally validated by data extracted from crystallized GAG-protein complexes. We have developed for this purpose a converter (the CT23D converter) to automatically translate the GlycoCT code of a GAG sequence into the input file required to construct a three-dimensional model.

Encoding and Estimating the Remarkable Diversity of Possible Sialyltrisaccharides in Nature

Glycan microarray development is a critical need for high throughput analysis of glycan‐protein interactions. Over last few years we have collaborated with several groups, and studied the binding of various protein molecules using this powerful technique, with a focus on non‐reducing terminal sialyltrisaccharides found in nature. Our current >200‐glycan microarray library includes a variety of sialoglycans terminated with common sialic acids (Neu5Ac, Neu5Gc, Kdn, and their modified derivatives) which were synthesized chemo‐enzymatically by our collaborators. Printing of these glycans on functionalized microarray slides gives a powerful approach to study glycan‐protein interactions.Considering the ever‐increasing size of our glycan library, microarray data sorting and analysis poses a major hurdle in any high throughput binding study. This situation called for a numerical bar‐coding system that assigns a unique code for individual glycans. Besides allowing for motif searches, one purpose of this system is to easily reorder the glycans in various logical ways during spreadsheet analyses, and another is to plan for further optimization of the printing process. The coding system encompasses the diverse linkage and stereochemistry of glycosyl bonds. Since most of our biological interest is in sialic acids, the first three digits of the code are assigned to describe the non‐reducing terminal sialic acid, its modifications, and the linkage. Underlying monosaccharides are assigned successively from the non‐reducing to the reducing end, each with three digits assigned to describe the monosaccharide, its modifications, and the linkage. Branching in glycan structures may be addressed by grouping digits in parentheses. The number sequence ends with a digit that represents the terminal amine linkers. With this method, we can accommodate all the structural variety that we have so far in our library, and many more. In addition, this system may be capable of creating an output of glycan symbol structures (using the Symbol Nomenclature for Glycans) via relevant programming.Using our coding system, we are able to consider new combinations of biologically‐possible defined terminal sialoglycan trisaccharides on O‐glycans, N‐glycans and gangliosides. In the course of setting up this coding system, we noted that the theoretical population of sialoglycan trisaccharide sequences is more than 205 million. Filtering out the impossible combinations, the number tentatively dropped two orders of magnitude to 1,359,709 (~106 possible combinations) of possible sialyltrisaccharides in nature. While we developed this system for linear trisaccharides, it has not escaped our notice that simply amplifying the calculation to a biantennary N‐glycan with two terminal sialoglycan trisaccharide sequences would result in squaring of the number of possibilities, giving >1012 potential combinations.Support or Funding InformationNIH U01 CA199792This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Corrigendum: Complex pectin metabolism by gut bacteria reveals novel catalytic functions.

This corrects the article DOI: 10.1038/nature21725.

Implementation of GlycanBuilder to draw a wide variety of ambiguous glycans

GlyTouCan version 1.0 was released in 2015 as the international glycan structure repository, and a new sequence format called WURCS (Web3 Unique Representation of Carbohydrate Structures) was proposed during the early stages of the GlyTouCan project. GlyTouCan uses WURCS as its base representation for glycans because existing formats were insufficient in their flexibility to represent any and all glycans universally. Therefore, in order to obtain WURCS strings for existing or new glycan structures, conversion tools or glycan structure editors that can export WURCS became necessary. GlycanBuilder was an obvious choice to extend due to its wide usage by the community. However, GlycanBuilder was limited because it was originally developed to support mammalian glycans. It also did not support the newly proposed monosaccharide symbol standard called Symbol Nomenclature for Glycans (SNFG). Therefore in this work, we implemented a new version of GlycanBuilder to greatly increase its usability. The glycan rendering system was refactored so that cyclic glycans, nested repeating units, monosaccharide compositions and cross-linked glycan structures can be represented. Both import and export utilities for WURCS were also implemented and SNFG symbols were incorporated to allow glycans to be exported as graphics using the latest glycan symbol nomenclature.This new version of GlycanBuilder called “GlycanBuilder2”, is able to support a wide variety of ambiguous glycans, including structures containing monosaccharides from bacteria and plants. These glycans can also be displayed using the new SNFG symbols. This tool can aid researchers in communicating about the complex, diverse, and ambiguous structures of glycans more rapidly. Moreover, the new GlycanBuilder can now easily output WURCS sequences from glycans drawn on the canvas. Most importantly, because GlyTouCan employs WURCS as the basic format for registration and searching of glycan information, a wider variety of glycans can now be readily registered and queried in GlyTouCan.

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

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.

3D implementation of the symbol nomenclature for graphical representation of glycans

3D implementation of the symbol nomenclature for graphical representation of glycans

Glycan Notation Standardized

Glycans, sugar polymers that decorate proteins and lipids, mediate molecular recognition and signaling processes in cells. Because of their critical role in cell biology, scientists want to synthesize and study glycans. But chemical line structures of glycans such as the one at right are difficult to interpret at a glance. To make representing glycans easier, scientists have developed two major graphical shorthand notations—the Essentials and Oxford systems—similar to the way amino acids are represented as single letters or sets of three letters, such as “A” or “Ala” for alanine. Carbohydrate chemists and glycobiologists have now agreed on an expanded and standardized symbol nomenclature based primarily on the Essentials notation (Glycobiology 2015, DOI: 10.1093/glycob/cwv091). The agreement “is a major step, as without a common vocabulary and language the glycosciences cannot advance as genomics and proteomics have,” says carbohydrate chemist Peter H. Seeberger of the Max Planck Institute of Colloids & Interfaces.