Glyco3D: a portal for structural glycosciences

TBL38 atypical homogalacturonan-acetylesterase activity and cell wall microdomain localization in Arabidopsis seed mucilage secretory cells

Plant cell walls constitute complex polysaccharidic/proteinaceous networks whose biosynthesis and dynamics implicate several cell compartments. The synthesis and remodeling of homogalacturonan pectins involve Golgi-localized methylation/acetylation and subsequent cell wall-localized demethylation/deacetylation. So far, TRICHOME BIREFRINGENCE-LIKE (TBL) family members have been described as Golgi-localized acetyltransferases targeting diverse hemicelluloses or pectins. Using seed mucilage secretory cells (MSCs) from Arabidopsis thaliana, we demonstrate the atypical localization of TBL38 restricted to a cell wall microdomain. A tbl38 mutant displays an intriguing homogalacturonan immunological phenotype in this cell wall microdomain and in an MSC surface-enriched abrasion powder. Mass spectrometry oligosaccharide profiling of this fraction reveals an increased homogalacturonan acetylation phenotype. Finally, TBL38 displays pectin acetylesterase activity in vitro. These results indicate that TBL38 is an atypical cell wall-localized TBL that displays a homogalacturonan acetylesterase activity rather than a Golgi-localized acetyltransferase activity as observed in previously studied TBLs. TBL38 function during seed development is discussed.

A periodic table of monosaccharides

It is important to recognize the great diversity of monosaccharides commonly encountered in animals, plants, and microbes, as well as to organize them in a visually interesting style that also emphasizes their similarities and relatedness. This article discusses the nature of building blocks, monosaccharides, and monosaccharide derivatives-terms commonly used in discussing "glycomolecules" found in nature. To aid in awareness of monosaccharide diversity, here is presented a Periodic Table of Monosaccharides. The rationale is given for construction of the Table and the selection of 103 monosaccharides, which is largely based on those presented in the KEGG and SNFG websites of monosaccharides, and includes room to enlarge as new discoveries are made. The Table should have educational value and is intended to capture the attention and foster imagination of those not very familiar with glycosciences, and encourage researchers to delve deeper into this fascinating area.

Conformational Preferences at the Glycosidic Linkage of Saccharides in Solution as Deduced from NMR Experiments and MD Simulations: Comparison to Crystal Structures

Glycans are central to information content and regulation in biological systems. These carbohydrate molecules are active either as oligo- or polysaccharides, often in the form of glycoconjugates. The monosaccharide entities are joined by glycosidic linkages and stereochemical arrangements are of utmost importance in determining conformation and flexibility of saccharides. The conformational preferences and population distributions at the glycosidic torsion angles φ and ψ have been investigated for O-methyl glycosides of three disaccharides where the substitution takes place at a secondary alcohol, viz., in α-l-Fucp-(1→3)-β-d-Glcp-OMe, α-l-Fucp-(1→3)-α-d-Galp-OMe and α-d-Glcp-(1→4)-α-d-Galp-OMe, corresponding to disaccharide structural elements present in bacterial polysaccharides. Stereochemical differences at or adjacent to the glycosidic linkage were explored by solution state NMR spectroscopy using one-dimensional 1 H,1 H-NOESY NMR experiments to obtain transglycosidic proton-proton distances and one- and two-dimensional heteronuclear NMR experiments to obtain 3 JCH transglycosidic coupling constants related to torsion angles φ and ψ. Computed effective proton-proton distances from molecular dynamics (MD) simulations showed excellent agreement to experimentally derived distances for the α-(1→3)-linked disaccharides and revealed that for the bimodal distribution at the ψ torsion angle for the α-(1→4)-linked disaccharide experiment and simulation were at variance with each other, calling for further force field developments. The MD simulations disclosed a highly intricate inter-residue hydrogen bonding pattern for the α-(1→4)-linked disaccharide, including a nonconventional hydrogen bond between H5' in the glucosyl residue and O3 in the galactosyl residue, supported by a large downfield 1 H NMR chemical shift displacement compared to α-d-Glcp-OMe. Comparison of population distributions of the glycosidic torsion angles φ and ψ in the disaccharide entities to those of corresponding crystal structures highlighted the potential importance of solvation on the preferred conformation.

Computational modeling of protein-carbohydrate interactions: Current trends and future challenges

The article leads the reader through an up-to-date presentation of the concepts, developments, and main applications of computational modeling to study protein-carbohydrate interactions. It follows with the presentation of some current issues and perspectives arising from the expected evolution of generic methodological developments in deep learning, immersive analytics, and virtual reality for molecular visualization and data management. Such methodological developments for macromolecular interactions would greatly benefit a wide range of scientific endeavors in the field of carbohydrate chemistry and biochemistry, including the following interrelated efforts dealing with highly crowded media, with examples concerning glycoside transferases, the extracellular matrix, and the exploration of interactions between complex carbohydrates and intrinsically disordered proteins.

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.

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.

Structure and interactions of the phloem lectin (phloem protein 2) Cus17 from Cucumis sativus

Phloem protein 2 (PP2) contributes crucially to phloem-based defense in plants by binding to carbohydrates displayed by pathogens. However, its three-dimensional structure and the sugar binding site remained unexplored. Here, we report the crystal structure of the dimeric PP2 Cus17 from Cucumis sativus in its apo form and complexed with nitrobenzene, N-acetyllactosamine, and chitotriose. Each protomer of Cus17 consists of two antiparallel four-stranded twisted β sheets, a β hairpin, and three short helices forming a β sandwich architectural fold. This structural fold has not been previously observed in other plant lectin families. Structure analysis of the lectin-carbohydrate complexes reveals an extended carbohydrate binding site in Cus17, composed mostly of aromatic amino acids. Our studies suggest a highly conserved tertiary structure and a versatile binding site capable of recognizing motifs common to diverse glycans on plant pathogens/pests, which makes the PP2 family suited for phloem-based plant defense.

Comparative study, homology modelling and molecular docking with cancer associated glycans of two non-fetuin-binding Tepary bean lectins

We present the purification and characterization of the two most abundant isoforms of lectins isolated from Tepary bean (Phaseolus acutifolius) seeds, which have been shown to differentially affect the survival of different cancer cells. They were separated by concanavalin A-affinity chromatography. After purification, to release the N-glycans, they were digested with the endoglycosidases PNGase and Glycanase A. Fractions resulted from the hydrolysis products were analyzed to determine their carbohydrate composition. Mass spectrometry data indicated that both isoforms contained high mannose glycans being mannose 6 the most abundant form. Furthermore, based on sequence Ans-X-Ser/Thr, where X is any amino acid except proline, a glycosylation site was determined on asparagine 36. When their metal requirement to preserve their biological activity was determined, the lectins showed differences. While lectin A (LA) agglutination activity was best in the presence of magnesium, lectin B (LB) was best with calcium. Additionally, only LA exhibited affinity to human type-A erythrocytes. Although both lectins showed small differences in their properties, an identical structure-model for both lectins was generated by the homology modelling process. Also, the analysis of ligand binding sites and in silico glycosylation were achieved. Molecular docking with colon adenocarcinoma associated-N-glycans revealed some highly possible interactions and, on the other hand, that N-glycan interaction zones of Tepary bean lectins is not restricted to the carbohydrate binding domain but to an extended part of their surface, which could lead new strategies to explain their biological activity.

Pineapple Lectin AcmJRL Binds SARS-CoV-2 Spike Protein in a Carbohydrate-Dependent Fashion

The highly glycosylated spike protein of SARS-CoV-2 is essential for infection and constitutes a prime target for antiviral agents and vaccines. The pineapple-derived jacalin-related lectin AcmJRL is present in the medication bromelain in significant quantities and has previously been described to bind mannosides. Here, we performed a large ligand screening of AcmJRL by glycan array analysis, quantified the interaction with carbohydrates and validated high-mannose glycans as preferred ligands. Because the SARS-CoV-2 spike protein was previously reported to carry a high proportion of high-mannose N-glycans, we tested the binding of AcmJRL to the recombinantly produced extraviral domain of spike protein. We could demonstrate that AcmJRL binds the spike protein with a low-micromolar KD in a carbohydrate-dependent fashion.

Multifaceted Computational Modeling in Glycoscience

Glycoscience assembles all the scientific disciplines involved in studying various molecules and macromolecules containing carbohydrates and complex glycans. Such an ensemble involves one of the most extensive sets of molecules in quantity and occurrence since they occur in all microorganisms and higher organisms. Once the compositions and sequences of these molecules are established, the determination of their three-dimensional structural and dynamical features is a step toward understanding the molecular basis underlying their properties and functions. The range of the relevant computational methods capable of addressing such issues is anchored by the specificity of stereoelectronic effects from quantum chemistry to mesoscale modeling throughout molecular dynamics and mechanics and coarse-grained and docking calculations. The Review leads the reader through the detailed presentations of the applications of computational modeling. The illustrations cover carbohydrate-carbohydrate interactions, glycolipids, and N- and O-linked glycans, emphasizing their role in SARS-CoV-2. The presentation continues with the structure of polysaccharides in solution and solid-state and lipopolysaccharides in membranes. The full range of protein-carbohydrate interactions is presented, as exemplified by carbohydrate-active enzymes, transporters, lectins, antibodies, and glycosaminoglycan binding proteins. A final section features a list of 150 tools and databases to help address the many issues of structural glycobioinformatics.

Structure-function relationship of a novel fucoside-binding fruiting body lectin from Coprinopsis cinerea exhibiting nematotoxic activity

Lectins are non-immunoglobulin-type proteins that bind to specific carbohydrate epitopes and play important roles in intra- and inter-organismic interactions. Here, we describe a novel fucose-specific lectin, termed CML1, which we identified from fruiting body extracts of Coprinopsis cinerea. For further characterization, the coding sequence for CML1 was cloned and heterologously expressed in Escherichia coli. Feeding of CML1-producing bacteria inhibited larval development of the bacterivorous nematode Caenorhabditis tropicalis, but not of C. elegans. The crystal structure of the recombinant protein in its apo-form and in complex with H type I or Lewis A blood group antigens was determined by X-ray crystallography. The protein folds as a sandwich of 2 antiparallel β-sheets and forms hexamers resulting from a trimer of dimers. The hexameric arrangement was confirmed by small-angle X-ray scattering (SAXS). One carbohydrate-binding site per protomer was found at the dimer interface with both protomers contributing to ligand binding, resulting in a hexavalent lectin. In terms of lectin activity of recombinant CML1, substitution of the carbohydrate-interacting residues His54, Asn55, Trp94, and Arg114 by Ala abolished carbohydrate-binding and nematotoxicity. Although no similarities to any characterized lectin were found, sequence alignments identified many non-characterized agaricomycete proteins. These results suggest that CML1 is the founding member of a novel family of fucoside-binding lectins involved in the defense of agaricomycete fruiting bodies against predation by fungivorous nematodes.

Current status of PTMs structural databases: applications, limitations and prospects

Protein 3D structures, determined by their amino acid sequences, are the support of major crucial biological functions. Post-translational modifications (PTMs) play an essential role in regulating these functions by altering the physicochemical properties of proteins. By virtue of their importance, several PTM databases have been developed and released in decades, but very few of these databases incorporate real 3D structural data. Since PTMs influence the function of the protein and their aberrant states are frequently implicated in human diseases, providing structural insights to understand the influence and dynamics of PTMs is crucial for unraveling the underlying processes. This review is dedicated to the current status of databases providing 3D structural data on PTM sites in proteins. Some of these databases are general, covering multiple types of PTMs in different organisms, while others are specific to one particular type of PTM, class of proteins or organism. The importance of these databases is illustrated with two major types of in silico applications: predicting PTM sites in proteins using machine learning approaches and investigating protein structure-function relationships involving PTMs. Finally, these databases suffer from multiple problems and care must be taken when analyzing the PTMs data.

An Interactive View of Glycosylation

The present chapter focuses on the interactive and explorative aspects of bioinformatics resources that have been recently released in glycobiology. The comparative analysis of data in a field where knowledge is scattered, incomplete, and disconnected from main biology requires efficient visualization, integration, and interactive tools that are currently only partially implemented. This overview highlights converging efforts toward building a consistent picture of protein glycosylation.

GTXplorer: A portal to navigate and visualize the evolutionary information encoded in fold a glycosyltransferases

Glycosyltransferases (GTs) play a central role in sustaining all forms of life through the biosynthesis of complex carbohydrates. Despite significant strides made in recent years to establish computational resources, databases, and tools to understand the nature and role of carbohydrates and related glycoenzymes, a data analytics framework that connects the sequence-structure-function relationships to the evolution of GTs is currently lacking. This hinders the characterization of understudied GTs and the synthetic design of GTs for medical and biotechnology applications. Here, we present GTXplorer as an integrated platform that presents evolutionary information of GTs adopting a GT-A fold in an intuitive format enabling in silico investigation through comparative sequence analysis to derive informed hypotheses about their function. The tree view mode provides an overview of the evolutionary relationships of GT-A families and allows users to select phylogenetically relevant families for comparisons. The selected families can then be compared in the alignment view at the residue level using annotated weblogo stacks of the GT-A core specific to the selected clade, family, or subfamily. All data are easily accessible and can be downloaded for further analysis. GTXplorer can be accessed at https://vulcan.cs.uga.edu/gtxplorer/ or from GitHub at https://github.com/esbgkannan/GTxplorer to deploy locally. By packaging multiple data streams into an accessible, user-friendly format, GTXplorer presents the first evolutionary data analytics platform for comparative glycomics.

Mevo lectin specificity towards high-mannose structures with terminal αMan(1,2)αMan residues and its implication to inhibition of the entry of Mycobacterium tuberculosis into macrophages

Mannose-binding lectins can specifically recognize and bind complex glycan structures on pathogens and have potential as anti-viral and anti-bacterial agents. We previously reported the structure of a lectin from an archaeal species, Mevo lectin, which has specificity towards terminal α1,2 linked manno-oligosaccharides. Mycobacterium tuberculosis (M. tuberculosis) expresses mannosylated structures including, lipoarabinomannan (ManLAM) on its surface and exploits C-type lectins to gain entry into the host cells. ManLAM structure has mannose capping with terminal αMan(1,2)αMan residues and is important for recognition by innate immune cells. Here, we aim to address the specificity of Mevo lectin towards high-mannose type glycans with terminal αMan(1,2)αMan residues and its effect on M. tuberculosis internalization by macrophages. ITC studies demonstrated that Mevo lectin shows preferential binding towards manno-oligosaccharides with terminal αMan(1,2)αMan structures, and showed a strong affinity for ManLAM, whereas it binds weakly to Mycobacterium smegmatis (M. smegmatis) lipoarabinomannan (MsmLAM), which displays relatively fewer and shorter mannosyl caps. Crystal structure of Mevo lectin complexed with a Man7D1 revealed the multivalent cross-linking interaction, which explains avidity-based high affinity for these ligands when compared to previously studied manno-oligosaccharides lacking the specific termini. Functional studies suggest that M. tuberculosis internalization by the macrophage was impaired by binding of Mevo lectin to ManLAM present on the surface of M. tuberculosis. Selectivity shown by Mevo lectin towards glycans with terminal αMan(1,2)αMan structures, and its ability to compromise the internalization of M. tuberculosis in vitro, underscore the potential utility of Mevo lectin as a research tool to study host-pathogen interactions.

GAG-DB, the New Interface of the Three-Dimensional Landscape of Glycosaminoglycans

Glycosaminoglycans (GAGs) are complex linear polysaccharides. GAG-DB is a curated database that classifies the three-dimensional features of the six mammalian GAGs (chondroitin sulfate, dermatan sulfate, heparin, heparan sulfate, hyaluronan, and keratan sulfate) and their oligosaccharides complexed with proteins. The entries are structures of GAG and GAG-protein complexes determined by X-ray single-crystal diffraction methods, X-ray fiber diffractometry, solution NMR spectroscopy, and scattering data often associated with molecular modeling. We designed the database architecture and the navigation tools to query the database with the Protein Data Bank (PDB), UniProtKB, and GlyTouCan (universal glycan repository) identifiers. Special attention was devoted to the description of the bound glycan ligands using simple graphical representation and numerical format for cross-referencing to other databases in glycoscience and functional data. GAG-DB provides detailed information on GAGs, their bound protein ligands, and features their interactions using several open access applications. Binding covers interactions between monosaccharides and protein monosaccharide units and the evaluation of quaternary structure. GAG-DB is freely available.

Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy

Glycosylation plays a crucial role in various diseases and their etiology. This has led to a clear understanding on the functions of carbohydrates in cell communication, which eventually will result in novel therapeutic approaches for treatment of various disease. Glycomics has now become one among the top ten technologies that will change the future. The direct implication of glycosylation as a hallmark of cancer and for cancer therapy is well established. As in proteomics, where bioinformatics tools have led to revolutionary achievements, bioinformatics resources for glycosylation have improved its practical implication. Bioinformatics tools, algorithms and databases are a mandatory requirement to manage and successfully analyze large amount of glycobiological data generated from glycosylation studies. This review consolidates all the available tools and their applications in glycosylation research. The achievements made through the use of bioinformatics into glycosylation studies are also presented. The importance of glycosylation in cancer diagnosis and therapy is discussed and the gap in the application of widely available glyco-informatic tools for cancer research is highlighted. This review is expected to bring an awakening amongst glyco-informaticians as well as cancer biologists to bridge this gap, to exploit the available glyco-informatic tools for cancer.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Interactions between cell wall polysaccharides and polyphenols: Effect of molecular internal structure

Cell wall polysaccharides (CPSs) and polyphenols are major constituents of the dietary fiber complex in plant-based foods. Their digestion (by gut microbiota) and bioefficacy depend not only on their structure and quantity, but also on their intermolecular interactions. The composition and structure of these compounds vary with their dietary source (i.e., fruit or vegetable of origin) and can be further modified by food processing. Various components and structures of CPSs and polyphenols have been observed to demonstrate common and characteristic behaviors during interactions. However, at a fundamental level, the mechanisms that ultimately drive these interactions are still not fully understood. This review summarizes the current state of knowledge on the internal factors that influence CPS-polyphenol interactions, describes the different ways in which these interactions can be mediated by molecular composition or structure, and introduces the main methods for the analysis of these interactions, as well as the mechanisms involved. Furthermore, a comprehensive overview is provided of recent key findings in the area of CPS-polyphenol interactions. It is becoming clear that these interactions are shaped by a multitude of factors, the most important of which are the physicochemical properties of the partners: their morphology (surface area and porosity/pore shape), chemical composition (sugar ratio, solubility, and non-sugar components), and molecular architecture (molecular weight, degree of esterification, functional groups, and conformation). An improved understanding of the molecular mechanisms that drive interactions between CPSs and polyphenols may allow us to better establish a bridge between food processing and the bioavailability of colonic fermentation products from CPSs and antioxidant polyphenols, which could ultimately lead to the development of new guidelines for the design of healthier and more nutritious foods.

Structural and related studies on Mevo lectin from Methanococcus voltae A3: the first thorough characterization of an archeal lectin and its interactions

Crystallographic and solution studies of Mevo lectin and its complexes, the first effort of its kind on an archeal lectin, reveal a structure similar to β-prism I fold lectins from plant and animal sources, but with a quaternary association involving a ring structure with seven-fold symmetry. Each subunit in the heptamer carries one sugar binding site on the first Greek key motif. The oligomeric interface is primarily made up of a parallel β-sheet involving a strand of Greek key I of one subunit and Greek key ΙΙΙ from a neighboring subunit. The crystal structures of the complexes of the lectin with mannose, αMan(1,2)αMan, αMan(1,3)αMan, a mannotriose and a mannopentose revealed a primary binding site similar to that found in other mannose specific β-prism I fold lectins. The complex with αMan(1,3)αMan provides an interesting case in which a few subunits have the reducing end at the primary binding site, while the majority have the nonreducing end at the primary binding site. The structures of complexes involving the trisaccharide and the pentasaccharide exhibit cross-linking among heptameric molecules. The observed arrangements may be relevant to the multivalency of the lectin. Phylogenetic analysis of amino acid sequences indicates that Mevo lectin is closer to β-prism I fold animal lectins than with those of plant origin. The results presented here reinforce the conclusion regarding the existence of lectins in all three domains of life. It would also appear that lectins evolved to the present form before the three domains diverged.

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.

The current structural glycome landscape and emerging technologies

Carbohydrates represent one of the building blocks of life, along with nucleic acids, proteins and lipids. Although glycans are involved in a wide range of processes from embryogenesis to protein trafficking and pathogen infection, we are still a long way from deciphering the glycocode. In this review, we aim to present a few of the challenges that researchers working in the area of glycobiology can encounter and what strategies can be utilised to overcome them. Our goal is to paint a comprehensive picture of the current saccharide landscape available in the Protein Data Bank (PDB). We also review recently updated repositories relevant to the topic proposed, the impact of software development on strategies to structurally solve carbohydrate moieties, and state-of-the-art molecular and cellular biology methods that can shed some light on the function and structure of glycans.

Current Status of Carbohydrates Information in the Protein Data Bank

Carbohydrates are well known for their physicochemical, biological, functional, and therapeutic characteristics. Unfortunately, their chemical nature imposes severe challenges for the structural elucidation of these phenomena, impairing not only the depth of our understanding of carbohydrates but also the development of new biotechnological and therapeutic applications based on these molecules. In the recent past, the amount of structural information, obtained mainly from X-ray crystallography, has increased progressively, as well as its quality. In this context, the current work presents a global analysis of the carbohydrate information available in the Protein Data Bank (PDB). From high quality structures, it is clear that most of the data are highly concentrated on a few sets of residue types, on their monosaccharidic forms, and connected by a small diversity of glycosidic linkages. The geometries of these linkages can be mostly associated with the types of linkages instead of residues, while the level of puckering distortion was characterized, quantified, and located in a pseudorotational equilibrium landscape, not only to local minima but also to transitional states. These qualitative and quantitative analyses offer a global picture of the carbohydrate structural content in the PDB, potentially supporting the building of new models for carbohydrate-related biological phenomena at the atomistic level, including new developments on force field parameters.

ProCarbDB: a database of carbohydrate-binding proteins

Carbohydrate-binding proteins play crucial roles across all organisms and viruses. The complexity of carbohydrate structures, together with inconsistencies in how their 3D structures are reported, has led to difficulties in characterizing the protein-carbohydrate interfaces. In order to better understand protein-carbohydrate interactions, we have developed an open-access database, ProCarbDB, which, unlike the Protein Data Bank (PDB), clearly distinguishes between the complete carbohydrate ligands and their monomeric units. ProCarbDB is a comprehensive database containing over 5200 3D X-ray crystal structures of protein-carbohydrate complexes. In ProCarbDB, the complete carbohydrate ligands are annotated and all their interactions are displayed. Users can also select any protein residue in the proximity of the ligand to inspect its interactions with the carbohydrate ligand and with other neighbouring protein residues. Where available, additional curated information on the binding affinity of the complex and the effects of mutations on the binding have also been provided in the database. We believe that ProCarbDB will be an invaluable resource for understanding protein-carbohydrate interfaces. The ProCarbDB web server is freely available at http://www.procarbdb.science/procarb.

BC2L-C N-Terminal Lectin Domain Complexed with Histo Blood Group Oligosaccharides Provides New Structural Information

Lectins mediate adhesion of pathogens to host tissues, filling in a key role in the first steps of infection. Belonging to the opportunistic pathogen Burkholderia cenocepacia, BC2L-C is a superlectin with dual carbohydrate specificity, believed to mediate cross-linking between bacteria and host cells. Its C-terminal domain binds to bacterial mannosides while its N-terminal domain (BCL2-CN) recognizes fucosylated human epitopes. BC2L-CN presents a tumor necrosis factor alpha (TNF-) fold previously unseen in lectins with a novel fucose binding mode. We report, here, the production of a novel recombinant form of BC2L-CN (rBC2L-CN2), which allowed better protein stability and unprecedented co-crystallization with oligosaccharides. Isothermal calorimetry measurements showed no detrimental effect on ligand binding and data were obtained on the binding of Globo H hexasaccharide and l-galactose. Crystal structures of rBC2L-CN2 were solved in complex with two blood group antigens: H-type 1 and H-type 3 (Globo H) by X-ray crystallography. They provide new structural information on the binding site, of importance for the structural-based design of glycodrugs as new antimicrobials with antiadhesive properties.

Structural Database for Lectins and the UniLectin Web Platform

The search for new biomolecules requires a clear understanding of biosynthesis and degradation pathways. This view applies to most metabolites as well as other molecule types such as glycans whose repertoire is still poorly characterized. Lectins are proteins that recognize specifically and interact noncovalently with glycans. This particular class of proteins is considered as playing a major role in biology. Glycan-binding is based on multivalence, which gives lectins a unique capacity to interact with surface glycans and significantly contribute to cell-cell recognition and interactions. Lectins have been studied for many years using multiple technologies and part of the resulting information is available online in databases. Unfortunately, the connectivity of these databases with the most popular omics databases (genomics, proteomics, and glycomics) remains limited. Moreover, lectin diversity is extended and requires setting out a flexible classification that remains compatible with new sequences and 3D structures that are continuously released. We have designed UniLectin as a new insight into the knowledge of lectins, their classification, and their biological role. This platform encompasses UniLectin3D, a curated database of lectin 3D structures that follows a periodically updated classification, a set of comparative and visualizing tools and gradually released modules dedicated to specific lectins predicted in sequence databases. The second module is PropLec, focused on β-propeller lectin prediction in all species based on five distinct family profiles. This chapter describes how UniLectin can be used to explore the diversity of lectins, their 3D structures, and associated functional information as well as to perform reliable predictions of β-propeller lectins.

Recent advances in glycoinformatic platforms for glycomics and glycoproteomics

Protein glycosylation is the most complex and prevalent post-translation modification in terms of the number of proteins modified and the diversity generated. To understand the functional roles of glycoproteins it is important to gain an insight into the repertoire of oligosaccharides present. The comparison and relative quantitation of glycoforms combined with site-specific identification and occupancy are necessary steps in this direction. Computational platforms have continued to mature assisting researchers with the interpretation of such glycomics and glycoproteomics data sets, but frequently support dedicated workflows and users rely on the manual interpretation of data to gain insights into the glycoproteome. The growth of site-specific knowledge has also led to the implementation of machine-learning algorithms to predict glycosylation which is now being integrated into glycoproteomics pipelines. This short review describes commercial and open-access databases and software with an emphasis on those that are actively maintained and designed to support current analytical workflows.

Lectin biosensors in cancer glycan biomarker detection

Cancer has high incidence and it will continue to increase over the next decades. Detection and quantification of cancer-associated biomarkers is frequently carried out for diagnosis, prognosis and treatment monitoring at various disease stages. It is well-known that glycosylation profiles change significantly during oncogenesis. Aberrant glycans produced during tumorigenesis are, therefore, valuable molecules for detection and characterization of cancer, and for therapeutic design and monitoring. Although glycoproteomics has benefited from the development of analytical tools such as high performance liquid chromatography, two-dimensional gel and capillary electrophoresis and mass spectrometry, these approaches are not well suited for rapid point-of-care (POC) testing easily performed by medical staff. Lectins are biomolecules found in nature with specific affinities toward particular glycan structures and bind them thus forming a relatively strong complex. Because of this characteristic, lectins have been used in analytical techniques for the selective capture or separation of certain glycans in complex samples, namely, in lectin affinity chromatography, or to characterize glycosylation profiles in diverse clinical situations, using lectin microarrays. Lectin-based biosensors have been developed for the detection of specific aberrant and cancer-associated glycostructures to aid diagnosis, prognosis and treatment assessment of these patients. The attractive features of biosensors, such as portability and simple use make them highly suitable for POC testing. Recent developments in lectin biosensors, as well as their potential and pitfalls in cancer glycan biomarker detection, are presented in this chapter.

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.

Perspective on computational simulations of glycosaminoglycans

Glycosaminoglycans (GAGs) represent a formidable frontier for chemists, biochemists, biologists, medicinal chemists and drug delivery specialists because of massive structural complexity. GAGs are arguably the most complex, natural linear biopolymers with theoretical diversity orders of magnitude higher than proteins and nucleic acids. Yet, this diversity remains generally untapped. Computational approaches offer major routes to understand GAG structure and dynamics so as to enable novel applications of these biopolymers. In fact, computational algorithms, softwares, online tools and techniques have reached a level of sophistication that help understand atomistic details of conformational variation and protein recognition of individual GAG sequences. This review describes current approaches and challenges in computational study of GAGs. It presents a history of major findings since the earliest mention of GAGs (the 1960s), the development of parameters and force fields specific for GAGs, and the application of these tools in understanding GAG structure-function relationship. This review also presents a section on how to perform simulation of GAGs, which is directed toward researchers interested in entering this promising field with potential to impact therapy.

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.

Computational Prediction of Carbohydrate-Binding Proteins and Binding Sites

Protein-carbohydrate interaction is essential for biological systems, and carbohydrate-binding proteins (CBPs) are important targets when designing antiviral and anticancer drugs. Due to the high cost and difficulty associated with experimental approaches, many computational methods have been developed as complementary approaches to predict CBPs or carbohydrate-binding sites. However, most of these computational methods are not publicly available. Here, we provide a comprehensive review of related studies and demonstrate our two recently developed bioinformatics methods. The method SPOT-CBP is a template-based method for detecting CBPs based on structure through structural homology search combined with a knowledge-based scoring function. This method can yield model complex structure in addition to accurate prediction of CBPs. Furthermore, it has been observed that similarly accurate predictions can be made using structures from homology modeling, which has significantly expanded its applicability. The other method, SPRINT-CBH, is a de novo approach that predicts binding residues directly from protein sequences by using sequence information and predicted structural properties. This approach does not need structurally similar templates and thus is not limited by the current database of known protein-carbohydrate complex structures. These two complementary methods are available at https://sparks-lab.org. © 2018 by John Wiley & Sons, Inc.

Recognition of Complex Core-Fucosylated N-Glycans by a Mini Lectin

The mini fungal lectin PhoSL was recombinantly produced and characterized. Despite a length of only 40 amino acids, PhoSL exclusively recognizes N-glycans with α1,6-linked fucose. Core fucosylation influences the intrinsic properties and bioactivities of mammalian N-glycoproteins and its level is linked to various cancers. Thus, PhoSL serves as a promising tool for glycoprofiling. Without structural precedence, the crystal structure was solved using the zinc anomalous signal, and revealed an interlaced trimer creating a novel protein fold termed β-prism III. Three biantennary core-fucosylated N-glycan azides of 8 to 12 sugars were cocrystallized with PhoSL. The resulting highly resolved structures gave a detailed view on how the exclusive recognition of α1,6-fucosylated N-glycans by such a small protein occurs. This work also provided a protein consensus motif for the observed specificity as well as a glimpse into N-glycan flexibility upon binding.

Glycan Reader is improved to recognize most sugar types and chemical modifications in the Protein Data Bank

Motivation

Glycans play a central role in many essential biological processes. Glycan Reader was originally developed to simplify the reading of Protein Data Bank (PDB) files containing glycans through the automatic detection and annotation of sugars and glycosidic linkages between sugar units and to proteins, all based on atomic coordinates and connectivity information. Carbohydrates can have various chemical modifications at different positions, making their chemical space much diverse. Unfortunately, current PDB files do not provide exact annotations for most carbohydrate derivatives and more than 50% of PDB glycan chains have at least one carbohydrate derivative that could not be correctly recognized by the original Glycan Reader.

Results

Glycan Reader has been improved and now identifies most sugar types and chemical modifications (including various glycolipids) in the PDB, and both PDB and PDBx/mmCIF formats are supported. CHARMM-GUI Glycan Reader is updated to generate the simulation system and input of various glycoconjugates with most sugar types and chemical modifications. It also offers a new functionality to edit the glycan structures through addition/deletion/modification of glycosylation types, sugar types, chemical modifications, glycosidic linkages, and anomeric states. The simulation system and input files can be used for CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Glycan Fragment Database in GlycanStructure.Org is also updated to provide an intuitive glycan sequence search tool for complex glycan structures with various chemical modifications in the PDB.

Availability and implementation

http://www.charmm-gui.org/input/glycan and http://www.glycanstructure.org.

Contact

wonpil@lehigh.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Emerging glycobiology tools: A renaissance in accessibility

The glycobiology of the immune response is a topic that has garnered increased attention due to a number of key discoveries surrounding IgG function, the specificity of some broadly neutralizing anti-HIV antibodies, cancer immunoregulation by galectin molecules and others. This review is the opening article in a Special Edition of Cellular Immunology focused on glycoimmunology, and has the goal of setting the context for these articles by providing a mini-review of how glycans impact immunity. We also focus on some of the technological and methodological advances in the field of glycobiology that are being deployed to lower the barrier of entry into the glycosciences, and to more fully interrogate the glycome and its function.

A Two-Step Feature Selection Method to Predict Cancerlectins by Multiview Features and Synthetic Minority Oversampling Technique

Cancerlectins have an inhibitory effect on the growth of cancer cells and are currently being employed as therapeutic agents. The accurate identification of the cancerlectins should provide insight into the molecular mechanisms of cancers. In this study, a new computational method based on the RF (Random Forest) algorithm is proposed for further improving the performance of identifying cancerlectins. Hybrid feature space before feature selection is developed by combining different individual feature spaces, CTD (Composition, Transition, and Distribution), PseAAC (Pseudo Amino Acid Composition), PSSM (Position-Specific Scoring Matrix), and disorder. The SMOTE (Synthetic Minority Oversampling Technique) is applied to solve the imbalanced data problem. To reduce feature redundancy and computation complexity, we propose a two-step feature selection process to select informative features. A 5-fold cross-validation technique is used for the evaluation of various prediction strategies. The proposed method achieves a sensitivity of 0.779, a specificity of 0.717, an accuracy of 0.748, and an MCC (Matthew's Correlation Coefficient) of 0.497. The prediction results are also compared with other existing methods on the same dataset using 5-fold cross-validation. The comparison results demonstrate the high effectiveness of our method for predicting cancerlectins.

Glycoscience@Synchrotron: Synchrotron radiation applied to structural glycoscience

Synchrotron radiation is the most versatile way to explore biological materials in different states: monocrystalline, polycrystalline, solution, colloids and multiscale architectures. Steady improvements in instrumentation have made synchrotrons the most flexible intense X-ray source. The wide range of applications of synchrotron radiation is commensurate with the structural diversity and complexity of the molecules and macromolecules that form the collection of substrates investigated by glycoscience. The present review illustrates how synchrotron-based experiments have contributed to our understanding in the field of structural glycobiology. Structural characterization of protein–carbohydrate interactions of the families of most glycan-interacting proteins (including glycosyl transferases and hydrolases, lectins, antibodies and GAG-binding proteins) are presented. Examples concerned with glycolipids and colloids are also covered as well as some dealing with the structures and multiscale architectures of polysaccharides. Insights into the kinetics of catalytic events observed in the crystalline state are also presented as well as some aspects of structure determination of protein in solution.

Legume Lectins: Proteins with Diverse Applications

Lectins are a diverse class of proteins distributed extensively in nature. Among these proteins; legume lectins display a variety of interesting features including antimicrobial; insecticidal and antitumor activities. Because lectins recognize and bind to specific glycoconjugates present on the surface of cells and intracellular structures; they can serve as potential target molecules for developing practical applications in the fields of food; agriculture; health and pharmaceutical research. This review presents the current knowledge of the main structural characteristics of legume lectins and the relationship of structure to the exhibited specificities; provides an overview of their particular antimicrobial; insecticidal and antitumor biological activities and describes possible applications based on the pattern of recognized glyco-targets.

Crystallization and biochemical characterization of an archaeal lectin from Methanococcus voltae A3

A lectin from Methanococcus voltae A3 has been cloned, expressed, purified and characterized. The lectin appears to be specific for complex sugars. The protein crystallized in a tetragonal space group, with around 16 subunits in the asymmetric unit. Sequence comparisons indicate the lectin to have a β-prism I fold, with poor homology to lectins of known three-dimensional structure.

Glycoblocks: a schematic three-dimensional representation for glycans and their interactions

The close-range interactions provided by covalently linked glycans are essential for the correct folding of glycoproteins and also play a pivotal role in recognition processes. Being able to visualise protein-glycan and glycan-glycan contacts in a clear way is thus of great importance for the understanding of these biological processes. In structural terms, glycosylation sugars glue the protein together via hydrogen bonds, whereas non-covalently bound glycans frequently harness additional stacking interactions. Finding an unobscured molecular view of these multipartite scenarios is usually far from trivial; in addition to the need to show the interacting protein residues, glycans may contain many branched sugars, each composed of more than ten non-H atoms and offering more than three potential bonding partners. With structural glycoscience finally gaining popularity and steadily increasing the deposition rate of three-dimensional structures of glycoproteins, the need for a clear way of depicting these interactions is more pressing than ever. Here a schematic representation, named Glycoblocks, is introduced which combines a simplified bonding-network depiction (covering hydrogen bonds and stacking interactions) with the familiar two-dimensional glycan notation used by the glycobiology community, brought into three dimensions by the CCP4 molecular graphics project (CCP4mg).

Databases and Associated Tools for Glycomics and Glycoproteomics

The access to biodatabases for glycomics and glycoproteomics has proven to be essential for current glycobiological research. This chapter presents available databases that are devoted to different aspects of glycobioinformatics. This includes oligosaccharide sequence databases, experimental databases, 3D structure databases (of both glycans and glycorelated proteins) and association of glycans with tissue, disease, and proteins. Specific search protocols are also provided using tools associated with experimental databases for converting primary glycoanalytical data to glycan structural information. In particular, researchers using glycoanalysis methods by U/HPLC (GlycoBase), MS (GlycoWorkbench, UniCarb-DB, GlycoDigest), and NMR (CASPER) will benefit from this chapter. In addition we also include information on how to utilize glycan structural information to query databases that associate glycans with proteins (UniCarbKB) and with interactions with pathogens (SugarBind).