Predicting the Structures of Glycans, Glycoproteins, and Their Complexes

CryoSeek II: Cryo-EM analysis of glycofibrils from freshwater reveals well-structured glycans coating linear tetrapeptide repeats

Despite the recent breakthrough in structure determination and prediction of proteins, the structural investigation of carbohydrates remains a challenge. Here, we report the cryo-EM analysis of a glycofibril found in the freshwater in the Tsinghua Lotus Pond. The fibril, which we name TLP-4, is made of a linear chain of tetrapeptide repeats coated with >4 nm thick glycans. In each repeat, two glycans are O-linked to a 3,4-dihydroxyproline and another glycan attaches to the adjacent Ser or Thr. The fibril structure is entirely maintained through glycan packing. Bioinformatic analysis confirms the conservation of the TLP-4 repeats across species, suggesting the existence of a large number of glycofibrils to be discovered. Our findings not only provide valuable insights into the structural roles of glycans in bio-assemblies but also demonstrate the potential of our recently formulated research strategy of CryoSeek to find bioentities and establish prototypes for structural studies of carbohydrates.

Molecular dynamics modeling of different conformations of beta-glucan, molecular docking with dectin-1, and the effects on macrophages

This study investigated β-glucan with diverse conformations by using molecular dynamics simulations to analyze their conformational transitions in water. Stable conformations were docked with the Dectin-1 protein to evaluate key metrics such as favorable conformations, root-mean-square deviation, hydrogen bond interactions, and their effects on macrophage activity. Results revealed that single-chain β-1,3-glucan with a degree of polymerization (DP) of 24 forms aggregates in water, while triple-chain β-1,3-glucan with a DP of 6 tends to form double helices. Other models exhibited single-helical or entangled-helical structures, with β-1,3/1,4-glucans favoring compact triple helices. The β-1,3 glycosidic bond promotes compact helical structures, while the β-1,4 bond hinders folding, increasing rigidity. Branching via β-1,6 glycosidic bonds introduces flexibility and enhances hydrogen bonding with water, although longer branches may cause localized aggregation. Molecular docking suggests that Dectin-1's recognition sites are predominantly hydrophobic. Lower polymerization models improve binding affinity through structural complexity, whereas higher polymerization models enhance binding via helical characteristics and larger contact areas. The study provides a comprehensive perspective on Dectin-1's differential recognition of β-glucans.

Synthetic chitin oligosaccharide nanocrystals and their higher-order assemblies

Self-assembly is a powerful strategy for creating complex architectures and elucidating the aggregation behaviors of biopolymers. Herein, we investigate the hierarchical assembly of chitin using a bottom-up approach based on synthetic oligosaccharides. We discovered that chitin oligosaccharides self-assemble into platelets, which then form higher-order structures. Subtle changes in experimental conditions drastically altered the self-assembly results, generating a wide array of higher-order architectures. Through systematic investigations employing transmission electron microscopy (TEM), photoinduced force microscopy (PiFM), and atomic force microscopy (AFM), we uncovered the role of water in shaping the different morphologies. This finding gave us the tools to promote the formation of chiral, uniform chitin oligosaccharide bundles. Our work not only sheds light on the fundamental aspects of chitin organization, but also suggests strategies for designing carbohydrate-based materials with tunable structures and properties.

Role of van der Waals, Electrostatic, and Hydrogen-Bond Interactions for the Relative Stability of Cellulose Iβ and II Crystals

Naturally occurring cellulose Iβ with its characteristic parallel orientation of cellulose chains is less stable than cellulose II, in which neighboring pairs of chains are oriented antiparallel to each other. While the distinct hydrogen-bond patterns of these two cellulose crystal forms are well established, the energetic role of the hydrogen bonds for crystal stability, in comparison to the van der Waals (vdW) and overall electrostatic interactions in the crystals, is a matter of current debate. In this article, we investigate the relative stability of celluloses Iβ and II in energy minimizations with classical force fields. We find that the larger stability of cellulose II results from clearly stronger electrostatic interchain energies that are only partially compensated for by stronger vdW interchain energies in cellulose Iβ. In addition, we show that a multipole description of hydrogen bonds that includes the COH groups of donor and acceptor oxygen atoms leads to consistent interchain hydrogen-bond energies that account for roughly 70% and 75% of the interchain electrostatics in celluloses Iβ and II, respectively.

Scanning Probe Microscopy Characterization of Biomolecules enabled by Mass-Selective, Soft-landing Electrospray Ion Beam Deposition

Scanning probe microscopy (SPM), in particular at low temperature (LT) under ultra-high vacuum (UHV) conditions, offers the possibility of real-space imaging with resolution reaching the atomic level. However, its potential for the analysis of complex biological molecules has been hampered by requirements imposed by sample preparation. Transferring molecules onto surfaces in UHV is typically accomplished by thermal sublimation in vacuum. This approach however is limited by the thermal stability of the molecules, i. e. not possible for biological molecules with low vapour pressure. Bypassing this limitation, electrospray ionisation offers an alternative method to transfer molecules from solution to the gas-phase as intact molecular ions. In soft-landing electrospray ion beam deposition (ESIBD), these molecular ions are subsequently mass-selected and gently landed on surfaces which permits large and thermally fragile molecules to be analyzed by LT-UHV SPM. In this concept, we discuss how ESIBD+SPM prepares samples of complex biological molecules at a surface, offering controls of the molecular structural integrity, three-dimensional shape, and purity. These achievements unlock the analytical potential of SPM which is showcased by imaging proteins, peptides, DNA, glycans, and conjugates of these molecules, revealing details of their connectivity, conformation, and interaction that could not be accessed by any other technique.

NMR investigations of glycan conformation, dynamics, and interactions

Glycans are ubiquitous in nature, decorating our cells and serving as the initial points of contact with any visiting entities. These glycan interactions are fundamental to host-pathogen recognition and are related to various diseases, including inflammation and cancer. Therefore, understanding the conformations and dynamics of glycans, as well as the key features that regulate their interactions with proteins, is crucial for designing new therapeutics. Due to the intrinsic flexibility of glycans, NMR is an essential tool for unravelling these properties. In this review, we describe the key NMR parameters that can be extracted from the different experiments, and which allow us to deduce the necessary geometry and molecular motion information, with a special emphasis on assessing the internal motions of the glycosidic linkages. We specifically address the NMR peculiarities of various natural glycans, from histo-blood group antigens to glycosaminoglycans, and also consider the special characteristics of their synthetic analogues (glycomimetics). Finally, we discuss the application of NMR protocols to study glycan-related molecular recognition events, both from the carbohydrate and receptor perspectives, including the use of stable isotopes and paramagnetic NMR methods to overcome the inherent degeneracy of glycan chemical shifts.

Restoring protein glycosylation with GlycoShape

Despite ground-breaking innovations in experimental structural biology and protein structure prediction techniques, capturing the structure of the glycans that functionalize proteins remains a challenge. Here we introduce GlycoShape ( https://glycoshape.org ), an open-access glycan structure database and toolbox designed to restore glycoproteins to their native and functional form in seconds. The GlycoShape database counts over 500 unique glycans so far, covering the human glycome and augmented by elements from a wide range of organisms, obtained from 1 ms of cumulative sampling from molecular dynamics simulations. These structures can be linked to proteins with a robust algorithm named Re-Glyco, directly compatible with structural data in open-access repositories, such as the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and AlphaFold Protein Structure Database, or own. The quality, performance and broad applicability of GlycoShape is demonstrated by its ability to predict N-glycosylation occupancy, scoring a 93% agreement with experiment, based on screening all proteins in the PDB with a corresponding glycoproteomics profile, for a total of 4,259 N-glycosylation sequons.

Refinement of the Drude Polarizable Force Field for Hexose Monosaccharides: Capturing Ring Conformational Dynamics with Enhanced Accuracy

We present a revised version of the Drude polarizable carbohydrate force field (FF), focusing on refining the ring and exocyclic torsional parameters for hexopyranose monosaccharides. This refinement addresses the previously observed discrepancies between calculated and experimental NMR 3J coupling values, particularly in describing ring dynamics and exocyclic rotamer populations within major hexose monosaccharides and their anomers. Specifically, α-MAN, β-MAN, α-GLC, β-GLC, α-GAL, β-GAL, α-ALT, β-ALT, α-IDO, and β-IDO were targeted for optimization. The optimization process involved potential energy scans (PES) of the ring and exocyclic dihedral angles computed using quantum mechanical (QM) methods. The target data for the reoptimization included PES of the inner ring dihedrals (C1-C2-C3-C4, C2-C3-C4-C5, C5-O5-C1-C2, C4-C5-O5-C1, O5-C1-C2-C3, C3-C4-C5-O5) and the exocyclic torsions, other than the pseudo ring dihedrals (O1-C1-O5-C5, O2-C2-C1-O5, and O4-C4-C5-O5) and hydroxyl torsions used in the previous parametrization efforts. These parameters, in conjunction with previously developed Drude parameters for hexopyranose monosaccharides, were validated against experimental observations, including NMR data and conformational energetics, in aqueous environments. The resulting polarizable model is shown to be in good agreement with a range of QM data, experimental NMR data, and conformational energetics of monosaccharides in aqueous solutions. This offers a significant improvement of the Drude carbohydrate force field, wherein the refinement enhances the accuracy of accessing the conformational dynamics of carbohydrates in biomolecular simulations.

Modeling Protein-Glycan Interactions with HADDOCK

The term glycan refers to a broad category of molecules composed of monosaccharide units linked to each other in a variety of ways, whose structural diversity is related to different functions in living organisms. Among others, glycans are recognized by proteins with the aim of carrying information and for signaling purposes. Determining the three-dimensional structures of protein-glycan complexes is essential both for the understanding of the mechanisms glycans are involved in and for applications such as drug design. In this context, molecular docking approaches are of undoubted importance as complementary approaches to experiments. In this study, we show how high ambiguity-driven DOCKing (HADDOCK) can be efficiently used for the prediction of protein-glycan complexes. Using a benchmark of 89 complexes, starting from their bound or unbound forms, and assuming some knowledge of the binding site on the protein, our protocol reaches a 70% and 40% top 5 success rate on bound and unbound data sets, respectively. We show that the main limiting factor is related to the complexity of the glycan to be modeled and the associated conformational flexibility.

Enzyme-Triggered Assembly of Glycan Nanomaterials

A comprehensive molecular understanding of carbohydrate aggregation is key to optimize carbohydrate utilization and to engineer bioinspired analogues with tailored shapes and properties. However, the lack of well-defined synthetic standards has substantially hampered advances in this field. Herein, we employ a phosphorylation-assisted strategy to synthesize previously inaccessible long oligomers of cellulose, chitin, and xylan. These oligomers were subjected to enzyme-triggered assembly (ETA) for the on-demand formation of well-defined carbohydrate nanomaterials, including elongated platelets, helical bundles, and hexagonal particles. Cryo-electron microscopy and electron diffraction analysis provided molecular insights into the aggregation behavior of these oligosaccharides, establishing a direct connection between the resulting morphologies and the oligosaccharide primary sequence. Our findings demonstrate that ETA is a powerful approach to elucidate the intrinsic aggregation behavior of carbohydrates in nature. Moreover, the ability to access a diverse array of morphologies, expanded with a non-natural sequence, underscores the potential of ETA, coupled with sequence design, as a robust tool for accessing programmable glycan architectures.

Insights into the role of glycosyltransferase in the targeted treatment of gastric cancer

Gastric cancer is a remarkably heterogeneous tumor. Despite some advances in the diagnosis and treatment of gastric cancer in recent years, the precise treatment and curative outcomes remain unsatisfactory. Poor prognosis continues to pose a major challenge in gastric cancer. Therefore, it is imperative to identify effective targets to improve the treatment and prognosis of gastric cancer patients. It should be noted that glycosylation, a novel form of posttranslational modification, is a process capable of regulating protein function and influencing cellular activities. Currently, numerous studies have shown that glycosylation plays vital roles in the occurrence and progression of gastric cancer. As crucial enzymes that regulate glycan synthesis in glycosylation processes, glycosyltransferases are potential targets for treating GC. Hence, investigating the regulation of glycosyltransferases and the expression of associated proteins in gastric cancer cells is highly important. In this review, the related glycosyltransferases and their related signaling pathways in gastric cancer, as well as the existing inhibitors of glycosyltransferases, provide more possibilities for targeted therapies for gastric cancer.

Cross-Species Insights into PR Proteins: A Comprehensive Study of Arabidopsis thaliana, Solanum lycopersicum, and Solanum tuberosum

This study provides a comprehensive analysis of pathogenesis-related (PR) proteins, focusing on PR1, PR5, and PR10, in three plant species: Arabidopsis thaliana (At), Solanum lycopersicum (Sl), and Solanum tuberosum (St). We investigated various physico-chemical properties, including protein length, molecular weight, isoelectric point (pI), hydrophobicity, and structural characteristics, such as RMSD, using state-of-the-art tools like AlphaFold and PyMOL. Our analysis found that the SlPR10-StPR10 protein pair had the highest sequence identity (80.00%), lowest RMSD value (0.307 Å), and a high number of overlapping residues (160) among all other protein pairs, indicating their remarkable similarity. Additionally, we used bioinformatics tools such as Cello, Euk-mPLoc 2.0, and Wolfpsort to predict subcellular localization, with AtPR1, AtPR5, and SlPR5 proteins predicted to be located in the extracellular space in both Arabidopsis and S. lycopersicum, while AtPR10 was predicted to be located in the cytoplasm. This comprehensive analysis, including the use of cutting-edge structural prediction and subcellular localization tools, enhances our understanding of the structural, functional, and localization aspects of PR proteins, shedding light on their roles in plant defense mechanisms across different plant species.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12088-024-01343-1.

Unveiling crucial amino acids in the carbohydrate recognition domain of a viral protein through a structural bioinformatic approach

Carbohydrate binding modules (CBMs) are protein domains that typically reside near catalytic domains, increasing substrate-protein proximity by constraining the conformational space of carbohydrates. Due to the flexibility and variability of glycans, the molecular details of how these protein regions recognize their target molecules are not always fully understood. Computational methods, including molecular docking and molecular dynamics simulations, have been employed to investigate lectin-carbohydrate interactions. In this study, we introduce a novel approach that integrates multiple computational techniques to identify the critical amino acids involved in the interaction between a CBM located at the tip of bacteriophage J-1's tail and its carbohydrate counterparts. Our results highlight three amino acids that play a significant role in binding, a finding we confirmed through in vitro experiments. By presenting this approach, we offer an intriguing alternative for pinpointing amino acids that contribute to protein-sugar interactions, leading to a more thorough comprehension of the molecular determinants of protein-carbohydrate interactions.

Deciphering disease through glycan codes: leveraging lectin microarrays for clinical insights

Glycosylation, a crucial posttranslational modification, plays a significant role in numerous physiological and pathological processes. Lectin microarrays, which leverage the high specificity of lectins for sugar binding, are ideally suited for profiling the glycan spectra of diverse and complex biological samples. In this review, we explore the evolution of lectin detection technologies, as well as the applications and challenges of lectin microarrays in analyzing the glycome profiles of various clinical samples, including serum, saliva, tissues, sperm, and urine. This review not only emphasizes significant advancements in the high-throughput analysis of polysaccharides but also provides insight into the potential of lectin microarrays for diagnosing and managing diseases such as tumors, autoimmune diseases, and chronic inflammation. We aim to provide a clear, concise, and comprehensive overview of the use of lectin microarrays in clinical settings, thereby assisting researchers in conducting clinical studies in glycobiology.

The Conformation of Glycosidic Linkages According to Various Force Fields: Monte Carlo Modeling of Polysaccharides Based on Extrapolation of Short-Chain Properties

The conformational features of the glycosidic linkage are the most important variable to consider when studying di-, oligo-, and polysaccharide molecules using molecular dynamics (MD) simulations. The accuracy of the theoretical model describing this degree of freedom influences the quality of the results obtained from MD calculations based on this model. This article focuses on the following two issues related to the conformation of the glycosidic linkage. First, we describe the results of a comparative analysis of the predictions of three carbohydrate-dedicated classical force fields for MD simulations, namely, CHARMM, GLYCAM, and GROMOS, in the context of different parameters of structural and energetic nature related to the conformation of selected types of glycosidic linkages, α(1 → 4), β(1 → 3), and β(1 → 4), connecting glucopyranose units. This analysis revealed several differences, mainly concerning the energy levels of the secondary and tertiary conformers and the linkage flexibility within the dominant exo-syn conformation for α(1 → 4) and β(1 → 3) linkages. Some aspects of the comparative analysis also included the newly developed, carbohydrate-dedicated Martini 3 coarse-grained force field. Second, to overcome the time-scale problem associated with sampling slow degrees of freedom in polysaccharide chains during MD simulations, we developed a coarse-grained (CG) model based on the data from MD simulations and designed for Monte Carlo modeling. This model (CG MC) is based on information from simulations of short saccharide chains, effectively sampled in atomistic MD simulations, and is capable of extrapolating local conformational properties to the case of polysaccharides of arbitrary length. The CG MC model has the potential to estimate the conformations of very long polysaccharide chains, taking into account the influence of secondary and tertiary conformations of glycosidic linkages. With respect to the comparative analysis of force fields, the application of CG MC modeling showed that relatively small differences in the predictions of individual force fields with respect to a single glycosidic linkage accumulate when considering their effect on the structure of longer chains, leading to drastically different predictions with respect to parameters describing the polymer conformation, such as the persistence length.

Metal adduction in mass spectrometric analyses of carbohydrates and glycoconjugates

Glycans, carbohydrates, and glycoconjugates are involved in many crucial biological processes, such as disease development, immune responses, and cell-cell recognition. Glycans and carbohydrates are known for the large number of isomeric features associated with their structures, making analysis challenging compared with other biomolecules. Mass spectrometry has become the primary method of structural characterization for carbohydrates, glycans, and glycoconjugates. Metal adduction is especially important for the mass spectrometric analysis of carbohydrates and glycans. Metal-ion adduction to carbohydrates and glycoconjugates affects ion formation and the three-dimensional, gas-phase structures. Herein, we discuss how metal-ion adduction impacts ionization, ion mobility, ion activation and dissociation, and hydrogen/deuterium exchange for carbohydrates and glycoconjugates. We also compare the use of different metals for these various techniques and highlight the value in using metals as charge carriers for these analyses. Finally, we provide recommendations for selecting a metal for analysis of carbohydrate adducts and describe areas for continued research.

Combined experiments and molecular simulations for understanding the thermo-responsive behavior and gelation of methylated glucans with different glycosidic linkages

HYPOTHESIS

Elucidation of the micro-mechanisms of sol-gel transition of gelling glucans with different glycosidic linkages is crucial for understanding their structure-property relationship and for various applications. Glucans with distinct molecular chain structures exhibit unique gelation behaviors. The disparate gelation phenomena observed in two methylated glucans, methylated (1,3)-β-d-glucan of curdlan (MECD) and methylated (1,4)-β-d-glucan of cellulose (MC), notwithstanding their equivalent degrees of substitution, are intricately linked to their unique molecular architectures and interactions between glucan and water.

EXPERIMENTS

Density functional theory and molecular dynamics simulations focused on the electronic property distinctions between MECD and MC, alongside conformational variations during thermal gelation. Inline attenuated total reflection Fourier transform infrared spectroscopy tracked secondary structure alterations in MECD and MC. To corroborate the simulation results, additional analyses including circular dichroism, rheology, and micro-differential scanning calorimetry were performed.

FINDINGS

Despite having similar thermally induced gel networks, MECD and MC display distinct physical gelation patterns and molecular-level conformational changes during gelation. The network of MC gel was formed via a "coil-to-ring" transition, followed by ring stacking. In contrast, the MECD gel comprised compact irregular helices accompanied by notable volume shrinkage. These variations in gelation behavior are ascribed to heightened hydrophobic interactions and diminished hydrogen bonding in both systems upon heating, resulting in gelation. These findings provide valuable insights into the microstructural changes during gelation and the thermo-gelation mechanisms of structurally similar polysaccharides.

Role of N343 glycosylation on the SARS-CoV-2 S RBD structure and co-receptor binding across variants of concern

Glycosylation of the SARS-CoV-2 spike (S) protein represents a key target for viral evolution because it affects both viral evasion and fitness. Successful variations in the glycan shield are difficult to achieve though, as protein glycosylation is also critical to folding and structural stability. Within this framework, the identification of glycosylation sites that are structurally dispensable can provide insight into the evolutionary mechanisms of the shield and inform immune surveillance. In this work, we show through over 45 μs of cumulative sampling from conventional and enhanced molecular dynamics (MD) simulations, how the structure of the immunodominant S receptor binding domain (RBD) is regulated by N-glycosylation at N343 and how this glycan's structural role changes from WHu-1, alpha (B.1.1.7), and beta (B.1.351), to the delta (B.1.617.2), and omicron (BA.1 and BA.2.86) variants. More specifically, we find that the amphipathic nature of the N-glycan is instrumental to preserve the structural integrity of the RBD hydrophobic core and that loss of glycosylation at N343 triggers a specific and consistent conformational change. We show how this change allosterically regulates the conformation of the receptor binding motif (RBM) in the WHu-1, alpha, and beta RBDs, but not in the delta and omicron variants, due to mutations that reinforce the RBD architecture. In support of these findings, we show that the binding of the RBD to monosialylated ganglioside co-receptors is highly dependent on N343 glycosylation in the WHu-1, but not in the delta RBD, and that affinity changes significantly across VoCs. Ultimately, the molecular and functional insight we provide in this work reinforces our understanding of the role of glycosylation in protein structure and function and it also allows us to identify the structural constraints within which the glycosylation site at N343 can become a hotspot for mutations in the SARS-CoV-2 S glycan shield.

Generalized biomolecular modeling and design with RoseTTAFold All-Atom

Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies that contain proteins, nucleic acids, small molecules, metals, and covalent modifications, given their sequences and chemical structures. By fine-tuning on denoising tasks, we developed RFdiffusion All-Atom (RFdiffusionAA), which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we designed and experimentally validated, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light-harvesting molecule bilin.

Metal-Assisted Carbohydrate Assembly

The sequence-controlled assembly of nucleic acids and amino acids into well-defined superstructures constitutes one of the most revolutionary technologies in modern science. The elaboration of such superstructures from carbohydrates, however, remains elusive and largely unexplored on account of their intrinsic constitutional and configurational complexity, not to mention their inherent conformational flexibility. Here, we report the bottom-up assembly of two classes of hierarchical superstructures that are formed from a highly flexible cyclo-oligosaccharide─namely, cyclofructan-6 (CF-6). The formation of coordinative bonds between the oxygen atoms of CF-6 and alkali metal cations (i) locks a myriad of flexible conformations of CF-6 into a few rigid conformations, (ii) bridges adjacent CF-6 ligands, and (iii) gives rise to the multiple-level assembly of three extended frameworks. The hierarchical superstructures present in these frameworks have been shown to modulate their nanomechanical properties. This research highlights the unique opportunities of constructing convoluted superstructures from carbohydrates and should encourage future endeavors in this underinvestigated field of science.

Substituted Oligosaccharides as Protein Mimics: Deep Learning Free Energy Landscapes

Protein-protein complexes power the majority of cellular processes. Interfering with the formation of such complexes using well-designed mimics is a difficult, yet actively pursued, research endeavor. Due to the limited availability of results on the conformational preferences of oligosaccharides compared to polypeptides, the former have been much less explored than the latter as protein mimics, despite interesting ADMET characteristics. In this work, the conformational landscapes of a series of 956 substituted glucopyranose oligomers of lengths 3 to 12 designed as protein interface mimics are revealed using microsecond-time-scale, enhanced-sampling molecular dynamics simulations. Deep convolutional networks are trained on these large conformational ensembles, to predict the stability of longer oligosaccharide structures from those of their constituent trimer motifs. Deep generative adversarial networks are then designed to suggest plausible conformations for oligosaccharide mimics of arbitrary length and substituent sequences that can subsequently be used as input to docking simulations. Analyzing the performance of the neural networks also yields insights into the intricate collective effects that dominate oligosaccharide conformational dynamics.

Towards Biomimetic Recognition of Glycans by Synthetic Receptors

Carbohydrates are abundant in Nature, where they are mostly assembled within glycans as free polysaccharides or conjugated to a variety of biological molecules such as proteins and lipids. Glycans exert several functions, including protein folding, stability, solubility, resistance to proteolysis, intracellular traffic, antigenicity, and recognition by carbohydrate-binding proteins. Interestingly, misregulation of their biosynthesis that leads to changes in glycan structures is frequently recognized as a mark of a disease state. Because of glycan ubiquity, carbohydrate binding agents (CBAs) targeting glycans can lead to a deeper understanding of their function and to the development of new diagnostic and prognostic strategies. Synthetic receptors selectively recognizing specific carbohydrates of biological interest have been developed over the past three decades. In addition to the success obtained in the effective recognition of monosaccharides, synthetic receptors recognizing more complex guests have also been developed, including di- and oligosaccharide fragments of glycans, shedding light on the structural and functional requirements necessary for an effective receptor. In this review, the most relevant achievements in molecular recognition of glycans and their fragments will be summarized, highlighting potentials and future perspectives of glycan-targeting synthetic receptors.

Molecular insights on the coronavirus MERS-CoV interaction with the CD26 receptor

The Middle East respiratory syndrome (MERS) is a severe respiratory disease with high fatality rates, caused by the Middle East respiratory syndrome coronavirus (MERS-CoV). The virus initiates infection by binding to the CD26 receptor (also known as dipeptidyl peptidase 4 or DPP4) via its spike protein. Although the receptor-binding domain (RBD) of the viral spike protein and the complex between RBD and the extracellular domain of CD26 have been studied using X-ray crystallography, conflicting studies exist regarding the importance of certain amino acids outside the resolved RBD-CD26 complex interaction interface. To gain atomic-level knowledge of the RBD-CD26 complex, we employed computational simulations to study the complex's dynamic behavior as it evolves from its crystal structure to a conformation stable in solution. Our study revealed previously unidentified interaction regions and interacting amino acids within the complex, determined a novel comprehensive RBD-binding domain of CD26, and by that expanded the current understanding of its structure. Additionally, we examined the impact of a single amino acid substitution, E513A, on the complex's stability. We discovered that this substitution disrupts the complex through an allosteric domino-like mechanism that affects other residues. Since MERS-CoV is a zoonotic virus, we evaluated its potential risk of human infection via animals, and suggest a low likelihood for possible infection by cats or dogs. The molecular structural information gleaned from our insights into the RBD-CD26 complex pre-dissociative states may be proved useful not only from a mechanistic view but also in assessing inter-species transmission and in developing anti-MERS-CoV antiviral therapeutics.

Glycans modulate lipid binding in Lili-Mip lipocalin protein: insights from molecular simulations and protein network analyses

The unique viviparous Pacific Beetle cockroaches provide nutrition to their embryo by secreting milk proteins Lili-Mip, a lipid-binding glycoprotein that crystallises in-vivo. The resolved in-vivo crystal structure of variably glycosylated Lili-Mip shows a classical Lipocalin fold with an eight-stranded antiparallel beta-barrel enclosing a fatty acid. The availability of physiologically unaltered glycoprotein structure makes Lili-Mip a very attractive model system to investigate the role of glycans on protein structure, dynamics, and function. Towards that end, we have employed all-atom molecular dynamics simulations on various glycosylated stages of a bound and free Lili-Mip protein and characterised the impact of glycans and the bound lipid on the dynamics of this glycoconjugate. Our work provides important molecular-level mechanistic insights into the role of glycans in the nutrient storage function of the Lili-Mip protein. Our analyses show that the glycans stabilise spatially proximal residues and regulate the low amplitude opening motions of the residues at the entrance of the binding pocket. Glycans also preserve the native orientation and conformational flexibility of the ligand. However, we find that either deglycosylation or glycosylation with high-mannose and paucimannose on the core glycans, which better mimic the natural insect glycosylation state, significantly affects the conformation and dynamics. A simple but effective distance- and correlation-based network analysis of the protein also reveals the key residues regulating the barrel's architecture and ligand binding characteristics in response to glycosylation.

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.

Dissecting the Conformational Stability of a Glycan Hairpin

Systematic structural studies of model oligopeptides revealed important aspects of protein folding and offered design principles to access non-natural materials. In the same way, the rules that regulate glycan folding could be established by studying synthetic oligosaccharide models. However, their analysis is often limited due to the synthetic and analytical complexity. By utilizing a glycan capable of spontaneously folding into a hairpin conformation as a model system, we investigated the factors that contribute to its conformational stability in aqueous solution. The modular design of the hairpin model featured a trisaccharide turn unit and two β-1,4-oligoglucoside stacking strands that allowed for systematic chemical modifications of the glycan sequence, including the introduction of NMR labels and staples. Nuclear magnetic resonance assisted by molecular dynamics simulations revealed that stereoelectronic effects and multiple glycan-glycan interactions are the major determinants of folding stabilization. Chemical modifications in the glycan primary sequence (e.g., strand elongation) can be employed to fine-tune the rigidity of structural motifs distant from the modification sites. These results could inspire the design of other glycan architectures, with implications in glycobiology and material sciences.

In Situ Glycan Analysis and Editing in Living Systems

Besides proteins and nucleic acids, carbohydrates are also ubiquitous building blocks of living systems. Approximately 70% of mammalian proteins are glycosylated. Glycans not only provide structural support for living systems but also act as crucial regulators of cellular functions. As a result, they are considered essential pieces of the life science puzzle. However, research on glycans has lagged far behind that on proteins and nucleic acids. The main reason is that glycans are not direct products of gene coding, and their synthesis is nontemplated. In addition, the diversity of monosaccharide species and their linkage patterns contribute to the complexity of the glycan structures, which is the molecular basis for their diverse functions. Research in glycobiology is extremely challenging, especially for the in situ elucidation of glycan structures and functions. There is an urgent need to develop highly specific glycan labeling tools and imaging methods and devise glycan editing strategies. This Perspective focuses on the challenges of in situ analysis of glycans in living systems at three spatial levels (i.e., cell, tissue, and in vivo) and highlights recent advances and directions in glycan labeling, imaging, and editing tools. We believe that examining the current development landscape and the existing bottlenecks can drive the evolution of in situ glycan analysis and intervention strategies and provide glycan-based insights for clinical diagnosis and therapeutics.

Many Roles of Carbohydrates: A Computational Spotlight on the Coronavirus S Protein Binding

Glycosylation is one of the post-translational modifications with more than 50% of human proteins being glycosylated. The exact nature and chemical composition of glycans are inaccessible to X-ray or cryo-electron microscopy imaging techniques. Therefore, computational modeling studies and molecular dynamics must be used as a "computational microscope". The spike (S) protein of SARS-CoV-2 is heavily glycosylated, and a few glycans play a more functional role "beyond shielding". In this mini-review, we discuss computational investigations of the roles of specific S-protein and ACE2 glycans in the overall ACE2-S protein binding. We highlight different functions of specific glycans demonstrated in myriad computational models and simulations in the context of the SARS-CoV-2 virus binding to the receptor. We also discuss interactions between glycocalyx and the S protein, which may be utilized to design prophylactic polysaccharide-based therapeutics targeting the S protein. In addition, we underline the recent emergence of coronavirus variants and their impact on the S protein and its glycans.

Glycan Shape, Motions, and Interactions Explored by NMR Spectroscopy

Glycans in the form of oligosaccharides, polysaccharides, and glycoconjugates are ubiquitous in nature, and their structures range from linear assemblies to highly branched and decorated constructs. Solution state NMR spectroscopy facilitates elucidation of preferred conformations and shapes of the saccharides, motions, and dynamic aspects related to processes over time as well as the study of transient interactions with proteins. Identification of intermolecular networks at the atomic level of detail in recognition events by carbohydrate-binding proteins known as lectins, unraveling interactions with antibodies, and revealing substrate scope and action of glycosyl transferases employed for synthesis of oligo- and polysaccharides may efficiently be analyzed by NMR spectroscopy. By utilizing NMR active nuclei present in glycans and derivatives thereof, including isotopically enriched compounds, highly detailed information can be obtained by the experiments. Subsequent analysis may be aided by quantum chemical calculations of NMR parameters, machine learning-based methodologies and artificial intelligence. Interpretation of the results from NMR experiments can be complemented by extensive molecular dynamics simulations to obtain three-dimensional dynamic models, thereby clarifying molecular recognition processes involving the glycans.

Molecular Dynamics Simulation and Docking of MUC1 O-Glycopeptide

Advances in computer performance and computational simulations allow increasing sophistication in applications in biological systems. Molecular dynamics (MD) simulations are especially suitable for studying conformation, dynamics, and interaction of flexible biomolecules such as free glycans and glycopeptides. Computer simulations are best performed when the scope and limitations in performance have been thoroughly assessed. Proper outputs are obtained only under suitable parameter settings, and results need to be properly validated. In this chapter, we will introduce an example of molecular dynamics simulations of MUC1 O-glycopeptide and its docking to anti-MUC1 antibody Fv fragment.

Structural insight into why S-linked glycosylation cannot adequately mimic the role of natural O-glycosylation

There is an increasing interest in using S-glycosylation as a replacement for the more commonly occurring O-glycosylation, aiming to enhance the resistance of glycans against chemical hydrolysis and enzymatic degradation. However, previous studies have demonstrated that these two types of glycosylation exert distinct effects on protein properties and functions. In order to elucidate the structural basis behind the observed differences, we conducted a systematic and comparative analysis of 6 differently glycosylated forms of a model glycoprotein, CBM, using NMR spectroscopy and molecular dynamic simulations. Our findings revealed that the different stabilizing effects of S- and O-glycosylation could be attributed to altered hydrogen-bonding capability between the glycan and the polypeptide chain, and their diverse impacts on binding affinity could be elucidated by examining the interactions and motion dynamics of glycans in substrate-bound states. Overall, this study underscores the pivotal role of the glycosidic linkage in shaping the function of glycosylation and advises caution when switching glycosylation types in protein glycoengineering.

Shiitake polysaccharides acted as a non-competitive inhibitor to α-glucosidase and inhibited glucose transport of digested starch from Caco-2 cells monolayer

The inhibition mechanism of shitake mushroom polysaccharides (Lentinula edodes polysaccharides, LEP) against α-glucosidase was studied by enzyme kinetic assay, fluorescence quenching and molecular docking. The effect of LEP on glucose transport of digested starch was investigated via an in vitro digestion/Caco-2 transwell model. LEP exhibited a stronger inhibiting effect (IC50 = 0.66 mg/mL) than acarbose and presented a non-competitive inhibition mechanism. The interaction between LEP and α-glucosidase primarily involved electrostatic interaction and hydrogen bonding. Molecular docking modelling showed that the four structures of LEP were bound to the allosteric tunnel or adjacent pocket of α-glucosidase via electrostatic force and hydrogen bonds. The (1 → 6)-linkages in LEP structures favoured its binding affinity to the α-glucosidase. The α-glucosidase inhibiting activity of LEP was also found to emanate from the reduction in glucose transport of digested starch as deducted from the in vitro digestion/Caco-2 transwell data. The release of glucose from digested starch cooked with LEP was significantly reduced (33.7%) compared to the digested starch without LEP. The findings from the current study suggest that LEP could be a promising ingredient to inhibit α-glucosidase activity as well as control the level of postprandial blood glucose when incorporated into starchy foods.

A quinolin-8-ol sub-millimolar inhibitor of UGGT, the ER glycoprotein folding quality control checkpoint

Misfolded glycoprotein recognition and endoplasmic reticulum (ER) retention are mediated by the ER glycoprotein folding quality control (ERQC) checkpoint enzyme, UDP-glucose glycoprotein glucosyltransferase (UGGT). UGGT modulation is a promising strategy for broad-spectrum antivirals, rescue-of-secretion therapy in rare disease caused by responsive mutations in glycoprotein genes, and many cancers, but to date no selective UGGT inhibitors are known. The small molecule 5-[(morpholin-4-yl)methyl]quinolin-8-ol (5M-8OH-Q) binds a CtUGGTGT24 "WY" conserved surface motif conserved across UGGTs but not present in other GT24 family glycosyltransferases. 5M-8OH-Q has a 47 μM binding affinity for CtUGGTGT24in vitro as measured by ligand-enhanced fluorescence. In cellula, 5M-8OH-Q inhibits both human UGGT isoforms at concentrations higher than 750 μM. 5M-8OH-Q binding to CtUGGTGT24 appears to be mutually exclusive to M5-9 glycan binding in an in vitro competition experiment. A medicinal program based on 5M-8OH-Q will yield the next generation of UGGT inhibitors.

Immune evasion through Toll-like receptor 4: The role of the core oligosaccharides from α2-Proteobacteria atypical lipopolysaccharides

Lipopolysaccharides (LPS) are major players in bacterial infection through the recognition by Toll-like receptor 4 (TLR4). The LPS chemical structure, including the oligosaccharide core and the lipid A moiety, can be strongly influenced by adaptation and modulated to assure bacteria protection, evade immune surveillance, or reduce host immune responses. Deep structural understanding of TLRs signaling is essential for the modulation of the innate immune system in sepsis control and inflammation, during bacterial infection. To advance this knowledge, we have employed computational techniques to characterize the TLR4 molecular recognition of atypical LPSs from different opportunistic members of α2-Proteobacteria, including Brucella melitensis, Ochrobactrum anthropi, and Ochrobactrum intermedium, with diverse immunostimulatory activities. We contribute to unraveling the role of uncommon lipid A chemical features such as bearing very long-chain fatty acid chains, whose presence has been rarely reported, on modulating the proper heterodimerization of the TLR4 receptor complex. Moreover, we further evaluated the influence of the different oligosaccharide cores, including sugar composition and net charge, on TLR4 activation. Our studies contribute to elucidating, from the molecular and biological perspectives, the impact of the α2-Proteobacteria LPS cores and the chemical structure of the atypical lipid A for immune system evasion in opportunistic bacteria.

Synthesis of a glycan hairpin

The primary sequence of a biopolymer encodes the essential information for folding, permitting to carry out sophisticated functions. Inspired by natural biopolymers, peptide and nucleic acid sequences have been designed to adopt particular three-dimensional (3D) shapes and programmed to exert specific functions. In contrast, synthetic glycans capable of autonomously folding into defined 3D conformations have so far not been explored owing to their structural complexity and lack of design rules. Here we generate a glycan that adopts a stable secondary structure not present in nature, a glycan hairpin, by combining natural glycan motifs, stabilized by a non-conventional hydrogen bond and hydrophobic interactions. Automated glycan assembly enabled rapid access to synthetic analogues, including site-specific 13C-labelled ones, for nuclear magnetic resonance conformational analysis. Long-range inter-residue nuclear Overhauser effects unequivocally confirmed the folded conformation of the synthetic glycan hairpin. The capacity to control the 3D shape across the pool of available monosaccharides has the potential to afford more foldamer scaffolds with programmable properties and functions.

Resolving domain positions of cellobiose dehydrogenase by small angle X-ray scattering

The interdomain electron transfer (IET) between the catalytic flavodehydrogenase domain and the electron-transferring cytochrome domain of cellobiose dehydrogenase (CDH) plays an essential role in biocatalysis, biosensors and biofuel cells, as well as in its natural function as an auxiliary enzyme of lytic polysaccharide monooxygenase. We investigated the mobility of the cytochrome and dehydrogenase domains of CDH, which is hypothesised to limit IET in solution by small angle X-ray scattering (SAXS). CDH from Myriococcum thermophilum (syn. Crassicarpon hotsonii, syn. Thermothelomyces myriococcoides) was probed by SAXS to study the CDH mobility at different pH and in the presence of divalent cations. By comparison of the experimental SAXS data, using pair-distance distribution functions and Kratky plots, we show an increase in CDH mobility at higher pH, indicating alterations of domain mobility. To further visualise CDH movement in solution, we performed SAXS-based multistate modelling. Glycan structures present on CDH partially masked the resulting SAXS shapes, we diminished these effects by deglycosylation and studied the effect of glycoforms by modelling. The modelling shows that with increasing pH, the cytochrome domain adopts a more flexible state with significant separation from the dehydrogenase domain. On the contrary, the presence of calcium ions decreases the mobility of the cytochrome domain. Experimental SAXS data, multistate modelling and previously reported kinetic data show how pH and divalent ions impact the closed state necessary for the IET governed by the movement of the CDH cytochrome domain.

Sequence variety in the CC' loop of Siglec-8/9/3 determines the recognitions to sulfated oligosaccharides

Siglecs are important lectins found in different types of immune cells and function as regulatory molecules by recognizing self-associated glycans and converting extracellular interactions into signals for inhibiting immune cell functions. Although many Siglecs have been found to show broad specificities and recognize different types of sulfated oligosaccharides, Siglec-8 and Siglec-9 displayed a high degree of specificity for sialyl N-acetyllactosamine (sLacNAc) with sulfations at O6-positions of the galactose (6'-sulfation) and N-acetylglucosamine (6-sulfation), respectively. Siglec-3 was recently discovered to bind sLacNAc both sulfations. In addition to a conserved arginine residue for binding to sialic acid residue, the sequence variety in the CC' loop may provide binding specificities to sulfated oligosaccharides in Siglecs. Thus, the present study employed molecular models to study the impact of different residues in the CC' loops of Siglec-8/9/3 to the recognitions of 6-sulfations in Gal and/or GlcNAc of sLacNAc. The negatively charged residues in the CC' loop of Siglec-9 formed unfavorable electrostatic repulsions with the 6-sulfate in Gal and resulted no recognitions, in contrast to the favorable interactions formed between the positively charged residues in the CC' loop of Siglec-8 and the 6-sulfate in Gal resulting strong specificity. A two-state binding model was proposed for Siglec-3 recognizing 6-sulfations in Gal and GlcNAc of sLacNAc, as the neutral residues in the CC' loop of Siglec-3 could not form strong favorable interactions to lock the 6-sulfate in Gal within a single binding pose or strong unfavorable interactions to repel the 6-sulfate in Gal. The oligosaccharide adopted two distinctive binding poses and oriented the sulfate groups to form interactions with residues in the CC' loop and G-strand. The present study provided a structural mechanism for the sequence variety in the CC' loop of Siglec-8/9/3 determining the recognitions to the sulfated oligosaccharides and offered insights into the binding specificities for Siglecs.

Primary Structure of Glycans by NMR Spectroscopy

Glycans, carbohydrate molecules in the realm of biology, are present as biomedically important glycoconjugates and a characteristic aspect is that their structures in many instances are branched. In determining the primary structure of a glycan, the sugar components including the absolute configuration and ring form, anomeric configuration, linkage(s), sequence, and substituents should be elucidated. Solution state NMR spectroscopy offers a unique opportunity to resolve all these aspects at atomic resolution. During the last two decades, advancement of both NMR experiments and spectrometer hardware have made it possible to unravel carbohydrate structure more efficiently. These developments applicable to glycans include, inter alia, NMR experiments that reduce spectral overlap, use selective excitations, record tilted projections of multidimensional spectra, acquire spectra by multiple receivers, utilize polarization by fast-pulsing techniques, concatenate pulse-sequence modules to acquire several spectra in a single measurement, acquire pure shift correlated spectra devoid of scalar couplings, employ stable isotope labeling to efficiently obtain homo- and/or heteronuclear correlations, as well as those that rely on dipolar cross-correlated interactions for sequential information. Refined computer programs for NMR spin simulation and chemical shift prediction aid the structural elucidation of glycans, which are notorious for their limited spectral dispersion. Hardware developments include cryogenically cold probes and dynamic nuclear polarization techniques, both resulting in enhanced sensitivity as well as ultrahigh field NMR spectrometers with a 1H NMR resonance frequency higher than 1 GHz, thus improving resolution of resonances. Taken together, the developments have made and will in the future make it possible to elucidate carbohydrate structure in great detail, thereby forming the basis for understanding of how glycans interact with other molecules.

Impact of Polarization on the Ring Puckering Dynamics of Hexose Monosaccharides

Analysis of crystal structures of hexose monosaccharides α-d-mannose (α-MAN), β-d-mannose (β-MAN), α-d-glucose (α-GLC), β-d-glucose (β-GLC), α-d-galactose (α-GAL), β-d-galactose (β-GAL), α-d-altrose (α-ALT), β-d-altrose (β-ALT), α-d-idose (α-IDO), and β-d-idose (β-IDO) reveals that the monosaccharide ring adopts multiple ring conformations. These ring conformations can be broadly classified as chair, half-chair, envelope, boat, and skew-boat conformations. The ability of the monosaccharide ring to adopt multiple conformations has been closely tied with their bioactivity. However, it has been difficult to capture the dynamic information of these conformations from experimental studies. Even from simulations, capturing these different conformations is challenging because of the energy barriers involved in the transitions between the stable ⁴C₁ and ¹C₄ chair forms. In this study, we analyze the influence of the polarizable force field on the ring dynamics of five major types of unsubstituted aldohexoses─glucose, mannose, galactose, altrose, and idose─and their anomers. We simulate microsecond trajectories to capture the influence of the CHARMM36 additive and polarizable carbohydrate force fields on the ring dynamics. The microsecond trajectories allow us to comment on the issues associated with equilibrium molecular dynamics simulations. Further, we use the extended system adaptive biasing force (eABF) method to compare the conformational sampling efficiencies of the additive and polarizable force fields. Our studies reveal that inclusion of polarization enhances the sampling of ring conformations and lowers the energy barriers between the ⁴C₁ and ¹C₄ conformations. Overall, the CHARMM36 additive force field is observed to be rigid and favor the ⁴C₁ conformations. Although the inclusion of polarizability results in enhancing ring flexibility, we observe sampling that does not agree with experimental results, warranting a revision of the polarizable Drude parameters.

Structural Analysis of Oligosaccharides and Glycoconjugates Using NMR

Carbohydrate chains play critical roles in cellular recognition and subsequent signal transduction in the nervous system. Furthermore, gangliosides are targets for various amyloidogenic proteins associated with neurodegenerative disorders. To better understand the molecular mechanisms underlying these biological phenomena, atomic views are essential to delineate dynamic biomolecular interactions. Nuclear magnetic resonance (NMR) spectroscopy provides powerful tools for studying structures, dynamics, and interactions of biomolecules at the atomic level. This chapter describes the basics of solution NMR techniques and their applications to the analysis of 3D structures and interactions of glycoconjugates in the nervous system.

Glycan Conformation in the Heavily Glycosylated Protein, CEACAM1

Glycans attached to glycoproteins can contribute to stability, mediate interactions with other proteins, and initiate signal transduction. Glycan conformation, which is critical to these processes, is highly variable and often depicted as sampling a multitude of conformers. These conformers can be generated by molecular dynamics simulations, and more inclusively by accelerated molecular dynamics, as well as other extended sampling methods. However, experimental assessments of the contribution that various conformers make to a native ensemble are rare. Here, we use long-range pseudo-contact shifts (PCSs) of NMR resonances from an isotopically labeled glycoprotein to identify preferred conformations of its glycans. The N-terminal domain from human Carcinoembryonic Antigen Cell Adhesion Molecule 1, hCEACAM1-Ig1, was used as the model glycoprotein in this study. It has been engineered to include a lanthanide-ion-binding loop that generates PCSs, as well as a homogeneous set of three ¹³C-labeled N-glycans. Analysis of the PCSs indicates that preferred glycan conformers have extensive contacts with the protein surface. Factors leading to this preference appear to include interactions between N-acetyl methyls of GlcNAc residues and hydrophobic surface pockets on the protein surface.

Synthetic Approaches to Break the Chemical Shift Degeneracy of Glycans

NMR spectroscopy is the leading technique for determining glycans' three-dimensional structure and dynamic in solution as well as a fundamental tool to study protein-glycan interactions. To overcome the severe chemical shift degeneracy of these compounds, synthetic probes carrying NMR-active nuclei (e. g., 13 C or 19 F) or lanthanide tags have been proposed. These elegant strategies permitted to simplify the complex NMR analysis of unlabeled analogues, shining light on glycans' conformational aspects and interaction with proteins. Here, we highlight some key achievements in the synthesis of specifically labeled glycan probes and their contribution towards the fundamental understanding of glycans.

One-Bond 13C-1H and 13C-13C Spin-Coupling Constants as Constraints in MA'AT Analysis of Saccharide Conformation

MA'AT analysis uses ensembles of redundant experimental NMR spin-coupling constants, parametrized J-coupling equations obtained from density functional theory (DFT) calculations, and circular statistics to produce probability distributions of molecular torsion angles in solution and information on librational motions about these angles (Meredith et al., J. Chem. Info. Model. 2022, 62, 3135-3141). Current DFT methods give nearly quantitative two- and three-bond J_HH, J_CH, and ¹J_CC values for use in MA'AT analysis of saccharides. In contrast, the accuracy of DFT-calculated one-bond ¹J_CH and ¹J_CC values is more difficult to determine, preventing their use in MA'AT modeling. This report describes experimental and computational studies that address this problem using two approaches (Strategies 1 and 2). Differences [¹J_CH^calc - ¹J_CH^exp] (Strategy 1) ranged from -1.2 to 2.5 Hz, giving an average difference of 0.8 ± 1.7 Hz. Percent differences ranged from -0.8% to 1.6%, giving an average % difference of 0.5 ± 1.1%. In comparison, [¹J_CH^MA'AT - ¹J_CH^exp] (Strategy 2) ranged from -1.8 to 0.2 Hz, giving an average difference of -1.2 ± 0.7 Hz. Percent differences ranged from -1.2% to 0.1%, giving an average % difference of -0.8 ± 0.5%. Strategy 1 gave an average difference of 2.1 Hz between calculated and experimental ¹J_CC values, with an average % difference of 5.1 ± 0.2%. Calculated ¹J_CC values were consistently larger than experimental values. Strategy 2 also gave calculated ¹J_CC values that were larger than the experimental values, with an average difference of 2.3 ± 0.6 Hz, and an average % difference of 5.6 ± 1.6%. The findings of both strategies are similar and indicate that ¹J_CH values in saccharides can be calculated nearly quantitatively, but ¹J_CC values appear to be consistently overestimated by ∼5% using current DFT methods.

Re-Emergence of Circulation of Seasonal Influenza during COVID-19 Pandemic in Russia and Receptor Specificity of New and Dominant Clade 3C.2a1b.2a.2 A(H3N2) Viruses in 2021-2022

The circulation of seasonal influenza in 2020-2021 around the world was drastically reduced after the start of the COVID-19 pandemic and the implementation of mitigation strategies. The influenza virus circulation reemerged in 2021-2022 with the global spread of the new genetic clade 3C.2a1b.2a.2 of A(H3N2) viruses. The purpose of this study was to characterize influenza viruses in the 2021-2022 season in Russia and to analyze the receptor specificity properties of the 3C.2a1b.2a.2 A(H3N2) viruses. Clinical influenza samples were collected at the local Sanitary-and-Epidemiological Centers of Rospotrebnadzor. Whole genome sequencing was performed using NGS. The receptor specificity of hemagglutinin was evaluated using molecular modeling and bio-layer interferometry. Clinical samples from 854 cases of influenza A and B were studied; A(H3N2) viruses were in the majority of the samples. All genetically studied A(H3N2) viruses belonged to the new genetic clade 3C.2a1b.2a.2. Molecular modeling analysis suggested a higher affinity of hemagglutinin of 3C.2a1b.2a.2. A(H3N2) viruses to the α2,6 human receptor. In vitro analysis using a trisaccharide 6'-Sialyl-N-acetyllactosamine receptor analog did not resolve the differences in the receptor specificity of 3C.2a1b.2a.2 clade viruses from viruses belonging to the 3C.2a1b.2a.1 clade. Further investigation of the A(H3N2) viruses is required for the evaluation of their possible adaptive advantages. Constant monitoring and characterization of influenza are critical for epidemiological analysis.

Effect of the Graphene Nanosheet on Functions of the Spike Protein in Open and Closed States: Comparison between SARS-CoV-2 Wild Type and the Omicron Variant

The spread of coronavirus disease 2019 caused by SARS-CoV-2 and its variants has become a global health crisis. Although there were many attempts to use nanomaterials-based devices to fight against SARS-CoV-2, it still remains elusive as to how the nanomaterials interact with SARS-CoV-2 and affect its biofunctions. Here, taking the graphene nanosheet (GN) as the model nanomaterial, we investigate its interaction with the spike protein in both WT and Omicron by molecular simulations. In the closed state, the GN can insert into the region between the receptor binding domain (RBD) and the N-terminal domain (NTD) in both wild type (WT) and Omicron, which keeps the RBD in the down conformation. In the open state, the GN can hamper the binding of up RBD to ACE2 in WT, but it has little impact on up RBD and, even worse, stimulates the down-to-up transition of down RBDs in Omicron. Moreover, the GN can insert in the vicinity of the fusion peptide in both WT and Omicron and prevents the detachment of S1 from the whole spike protein. The present study reveals the effect of the SARS-CoV-2 variant on the nanomaterial-spike protein interaction, which informs prospective efforts to design functional nanomaterials against SARS-CoV-2.

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.

Exploration, Representation, and Rationalization of the Conformational Phase Space of N-Glycans

Despite their fundamental biological relevance, structure-property relationships in N-glycans are fundamentally lacking, and their highly multidimensional compositional and conformational phase spaces remain largely unexplored. The torsional flexibility of the glycosidic linkages and the ring dynamics result in wide, rugged free-energy landscapes that are difficult to sample in molecular dynamics simulations. We show that a novel enhanced-sampling scheme combining replica exchange with solute and collective-variable tempering, enabling transitions over all relevant energy barriers, delivers converged distributions of solvated N-glycan conformers. Several dimensionality-reduction algorithms are compared and employed to generate conformational free-energy maps in two dimensions. Together with an originally developed conformation-based nomenclature scheme that uniquely identifies glycan conformers, our modeling procedure is applied to reveal the effect of chemical substitutions on the conformational ensemble of selected high-mannose-type and complex glycans. Moreover, the structure-prediction capabilities of two commonly used glycan force fields are assessed via the theoretical prediction of experimentally available nuclear magnetic resonance J-coupling constants. The results especially confirm the key role of ω and ψ torsion angles in discriminating between different conformational states and suggest an intriguing correlation between the torsional and ring-puckering degrees of freedom that may be biologically relevant.

Extending the Martini 3 Coarse-Grained Force Field to Carbohydrates

Carbohydrates play an essential role in a large number of chemical and biochemical processes. High structural diversity and conformational heterogeneity make it problematic to link their measurable properties to molecular features. Molecular dynamics simulations carried out at the level of classical force fields are routinely applied to study the complex processes occurring in carbohydrate-containing systems, while the usefulness of such simulations relies on the accuracy of the underlying theoretical model. In this article, we present the coarse-grained force field dedicated to glucopyranose-based carbohydrates and compatible with the recent version of the Martini force field (v. 3.0). The parameterization was based on optimizing bonded and nonbonded parameters with a reference to the all-atom simulation results and the experimental data. Application of the newly developed coarse-grained carbohydrate model to oligosaccharides curdlan and cellulose displays spontaneous formation of aggregates of experimentally identified features. In contact with other biomolecules, the model is capable of recovering the protective effect of glucose monosaccharides on a lipid bilayer and correctly identifying the binding pockets in carbohydrate-binding proteins. The features of the newly proposed model make it an excellent candidate for further extensions, aimed at modeling more complex, functionalized, and biologically relevant carbohydrates.