Prospects for glycoinformatics

Protein glycosylation and glycoinformatics for novel biomarker discovery in neurodegenerative diseases

Glycosylation is a common post-translational modification of brain proteins including cell surface adhesion molecules, synaptic proteins, receptors and channels, as well as intracellular proteins, with implications in brain development and functions. Using advanced state-of-the-art glycomics and glycoproteomics technologies in conjunction with glycoinformatics resources, characteristic glycosylation profiles in brain tissues are increasingly reported in the literature and growing evidence shows deregulation of glycosylation in central nervous system disorders, including aging associated neurodegenerative diseases. Glycan signatures characteristic of brain tissue are also frequently described in cerebrospinal fluid due to its enrichment in brain-derived molecules. A detailed structural analysis of brain and cerebrospinal fluid glycans collected in publications in healthy and neurodegenerative conditions was undertaken and data was compiled to create a browsable dedicated set in the GlyConnect database of glycoproteins (https://glyconnect.expasy.org/brain). The shared molecular composition of cerebrospinal fluid with brain enhances the likelihood of novel glycobiomarker discovery for neurodegeneration, which may aid in unveiling disease mechanisms, therefore, providing with novel therapeutic targets as well as diagnostic and progression monitoring tools.

Simple and practical sialoglycan encoding system reveals vast diversity in nature and identifies a universal sialoglycan-recognizing probe derived from AB5 toxin B subunits

Vertebrate sialic acids (Sias) display much diversity in modifications, linkages, and underlying glycans. Slide microarrays allow high-throughput explorations of sialoglycan-protein interactions. A microarray presenting ~150 structurally defined sialyltrisaccharides with various Sias linkages and modifications still poses challenges in planning, data sorting, visualization, and analysis. To address these issues, we devised a simple 9-digit code for sialyltrisaccharides with terminal Sias and underlying two monosaccharides assigned from the nonreducing end, with 3 digits assigning a monosaccharide, its modifications, and linkage. Calculations based on the encoding system reveal >113,000 likely linear sialyltrisaccharides in nature. Notably, a biantennary N-glycan with 2 terminal sialyltrisaccharides could thus have >1010 potential combinations and a triantennary N-glycan with 3 terminal sequences, >1015 potential combinations. While all possibilities likely do not exist in nature, sialoglycans encode enormous diversity. While glycomic approaches are used to probe such diverse sialomes, naturally occurring bacterial AB5 toxin B subunits are simpler tools to track the dynamic sialome in biological systems. Sialoglycan microarray was utilized to compare sialoglycan-recognizing bacterial toxin B subunits. Unlike the poor correlation between B subunits and species phylogeny, there is stronger correlation with Sia-epitope preferences. Further supporting this pattern, we report a B subunit (YenB) from Yersinia enterocolitica (broad host range) recognizing almost all sialoglycans in the microarray, including 4-O-acetylated-Sias not recognized by a Yersinia pestis orthologue (YpeB). Differential Sia-binding patterns were also observed with phylogenetically related B subunits from Escherichia coli (SubB), Salmonella Typhi (PltB), Salmonella Typhimurium (ArtB), extra-intestinal E.coli (EcPltB), Vibrio cholera (CtxB), and cholera family homologue of E. coli (EcxB).

Glycoinformatics in the Artificial Intelligence Era

Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.

Informatics Ecosystems to Advance the Biology of Glycans

Glycomics researchers have identified the need for integrated database systems for collecting glycomics information in a consistent format. The goal is to create a resource for knowledge discovery and dissemination to wider research communities. This has the potential and has exhibited initial success, to extend the research community to include biologists, clinicians, chemists, and computer scientists. This chapter discusses the technology and approach needed to create integrated data resources and informatics ecosystems to empower the broader community to leverage extant glycomics data. The focus is on glycosaminoglycan (GAGs) and proteoglycan research, but the approach can be generalized. The methods described span the development of glycomics standards from CarbBank to Glyco Connection Tables. Integrated data sets provide a foundation for novel methods of analysis such as machine learning and deep learning for knowledge discovery. The implications of predictive analysis are examined in relation to disease biomarker to expand the target audience of GAG and proteoglycan research.

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.

Heparan sulfate and heparin interactions with proteins

Heparan sulfate (HS) polysaccharides are ubiquitous components of the cell surface and extracellular matrix of all multicellular animals, whereas heparin is present within mast cells and can be viewed as a more sulfated, tissue-specific, HS variant. HS and heparin regulate biological processes through interactions with a large repertoire of proteins. Owing to these interactions and diverse effects observed during in vitro, ex vivo and in vivo experiments, manifold biological/pharmacological activities have been attributed to them. The properties that have been thought to bestow protein binding and biological activity upon HS and heparin vary from high levels of sequence specificity to a dependence on charge. In contrast to these opposing opinions, we will argue that the evidence supports both a level of redundancy and a degree of selectivity in the structure-activity relationship. The relationship between this apparent redundancy, the multi-dentate nature of heparin and HS polysaccharide chains, their involvement in protein networks and the multiple binding sites on proteins, each possessing different properties, will also be considered. Finally, the role of cations in modulating HS/heparin activity will be reviewed and some of the implications for structure-activity relationships and regulation will be discussed.

Databases of Conformations and NMR Structures of Glycan Determinants

The present study reports a comprehensive nuclear magnetic resonance (NMR) characterization and a systematic conformational sampling of the conformational preferences of 170 glycan moieties of glycosphingolipids as produced in large-scale quantities by bacterial fermentation. These glycans span across a variety of families including the blood group antigens (A, B and O), core structures (Types 1, 2 and 4), fucosylated oligosaccharides (core and lacto-series), sialylated oligosaccharides (Types 1 and 2), Lewis antigens, GPI-anchors and globosides. A complementary set of about 100 glycan determinants occurring in glycoproteins and glycosaminoglycans has also been structurally characterized using molecular mechanics-based computation. The experimental and computational data generated are organized in two relational databases that can be queried by the user through a user-friendly search engine. The NMR ((1)H and (13)C, COSY, TOCSY, HMQC, HMBC correlation) spectra and 3D structures are available for visualization and download in commonly used structure formats. Emphasis has been given to the use of a common nomenclature for the structural encoding of the carbohydrates and each glycan molecule is described by four different types of representations in order to cope with the different usages in chemistry and biology. These web-based databases were developed with non-proprietary software and are open access for the scientific community available at http://glyco3d.cermav.cnrs.fr.

Informatics tools to advance the biology of glycosaminoglycans and proteoglycans

Glycomics researchers have identified the need for integrated database systems for collecting glycomics information in a consistent format. The goal is to create a resource for knowledge discovery and dissemination to wider research communities. This has the potential to extend the research community to include biologists, clinicians, chemists, and computer scientists. This chapter discusses the technology and approach needed to create integrated data resources to empower the broader community to leverage extant glycomics data. The focus is on glycosaminoglycan (GAGs) and proteoglycan research, but the approach can be generalized. The methods described span the development of glycomics standards from CarbBank to Glyco Connection Tables. The existence of integrated data sets provides a foundation for novel methods of analysis such as machine learning for knowledge discovery. The implications of predictive analysis are examined in relation to disease biomarker to expand the target audience of GAG and proteoglycan research.

Glyco3D: a portal for structural glycosciences

The present work describes, in a detailed way, a family of databases covering the three-dimensional features of monosaccharides, disaccharides, oligosaccharides, polysaccharides, glycosyltransferases, lectins, monoclonal antibodies against carbohydrates, and glycosaminoglycan-binding proteins. These databases have been developed with non-proprietary software, and they are open freely to the scientific community. They are accessible through the common portal called "Glyco3D" http://www.glyco3d.cermav.cnrs.fr. The databases are accompanied by a user-friendly graphical user interface (GUI) which offers several search options. All three-dimensional structures are available for visual consultations (with basic measurements possibilities) and can be downloaded in commonly used formats for further uses.

Advances in LC-MS/MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N- and O-glycoproteome

Site-specific structural characterization of glycoproteins is important for understanding the exact functional relevance of protein glycosylation. Resulting partly from the multiple layers of structural complexity of the attached glycans, the system-wide site-specific characterization of protein glycosylation, defined as glycoproteomics, is still far from trivial leaving the N- and O-linked glycoproteomes significantly under-defined. However, recent years have seen significant advances in glycoproteomics driven, in part, by the developments of dedicated workflows and efficient sample preparation, including glycopeptide enrichment and prefractionation. In addition, glycoproteomics has benefitted from the continuous performance enhancement and more intelligent use of liquid chromatography and tandem mass spectrometry (LC-MS/MS) instrumentation and a wider selection of specialized software tackling the unique challenges of glycoproteomics data. Together these advances promise more streamlined N- and O-linked glycoproteome analysis. Tangible examples include system-wide glycoproteomics studies detecting thousands of intact glycopeptides from hundreds of glycoproteins from diverse biological samples. With a strict focus on the system-wide site-specific analysis of protein N- and O-linked glycosylation, we review the recent advances in LC-MS/MS based glycoproteomics. The review opens with a more general discussion of experimental designs in glycoproteomics and sample preparation prior to LC-MS/MS based data acquisition. Although many challenges still remain, it becomes clear that glycoproteomics, one of the last frontiers in proteomics, is gradually maturing enabling a wider spectrum of researchers to access this new emerging research discipline. The next milestone in analytical glycobiology is being reached allowing the glycoscientist to address the functional importance of protein glycosylation in a system-wide yet protein-specific manner.

Conformational characterization of ipomotaosides and their recognition by COX-1 and 2

The aerial parts of Ipomoea batatas are described herein to produce four new resin glycosides, designated as ipomotaosides A, B, C, and D. Ipomotaoside A was found to present inhibitory activity on both cyclooxygenases. However, the conformational elucidation of these molecules may be difficult due to their high flexibility. In this context, the current work presents a conformational characterization of ipomotaosides A-D in aqueous and nonaqueous solvents. The employed protocol includes metadynamics evaluation and unrestrained molecular dynamics simulations (MD). The obtained data provided structural models for the ipomotaosides in good agreement with previous ROESY distances measured in pyridine. Accordingly, the most abundant conformation of ipomotaoside A in solution was employed in flexible docking studies, providing a structural basis for the compound's inhibition of COX enzymes. The so-obtained complex supports resin glycosides' role as original scaffolds for future studies, aiming at structural optimization and development of potential new anti-inflammatory agents.

Protein glycosylation in diverse cell systems: implications for modification and analysis of recombinant proteins

A major challenge for the biotechnology industry is to engineer the glycosylation pathways of expression systems to synthesize recombinant proteins with human glycosylation. Inappropriate glycosylation can result in reduced activity, limited half-life in circulation and unwanted immunogenicity. In this review, the complexities of glycosylation in human cells are explained and compared with glycosylation in bacteria, yeasts, fungi, insects, plants and nonhuman mammalian species. Key advances in the engineering of the glycosylation of expression systems are highlighted. Advances in the challenging and technically complex field of glycan analysis are also described. The emergence of a new generation of expression systems with sophisticated engineering for humanized glycosylation of glycoproteins appears to be on the horizon.

Unrestrained conformational characterization of Stenocereus eruca saponins in aqueous and nonaqueous solvents

Saponins are secondary metabolites that have a plethora of biological activities. However, the absence of knowledge of their 3D structures is a major drawback for structural-based strategies in medicinal chemistry. To address this problem, the current work presents structural models of Stenocereus eruca saponins, named erucasaponin A and stellatoside B. These compounds were constructed on the basis of a combination of unrestrained molecular dynamics (MD) simulations and NOESY data, in both pyridine and water. The models obtained in this way offer a robust description of the saponin dynamics in solution and support the use of submicrosecond MD simulations in describing and predicting glycoconjugate conformations.

The use of glycoinformatics in glycochemistry

Glycoinformatics is a small but growing branch of bioinformatics and chemoinformatics. Various resources are now available that can be of use to glycobiologists, but also to chemists who work on the synthesis or analysis of carbohydrates. This article gives an overview of existing glyco-specific databases and tools, with a focus on their application to glycochemistry: Databases can provide information on candidate glycan structures for synthesis, or on glyco-enzymes that can be used to synthesize carbohydrates. Statistical analyses of glycan databases help to plan glycan synthesis experiments. 3D-Structural data of protein-carbohydrate complexes are used in targeted drug design, and tools to support glycan structure analysis aid with quality control. Specific problems of glycoinformatics compared to bioinformatics for genomics or proteomics, especially concerning integration and long-term maintenance of the existing glycan databases, are also discussed.

Harnessing glycomics technologies: integrating structure with function for glycan characterization

Glycans, or complex carbohydrates, are a ubiquitous class of biological molecule which impinge on a variety of physiological processes ranging from signal transduction to tissue development and microbial pathogenesis. In comparison to DNA and proteins, glycans present unique challenges to the study of their structure and function owing to their complex and heterogeneous structures and the dominant role played by multivalency in their sequence-specific biological interactions. Arising from these challenges, there is a need to integrate information from multiple complementary methods to decode structure-function relationships. Focusing on acidic glycans, we describe here key glycomics technologies for characterizing their structural attributes, including linkage, modifications, and topology, as well as for elucidating their role in biological processes. Two cases studies, one involving sialylated branched glycans and the other sulfated glycosaminoglycans, are used to highlight how integration of orthogonal information from diverse datasets enables rapid convergence of glycan characterization for development of robust structure-function relationships.

Structure elucidation of native N- and O-linked glycans by tandem mass spectrometry (tutorial)

Oligosaccharides play important roles in many biological processes. However, the structural elucidation of oligosaccharides remains a major challenge due to the complexities of their structures. Mass spectrometry provides a powerful method for determining oligosaccharide composition. Tandem mass spectrometry (MS) provides structural information with high sensitivity. Oligosaccharide structures differ from other polymers such as peptides because of the large number of linkage combinations and branching. This complexity makes the analysis of oligosaccharide unique from that of peptides. This tutorial addresses the issue of spectral interpretation of tandem MS under conditions of collision-induced dissociation (CID) and infrared multiphoton dissociation (IRMPD). The proper interpretation of tandem MS data can provide important structural information on different types of oligosaccharides including O- and N-linked.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: an update for the period 2005-2006

This review is the fourth update of the original review, published in 1999, on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2006. The review covers fundamental studies, fragmentation of carbohydrate ions, method developments, and applications of the technique to the analysis of different types of carbohydrate. Specific compound classes that are covered include carbohydrate polymers from plants, N- and O-linked glycans from glycoproteins, glycated proteins, glycolipids from bacteria, glycosides, and various other natural products. There is a short section on the use of MALDI-TOF mass spectrometry for the study of enzymes involved in glycan processing, a section on industrial processes, particularly the development of biopharmaceuticals and a section on the use of MALDI-MS to monitor products of chemical synthesis of carbohydrates. Large carbohydrate-protein complexes and glycodendrimers are highlighted in this final section.

A reoptimized GROMOS force field for hexopyranose-based carbohydrates accounting for the relative free energies of ring conformers, anomers, epimers, hydroxymethyl rotamers, and glycosidic linkage conformers

This article presents a reoptimization of the GROMOS 53A6 force field for hexopyranose-based carbohydrates (nearly equivalent to 45A4 for pure carbohydrate systems) into a new version 56A(CARBO) (nearly equivalent to 53A6 for non-carbohydrate systems). This reoptimization was found necessary to repair a number of shortcomings of the 53A6 (45A4) parameter set and to extend the scope of the force field to properties that had not been included previously into the parameterization procedure. The new 56A(CARBO) force field is characterized by: (i) the formulation of systematic build-up rules for the automatic generation of force-field topologies over a large class of compounds including (but not restricted to) unfunctionalized polyhexopyranoses with arbritrary connectivities; (ii) the systematic use of enhanced sampling methods for inclusion of experimental thermodynamic data concerning slow or unphysical processes into the parameterization procedure; and (iii) an extensive validation against available experimental data in solution and, to a limited extent, theoretical (quantum-mechanical) data in the gas phase. At present, the 56A(CARBO) force field is restricted to compounds of the elements C, O, and H presenting single bonds only, no oxygen functions other than alcohol, ether, hemiacetal, or acetal, and no cyclic segments other than six-membered rings (separated by at least one intermediate atom). After calibration, this force field is shown to reproduce well the relative free energies of ring conformers, anomers, epimers, hydroxymethyl rotamers, and glycosidic linkage conformers. As a result, the 56A(CARBO) force field should be suitable for: (i) the characterization of the dynamics of pyranose ring conformational transitions (in simulations on the microsecond timescale); (ii) the investigation of systems where alternative ring conformations become significantly populated; (iii) the investigation of anomerization or epimerization in terms of free-energy differences; and (iv) the design of simulation approaches accelerating the anomerization process along an unphysical pathway.

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein-carbohydrate interaction are reviewed.

GROMOS96 43a1 performance in predicting oligosaccharide conformational ensembles within glycoproteins

In previous work [Pol-Fachin, L.; Fernandes, C. L.; Verli, H.; Carbohydr. Res.2009, 344, 491-500], we had demonstrated that GROMOS96 43a1 force field and Löwdin HF/6-31G * *-derived atomic charges, adequately represent a glycoprotein's conformational ensemble in aqueous solutions, taking as the starting geometries NMR-determined structures. Based on such data, the present work intends to evaluate the use of the main solution conformations of isolated disaccharides, to build the carbohydrate moiety of glycoproteins, for which no previous experimental information is available. The observed results suggested that the entire glycoprotein scaffold appears unable to promote major modifications in the conformational behavior of glycosidic linkages. Additionally, when compared to energy contour plots, the results support the use of solution ensembles, to refine vacuum conformations of carbohydrate databases in the assembling of glycoproteins 3D structures. Finally, such approach is applied to build a full glycosylated model for COX-1 and COX-2 enzymes.

Shape: automatic conformation prediction of carbohydrates using a genetic algorithm

Background

Detailed experimental three dimensional structures of carbohydrates are often difficult to acquire. Molecular modelling and computational conformation prediction are therefore commonly used tools for three dimensional structure studies. Modelling procedures generally require significant training and computing resources, which is often impractical for most experimental chemists and biologists. Shape has been developed to improve the availability of modelling in this field.

Results

The Shape software package has been developed for simplicity of use and conformation prediction performance. A trivial user interface coupled to an efficient genetic algorithm conformation search makes it a powerful tool for automated modelling. Carbohydrates up to a few hundred atoms in size can be investigated on common computer hardware. It has been shown to perform well for the prediction of over four hundred bioactive oligosaccharides, as well as compare favourably with previously published studies on carbohydrate conformation prediction.

Conclusion

The Shape fully automated conformation prediction can be used by scientists who lack significant modelling training, and performs well on computing hardware such as laptops and desktops. It can also be deployed on computer clusters for increased capacity. The prediction accuracy under the default settings is good, as it agrees well with experimental data and previously published conformation prediction studies. This software is available both as open source and under commercial licenses.

Determination of glycosylation sites and site-specific heterogeneity in glycoproteins

Glycosylation is one of the most common post-translational modifications (PTMs) of proteins. At least 50% of human proteins are glycosylated with some estimates being as high as 70%. Glycoprotein analysis requires determining both the sites of glycosylation as well as the glycan structures associated with each site. Recent advances have led to the development of new analytical methods that employ mass spectrometry extensively making it possible to obtain the glycosylation site and the site microheterogeneity. These tools will be important for the eventual development of glycoproteomics.

Glycosaminoglycan characterization methodologies: probing biomolecular interactions

Interactions between glycans and proteins are central to many of the regulatory processes within biology. The development of analytical methodologies that enable structural characterization of glycosaminoglycan oligosaccharides has fostered improved understanding of the specificity of these biomolecular interactions. This facilitates an appreciation in understanding how changes in GAG structure can regulate physiology as well as pathology. While there are various techniques for studying the interaction of GAGs with proteins, in this chapter we focus on two approaches. First, an integrated analytical methodology, surface non-covalent affinity mass spectrometry (SNA-MS), is described to isolate, enrich, and sequence tissue-derived GAGs that bind to specific proteins. The broad applicability of this powerful platform offers an insight into how changes in cell-surface and extracellular GAG composition and sequence influences the ability of cells and tissues to dynamically alter responses to signaling molecules. Thus, this approach provides a window into understanding how changes at a molecular level manifest with respect to cellular phenotype. Second, surface plasmon resonance, or SPR, represents an additional platform for the study of protein-polysaccharide interaction, specifically for measuring the binding between GAG chains and proteins.

An alpha-numeric code for representing N-linked glycan structures in secreted glycoproteins

Advances in high-throughput techniques have led to the creation of increasing amounts of glycome data. The storage and analysis of this data would benefit greatly from a compact notation for describing glycan structures that can be easily stored and interpreted by computers. Towards this end, we propose a fixed-length alpha-numeric code for representing N-linked glycan structures commonly found in secreted glycoproteins from mammalian cell cultures. This code, GlycoDigit, employs a pre-assigned alpha-numeric index to represent the monosaccharides attached in different branches to the core glycan structure. The present branch-centric representation allows us to visualize the structure while the numerical nature of the code makes it machine readable. In addition, a difference operator can be defined to quantitatively differentiate between glycan structures for further analysis. The usefulness and applicability of GlycoDigit were demonstrated by constructing and visualizing an N-linked glycosylation network.

Linkage position and residue identification of disaccharides by tandem mass spectrometry and linear discriminant analysis

The discrimination of isomeric disaccharides with different linkage types and different monosaccharide residues--glucose (Glc), galactose (Gal), and mannose (Man) at the non-reducing end--was investigated with tandem mass spectrometry (MS/MS) and linear discriminant analysis (LDA). Conventional matrix-assisted laser desorption/ionization (MALDI)-MS has strong interference peaks from matrix ions in the low mass region (<500 Da). This greatly limits the application of MALDI-MS for the analysis of small molecules such as saccharides. We solved this problem by using LDI with acidic fullerene matrix, which gives a very clean background in the low-mass region. Disaccharides with different linkage types give different tandem mass spectral profiles from various cross-ring fragmentation pathways. Disaccharides with the same linkage type but with three different kinds of monosaccharide residues bear the same fragmentation profiles. However, the relative ratios of the fragment ion intensities were found to be distinctly different among the three disaccharide isomers. By employing statistical tools such as LDA to classify the tandem mass spectra, disaccharide isomers with either different linkages or different monosaccharide residues were successfully classified.

Conformation, dynamics, solvation and relative stabilities of selected β-hexopyranoses in water: a molecular dynamics study with the gromos 45A4 force field

The present article reports long timescale (200 ns) simulations of four beta-D-hexopyranoses (beta-D-glucose, beta-D-mannose, beta-D-galactose and beta-D-talose) using explicit-solvent (water) molecular dynamics and vacuum stochastic dynamics simulations together with the GROMOS 45A4 force field. Free-energy and solvation free-energy differences between the four compounds are also calculated using thermodynamic integration. Along with previous experimental findings, the present results suggest that the formation of intramolecular hydrogen-bonds in water is an 'opportunistic' consequence of the close proximity of hydrogen-bonding groups, rather than a major conformational driving force promoting this proximity. In particular, the conformational preferences of the hydroxymethyl group in aqueous environment appear to be dominated by 1,3-syn-diaxial repulsion, with gauche and solvation effects being secondary, and intramolecular hydrogen-bonding essentially negligible. The rotational dynamics of the exocyclic hydroxyl groups, which cannot be probed experimentally, is found to be rapid (10-100 ps timescale) and correlated (flip-flop hydrogen-bonds interconverting preferentially through an asynchronous disrotatory pathway). Structured solvent environments are observed between the ring and lactol oxygen atoms, as well as between the 4-OH and hydroxymethyl groups. The calculated stability differences between the four compounds are dominated by intramolecular effects, while the corresponding differences in solvation free energies are small. An inversion of the stereochemistry at either C(2) or C(4) from equatorial to axial is associated with a raise in free energy. Finally, the particularly low hydrophilicity of beta-D-talose appears to be caused by the formation of a high-occurrence hydrogen-bonded bridge between the 1,3-syn-diaxial 2-OH and 4-OH groups. Overall, good agreement is found with available experimental and theoretical data on the structural, dynamical, solvation and energetic properties of these compounds. However, this detailed comparison also reveals some discrepancies, suggesting the need (and providing a solid basis) for further refinement.

GlycoPep DB: a tool for glycopeptide analysis using a "Smart Search"

Mass spectrometry is emerging as a versatile analytical tool for profiling glycan and glycopeptide structures. While the interpretation of MS data remains a challenging and difficult task, substantial efforts have been made to develop informatics tools to alleviate MS data interpretation. Here, we present a web-based tool, GlycoPep DB, designed to facilitate compositional assignment for glycopeptides by comparing experimentally measured masses to all calculated glycopeptide masses from a carbohydrate database with N-linked glycans. GlycoPep DB is an advance over current tools to assign N-linked glycans because it uses a concept of "smart searching", where only biologically relevant carbohydrate compositions are searched, when matching carbohydrate compositions with the MS data making glycopeptide compositional assignment more efficient. This is in contrast to currently used tools, where many implausible glycan structures are present in the search output, but fewer biologically relevant glycan motifs are predicted. The utility of GlycoPep DB is illustrated in the analysis of glycopeptides derived from a proteolytic digest of follicle stimulating hormone.

GLYCOMICS APPROACH TO STRUCTURE-FUNCTION RELATIONSHIPS OF GLYCOSAMINOGLYCANS

Extracellular modulation of phenotype is an emerging paradigm in this current postgenomics age of molecular and cell biology. Glycosaminoglycans (GAGs) are primary components of the cell surface and the cell-extracellular matrix (ECM) interface. Advances in the technology to analyze GAGs and in whole-organism genetics have led to a dramatic increase in the known important biological role of these complex polysaccharides. Owing to their ubiquitous distribution at the cell-ECM interface, GAGs interact with numerous proteins and modulate their activity, thus impinging on fundamental biological processes such as cell growth and development. Many recent reviews have captured important aspects of GAG structure and biosynthesis, GAG-protein interactions, and GAG biology. GAG research is currently at a stage where there is a need for an integrated systems or glycomics approach, which involves an integration of all of the above concepts to define their structure-function relationships. Focusing on heparin/heparan (HSGAGs) and chondroitin/dermatan sulfate (CSGAGs), this review highlights the important aspects of GAGs and summarizes these aspects in the context of taking a glycomics approach that integrates the different technologies to define structure-function relationships of GAGs.

The role of informatics in glycobiology research with special emphasis on automatic interpretation of MS spectra

This paper reviews the current status of bioinformatics applications and databases in glycobiology, which are based on bioinformatics approaches as well as informatics for glycobiology where an explicit encoding of glycan structures is required. The availability of the complete sequence of the human genome has accelerated the systematic identification of so far unidentified glycogenes considerably in many areas of glycobiology using well-established bioinfomatics tools. Although there has been an immense development of new glyco-related data collections as well as informatics tools and several efforts have been started to cross-link and reference the various data deposited in distributed databases, informatics for glycobiology and glycomics is still poorly developed compared to the genomics and proteomics area. The development of algorithms for the automatic interpretation of MS spectra - currently, a severe bottleneck, which hampers the rapid and reliable interpretation of MS data in high-throughput glycomics projects - is reviewed. A comprehensive list of web resources is given. Several lines of progression are discussed. There is an urgent need for the development of decentralised input facilities of experimentally determined glycan structures. Simultaneously, agreements of standards for the structural description of glycans as well as formats for the related data have to be established. The integration of glycomics with genomics/proteomics has to increase.