doGlycans-Tools for Preparing Carbohydrate Structures for Atomistic Simulations of Glycoproteins, Glycolipids, and Carbohydrate Polymers for GROMACS

Impact of glycan nature on structure and viscoelastic properties of glycopeptide hydrogels

Mucus is a complex biological hydrogel that acts as a barrier for almost everything entering or exiting the body. It is therefore of emerging interest for biomedical and pharmaceutical applications. Besides water, the most abundant components are the large and densely glycosylated mucins, glycoproteins of up to 20 MDa and carbohydrate content of up to 80 wt%. Here, we designed and explored a library of glycosylated peptides to deconstruct the complexity of mucus. Using the well-characterized hFF03 coiled-coil system as a hydrogel-forming peptide scaffold, we systematically probed the contribution of single glycans to the secondary structure as well as the formation and viscoelastic properties of the resulting hydrogels. We show that glycan-decoration does not affect α-helix and coiled-coil formation while it alters gel stiffness. By using oscillatory macrorheology, dynamic light scattering microrheology, and fluorescence lifetime-based nanorheology, we characterized the glycopeptide materials over several length scales. Molecular simulations revealed that the glycosylated linker may extend into the solvent, but more frequently interacts with the peptide, thereby likely modifying the stability of the self-assembled fibers. This systematic study highlights the interplay between glycan structure and hydrogel properties and may guide the development of synthetic mucus mimetics.

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.

Lignocellulosic biomass-based glycoconjugates for diverse biotechnological applications

Glycoconjugates are the ubiquitous components of mammalian cells, mainly synthesized by covalent bonds of carbohydrates to other biomolecules such as proteins and lipids, with a wide range of potential applications in novel vaccines, therapeutic peptides and antibodies (Ab). Considering the emerging developments in glycoscience, renewable production of glycoconjugates is of importance and lignocellulosic biomass (LCB) is a potential source of carbohydrates to produce synthetic glycoconjugates in a sustainable pathway. In this review, recent advances in glycobiology aiming on glycoconjugates production is presented together with the recent and cutting-edge advances in the therapeutic properties and application of glycoconjugates, including therapeutic glycoproteins, glycosaminoglycans (GAGs), and nutraceuticals, emphasizing the integral role of glycosylation in their function and efficacy. Special emphasis is given towards the potential exploration of carbon neutral feedstocks, in which LCB has an emerging role. Techniques for extraction and recovery of mono- and oligosaccharides from LCB are critically discussed and influence of the heterogeneous nature of the feedstocks and different methods for recovery of these sugars in the development of the customized glycoconjugates is explored. Although reports on the use of LCB for the production of glycoconjugates are scarce, this review sets clear that the potential of LCB as a source for the production of valuable glycoconjugates cannot be underestimated and encourages that future research should focus on refining the existing methodologies and exploring new approaches to fully realize the potential of LCB in glycoconjugate production.

polyGraft 1.0: A program for molecular structure and topology generation of polymer-grafted hybrid nanostructures

Polymer-grafted hybrid materials have been ubiquitously employed in various engineering applications. The design of these hybrid materials with superior performances requires a molecularly detailed understanding of the structure and dynamics of the polymer brushes and their interactions with the grafting substrate. Molecular dynamics (MD) simulations are very well suited for the study of these materials which can provide molecular insights into the effects of polymer composition and length, grafting density, substrate composition and curvatures, and nanoconfinement. However, few existing tools are available to generate such systems, which would otherwise reduce the barrier of preparation for such systems to enable high throughput simulations. Here polyGraft, a general, flexible, and easy to use Python program, is introduced for automated generation of molecular structure and topology of polymer grafted hybrid materials for MD simulations purposes, ranging from polymer brushes grafted to hard substrates, to densely grafted bottlebrush polymers. polyGraft is openly accessible on GitHub (https://github.com/nanogchen/polyGraft).

Optimization of a small molecule inhibitor of secondary nucleation in α-synuclein aggregation

Parkinson's disease is characterised by the deposition in the brain of amyloid aggregates of α-synuclein. The surfaces of these amyloid aggregates can catalyse the formation of new aggregates, giving rise to a positive feedback mechanism responsible for the rapid proliferation of α-synuclein deposits. We report a procedure to enhance the potency of a small molecule to inhibit the aggregate proliferation process using a combination of in silico and in vitro methods. The optimized small molecule shows potency already at a compound:protein stoichiometry of 1:20. These results illustrate a strategy to accelerate the optimisation of small molecules against α-synuclein aggregation by targeting secondary nucleation.

Automatic Multiscale Method of Building up a Cross-linked Polymer Reaction System: Bridging SMILES to the Multiscale Molecular Dynamics Simulation

An automatic method is introduced to generate the initial configuration and input file from SMILES for multiscale molecular dynamics (MD) simulation of cross-linked polymer reaction systems. Inputs are a modified version of SMILES of all the components and conditions of coarse-grained (CG) and all-atom (AA) simulations. The overall process comprises the following steps: (1) Modified SMILES inputs of all the components are converted to 3-dimensional coordinates of molecular structures. (2) Molecular structures are mapped to the coarse-grained scale, followed by a CG reaction simulation. (3) CG beads are backmapped to the atomic scale after the CG reaction. (4) An AA productive run is finally performed to analyze volume shrinkage, glass transition, and atomic detail of network structure. The method is applied to two common epoxy resin reactions, that is, the cross-linking process of DGEVA (diglycidyl ether of vanillyl alcohol) and DHAVA (dihydroxyaminopropane of vanillyl alcohol) and that of DGEBA (diglycidyl ether of bisphenol A) and DETA (diethylenetriamine). These components form network structures after the CG cross-linking reaction and are then backmapped to calculate properties in the atomic scale. The result demonstrates that the method can accurately predict volume shrinkage, glass transition, and all-atom structure of cross-linked polymers. The method bridges from SMILES to MD simulation trajectories in an automatic way, which shortens the time of building up cross-linked polymer reaction model and suitable for high-throughput computations.

Differential MMP-14 targeting by biglycan, decorin, fibromodulin, and lumican unraveled by in silico approach

Small leucine-rich proteoglycans (SLRPs) are major regulators of extracellular matrix assembly and cell signaling. Lumican, a member of the SLRPs family, and its derived peptides were shown to possess antitumor activity by interacting directly with the catalytic domain of MMP-14 leading to the inhibition of its activity. The aim of the present report was to characterize by in silico three-dimensional (3D) modeling the structure and the dynamics of four SLRPs including their core protein and their specific polysaccharide chains to assess their capacity to bind to MMP-14 and to regulate its activity. Molecular docking experiments were performed to identify the specific amino acids of MMP-14 interacting with each of the four SLRPs. The inhibition of each SLRP (100 nM) on MMP-14 activity was measured and the constants of inhibition (K_i) were evaluated. The impact of the number of glycan chains, structures, and dynamics of lumican on the interaction with MMP-14 was assessed by molecular dynamics simulations. Molecular docking analysis showed that all SLRPs bind to MMP-14 through their concave face, but in different regions of the catalytic domain of MMP-14. Each SLRPs inhibited significantly the MMP-14 activity. Finally, molecular dynamics showed the role of glycan chains in interaction with MMP-14 and shielding effect of SLRPs. Altogether, the results demonstrated that each SLRP exhibited inhibition of MMP-14 activity. However, the differential targeting of MMP-14 by the SLRPs was shown to be related not only to the core protein conformation but also to the glycan chain structures and dynamics.

Polyelectrolyte Influence on Beta-Hairpin Peptide Stability: A Simulation Study

Assemblies of proteins and charged macromolecules (polyelectrolytes) find important applications as pharmaceutical formulations, biocatalysts, and cell-contacting substrates. A key question is how the polymer component influences the structure and function of the protein. The present paper addresses the influence of charged polymers on the thermal stability of two model beta-hairpin-forming peptides through an all-atom, replica exchange molecular dynamics simulation. The (negatively charged) peptides consist of the terminal 16 amino acids of the B1 domain of Protein G (GB1) and a variant with three of the GB1 residues substituted with tryptophan (Tryptophan Zipper 4, or TZ4). A (cationic) lysine polymer is seen to thermally stabilize TZ4 and destabilize GB1, while a (also cationic) chitosan polymer slightly stabilizes GB1 but has essentially no effect on TZ4. Free energy profiles reveal folded and unfolded conformations to be separated by kinetic barriers generally acting in the direction of the thermodynamically favored state. Through application of an Ising-like statistical mechanical model, a mechanism is proposed based on competition between (indirect) entropic stabilization of folded versus unfolded states and (direct) competition for hydrogen-bonding and hydrophobic interactions. These findings have important implications to the design of polyelectrolyte-based materials for biomedical and biotechnological applications.

Modelling and Simulations of Extracellular Glycoproteins

While the knowledge of protein structure and function has seen vast advances in previous decades, the understanding of how their posttranslational modifications, such as glycosylations, influence their structure and function remains poor. However, advances in in silico methodologies to study glycosylations in recent past have enabled us to study this and understand the role of glycosylations in protein structure and function in ways that would not be possible by conventional experimental methods. In this chapter, we will demonstrate how to leverage these methodologies to study glycoproteins and their structural and dynamic properties using molecular modelling techniques.

Molecular dynamics simulations and kinetic measurements provide insights into the structural requirements of substrate size-dependent specificity of oligogalacturonide oxidase 1 (OGOX1)

Oligogalacturonides (OGs) are pectin fragments released from the breakdown of the homogalacturonan during pathogenesis that act as Damage-Associated Molecular Patterns. OG-oxidase 1 (OGOX1) is an Arabidopsis berberine bridge enzyme-like (BBE-l) oligosaccharide oxidase that oxidizes OGs, impairing their elicitor activity and concomitantly releasing H₂O₂. The OG-oxidizing activity of OGOX1 is markedly pH-dependent, with optimum pH around 10, and is higher towards OGs with a degree of polymerization higher than two. Here, the molecular determinants of OGOX1 responsible for the binding of OGs with different lengths have been investigated through molecular dynamics simulations and enzyme kinetics studies. OGOX1 was simulated in complex with OGs with different degree of polymerization such as di-, tri-, tetra- and penta-galacturonide, in water solution at alkaline pH. Our simulations revealed that, among the four OGOX1/OG combinations, the penta-galacturonide (OG5) showed the best conformation in the active site to be efficiently oxidized by OGOX1. The optimal conformation can be stabilized by salt-bridges formed between the carboxyl groups of OG5 and five positively charged amino acids of OGOX1, highly conserved in all OGOX paralogs. Our results suggest that these interactions limit the mobility of OG5 as well as longer OGs, contributing to maintain the terminal monomer of OGs in the optimal orientation in order to be oxidized by the enzyme. In accordance with these results, the enzyme efficiency (K_cat/K_M) of OGOX1 on OG5 (40.04) was found to be significantly higher than that on OG4 (13.05) and OG3 (0.6).

Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities

Influenza virus has resurfaced recently from inactivity during the early stages of the COVID-19 pandemic, raising serious concerns about the nature and magnitude of future epidemics. The main antigenic targets of influenza virus are two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). Whereas the structural and dynamical properties of both glycoproteins have been studied previously, the understanding of their plasticity in the whole-virion context is fragmented. Here, we investigate the dynamics of influenza glycoproteins in a crowded protein environment through mesoscale all-atom molecular dynamics simulations of two evolutionary-linked glycosylated influenza A whole-virion models. Our simulations reveal and kinetically characterize three main molecular motions of influenza glycoproteins: NA head tilting, HA ectodomain tilting, and HA head breathing. The flexibility of HA and NA highlights antigenically relevant conformational states, as well as facilitates the characterization of a novel monoclonal antibody, derived from convalescent human donor, that binds to the underside of the NA head. Our work provides previously unappreciated views on the dynamics of HA and NA, advancing the understanding of their interplay and suggesting possible strategies for the design of future vaccines and antivirals against influenza.

Conformational alteration in glycan induces phospholipase Cβ1 activation and angiogenesis

BACKGROUND

In endothelial cells, phospholipase C (PLC) β1-activated Ca²⁺ is a crucial second messenger for the signaling pathways governing angiogenesis. PLCβ1 is inactivated by complexing with an intracellular protein called translin-associated factor X (TRAX). This study demonstrates specific interactions between Globo H ceramide (GHCer) and TRAX, which highlight a new angiogenic control through PLCβ1 activation.

METHODS

Globo-series glycosphingolipids (GSLs), including GHCer and stage-specific embryonic antigen-3 ceramide (SSEA3Cer), were analyzed using enzyme-linked immunosorbent assay (ELISA) and Biacore for their binding with TRAX. Angiogenic activities of GSLs in human umbilical vein endothelial cells (HUVECs) were evaluated. Molecular dynamics (MD) simulation was used to study conformations of GSLs and their molecular interactions with TRAX. Fluorescence resonance energy transfer (FRET) analysis of HUVECs by confocal microscopy was used to validate the release of PLCβ1 from TRAX. Furthermore, the in vivo angiogenic activity of extracellular vesicles (EVs) containing GHCer was confirmed using subcutaneous Matrigel plug assay in mice.

RESULTS

The results of ELISA and Biacore analysis showed a stable complex between recombinant TRAX and synthetic GHCer with KD of 40.9 nM. In contrast, SSEA3Cer lacking a fucose residue of GHCer at the terminal showed ~ 1000-fold decrease in the binding affinity. These results were consistent with their angiogenic activities in HUVECs. The MD simulation indicated that TRAX interacted with the glycan moiety of GHCer at amino acid Q223, Q219, L142, S141, and E216. At equilibrium the stable complex maintained 4.6 ± 1.3 H-bonds. TRAX containing double mutations with Q223A and Q219A lost its ability to interact with GHCer in both MD simulation and Biacore assays. Removal of the terminal fucose from GHCer to become SSEA3Cer resulted in decreased H-bonding to 1.2 ± 1.0 by the MD simulation. Such specific H-bonding was due to the conformational alteration in the whole glycan which was affected by the presence or absence of the fucose moiety. In addition, ELISA, Biacore, and in-cell FRET assays confirmed the competition between GHCer and PLCβ1 for binding to TRAX. Furthermore, the Matrigel plug assay showed robust vessel formation in the plug containing tumor-secreted EVs or synthetic GHCer, but not in the plug with SSEA3Cer. The FRET analysis also indicated the disruption of colocalization of TRAX and PLCβ1 in cells by GHCer derived from EVs.

CONCLUSIONS

Overall, the fucose residue in GHCer dictated the glycan conformation for its complexing with TRAX to release TRAX-sequestered PLCβ1, leading to Ca²⁺ mobilization in endothelial cells and enhancing angiogenesis in tumor microenvironments.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.

Breathing and tilting: mesoscale simulations illuminate influenza glycoprotein vulnerabilities

Influenza virus has resurfaced recently from inactivity during the early stages of the COVID-19 pandemic, raising serious concerns about the nature and magnitude of future epidemics. The main antigenic targets of influenza virus are two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). Whereas the structural and dynamical properties of both glycoproteins have been studied previously, the understanding of their plasticity in the whole-virion context is fragmented. Here, we investigate the dynamics of influenza glycoproteins in a crowded protein environment through mesoscale all-atom molecular dynamics simulations of two evolutionary-linked glycosylated influenza A whole-virion models. Our simulations reveal and kinetically characterize three main molecular motions of influenza glycoproteins: NA head tilting, HA ectodomain tilting, and HA head breathing. The flexibility of HA and NA highlights antigenically relevant conformational states, as well as facilitates the characterization of a novel monoclonal antibody, derived from human convalescent plasma, that binds to the underside of the NA head. Our work provides previously unappreciated views on the dynamics of HA and NA, advancing the understanding of their interplay and suggesting possible strategies for the design of future vaccines and antivirals against influenza.

Multifaceted Computational Modeling in Glycoscience

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

Loss of core-fucosylation of SPARC impairs collagen binding and contributes to COPD

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease with high morbidity and mortality worldwide. Although several mechanisms to account for deleterious immune effects were proposed, molecular description for the underlying alveolar structural alterations for COPD is lacking. Here, silencing of α1,6-fucosyltransferase (Fut8), the enzyme for core-fucosylation and highly expressed in lung stem cells, resulted in alveolar structural changes in lung organoids, recapitulating COPD. Site-specific mass spectrometry analysis demonstrated that the secreted protein acidic and rich in cysteine (SPARC), which binds collagen, contains a core-fucosylation site in its VCSNDN^cfK glycopeptide. Biacore assay showed markedly reduced collagen binding of SPARC lacking core fucosylation. Molecular dynamics analysis revealed that core fucosylation of SPARC-induced dynamic conformational changes in its N-glycan, allowing terminal galactose and N-acetylglucosamine to interact with K150, P261 and H264 residues, thereby promoting collagen binding. Site-specific mutagenesis of these residues also resulted in low affinity for collagen binding. Moreover, loss of collagen and decline of core fucosylation were observed in COPD lung tissues. These findings provide a new mechanistic insight into the role of core fucosylation of SPARC in cell–matrix communication and contribution to the abnormal alveolar structures in COPD.

How molecular modelling can better broaden the understanding of glycosylations

Glycosylations are among the most ubiquitous post-translational modifications (PTMs) in proteins, and the effects of their perturbations are seen in various diseases such as cancers, diabetes and arthritis to name a few. Yet they remain one of the most enigmatic aspects of protein structure and function. On the other hand, molecular modelling techniques have been rapidly bridging this knowledge gap since the last decade. In this review, we discuss how these techniques have proven to be indispensable for a better understanding of the role of glycosylations in glycoprotein structure and function.

prepareforleap: An automated tool for fast PDB-to-parameter generation

Setting up molecular dynamics simulations from experimentally determined structures is often complicated by a variety of factors, particularly the inclusion of carbohydrates, since these have several anomer types which can be linked in a variety of ways. Here we present a stand-alone tool implemented in the widely-used software CPPTRAJ that can be used to automate building structures and generating a "ready to run" parameter and coordinate file pair. This tool automatically identifies carbohydrate anomer type, configuration, linkage, and functional groups, and performs topology modifications (e.g., renaming residue/atom names) required to build the final system using state of the art GLYCAM force field parameters. It will also generate the necessary commands for bonding carbohydrates and creating any disulfide bonds.

Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that provides 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating realistic coordinates for polymer melt simulations, single-stranded as well as circular single-stranded DNA. We further demonstrate the power of our approach by setting up a microphase-separated block copolymer system, and by generating a liquid-liquid phase separated system inside a lipid vesicle.

Structural and Functional Analysis of Female Sex Hormones against SARS-CoV-2 Cell Entry

Emerging evidence suggests that males are more susceptible to severe infection by the SARS-CoV-2 virus than females. A variety of mechanisms may underlie the observed gender-related disparities including differences in sex hormones. However, the precise mechanisms by which female sex hormones may provide protection against SARS-CoV-2 infectivity remains unknown. Here we report new insights into the molecular basis of the interactions between the SARS-CoV-2 spike (S) protein and the human ACE2 receptor. We further report that glycosylation of the ACE2 receptor enhances SARS-CoV-2 infectivity. Importantly, estrogens can disrupt glycan-glycan interactions and glycan-protein interactions between the human ACE2 and the SARS-CoV-2 thereby blocking its entry into cells. In a mouse model of COVID-19, estrogens reduced ACE2 glycosylation and thereby alveolar uptake of the SARS-CoV-2 spike protein. These results shed light on a putative mechanism whereby female sex hormones may provide protection from developing severe infection and could inform the development of future therapies against COVID-19.

N-Glycosylation Enhances Conformational Flexibility of Protein Disulfide Isomerase Revealed by Microsecond Molecular Dynamics and Markov State Modeling

Secreted proteins of eukaryotes are decorated with branched carbohydrate oligomers called glycans. This fact is only starting to be considered for in silico investigations of protein dynamics. Using all-atom molecular dynamics (MD) simulations and Markov state modeling (MSM), we unveil the influence of glycans on the conformational flexibility of the multidomain protein disulfide isomerase (PDI), which is a ubiquitous chaperone in the endoplasmic reticulum (ER). Yeast PDI (yPDI) from Saccharomyces cerevisiae is glycosylated at asparagine side chains and the knowledge of its five modified sites enables a realistic computational modeling. We compare simulations of glycosylated and unglycosylated yPDI and find that the presence of glycan-glycan and glycan-protein interactions influences the flexibility of PDI in different ways. For example, glycosylation reduces interdomain interactions, shifting the conformational ensemble toward more open, extended structures. In addition, we compare our results on yPDI with structural information of homologous proteins such as human PDI (hPDI), which is natively unglycosylated. Interestingly, hPDI lacks a surface recess that is present in yPDI. We find that glycosylation of yPDI facilitates its catalytic site to reach close to this surface recess. Hence, this might point to a possible functional relevance of glycosylation in yeast to act on substrates, while glycosylation seems redundant for the human homologous protein. We conclude that glycosylation is fundamental for protein dynamics, making it a necessity for a truthful representation of the flexibility and function in in silico studies of glycoproteins.

Determination of intermediate state structures in the opening pathway of SARS-CoV-2 spike using cryo-electron microscopy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of COVID-19, a highly infectious disease that is severely affecting our society and welfare systems. In order to develop therapeutic interventions against this condition, one promising strategy is to target spike, the trimeric transmembrane glycoprotein that the virus uses to recognise and bind its host cells. Here we use a metainference cryo-electron microscopy approach to determine the opening pathway that brings spike from its inactive (closed) conformation to its active (open) one. The knowledge of the structures of the intermediate states of spike along this opening pathway enables us to identify a cryptic pocket that is not exposed in the open and closed states. These results underline the opportunities offered by the determination of the structures of the transient intermediate states populated during the dynamics of proteins to allow the therapeutic targeting of otherwise invisible cryptic binding sites.

A structural ensemble derived from cryo-electron microscopy reveals a cryptic pocket site in intermediate states along the opening pathway of the SARS-CoV-2 spike protein.

Glycan-protein interactions determine kinetics of N-glycan remodeling

A hallmark of N-linked glycosylation in the secretory compartments of eukaryotic cells is the sequential remodeling of an initially uniform oligosaccharide to a site-specific, heterogeneous ensemble of glycostructures on mature proteins. To understand site-specific processing, we used protein disulfide isomerase (PDI), a model protein with five glycosylation sites, for molecular dynamics (MD) simulations and compared the result to a biochemical in vitro analysis with four different glycan processing enzymes. As predicted by an analysis of the accessibility of the N-glycans for their processing enzymes derived from the MD simulations, N-glycans at different glycosylation sites showed different kinetic properties for the processing enzymes. In addition, altering the tertiary structure of the glycoprotein PDI affected its N-glycan remodeling in a site-specific way. We propose that the observed differential N-glycan reactivities depend on the surrounding protein tertiary structure and lead to different glycan structures in the same protein through kinetically controlled processing pathways.

Atomistic glycoprotein simulations reveal a site-specific availability of glycan substrates in time-resolved mass spectrometry of maturating enzyme kinetics.

N-Glycosylation can selectively block or foster different receptor-ligand binding modes

While DNA encodes protein structure, glycans provide a complementary layer of information to protein function. As a prime example of the significance of glycans, the ability of the cell surface receptor CD44 to bind its ligand, hyaluronan, is modulated by N-glycosylation. However, the details of this modulation remain unclear. Based on atomistic simulations and NMR, we provide evidence that CD44 has multiple distinct binding sites for hyaluronan, and that N-glycosylation modulates their respective roles. We find that non-glycosylated CD44 favors the canonical sub-micromolar binding site, while glycosylated CD44 binds hyaluronan with an entirely different micromolar binding site. Our findings show (for the first time) how glycosylation can alter receptor affinity by shielding specific regions of the host protein, thereby promoting weaker binding modes. The mechanism revealed in this work emphasizes the importance of glycosylation in protein function and poses a challenge for protein structure determination where glycosylation is usually neglected.

A functional antibody cross-reactive to both human and murine cytotoxic T-lymphocyte-associated protein 4 via binding to an N-glycosylation epitope

Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4, CD152) is a receptor on T cells that inhibits the cell’s functions. Blocking CTLA-4 with an antibody has proven effective for the treatment of cancer patients. Anti-CTLA-4 antibodies currently approved for clinical use can bind to human CTLA-4, but do not cross-react to murine CTLA-4. Here, we report the generation and characterization of a functional humanized antibody, mAb146, against both human and murine CTLA-4. Alanine scanning of CTLA-4 using mammalian cell expression cassette identified the unique epitopes of this novel antibody. In addition to the amino acid residues interacting with ligands CD80 and CD86, an N-glycosylation site on N110, conserved in CTLA-4 of human, monkey, and mouse, was identified as the specific epitope that might contribute to the cross-species binding and function of this antibody. This finding may also contribute to the understanding of the glycosylation of CTLA-4 and its related biologic function. In addition to facilitating preclinical development of anti-CTLA-4 antibodies, mAb146 may be useful as a therapeutic agent.

Multiscale modelling investigation of wood modification with acetic anhydride

Density functional theory (DFT) and molecular dynamics (MD) simulations were employed to investigate the interaction of cellulose and lignin with acetic anhydride for explaining the wood modification process. Cellulose was modelled with a cellobiose unit and dibenzodioxocin was used to represent the lignin model. Results obtained from both methods revealed that acetic anhydride interacted substantially more with the cellobiose model than the lignin model. The interaction energy of cellobiose-acetic anhydride was higher (about 20 kJ mol-1) than that of lignin-acetic anhydride. DFT results on hydrogen bonding indicated that the hydroxyl group from cellobiose and the aromatic hydroxyl group from lignin models have similar energy values, which explain the equal strength of hydrogen bond interaction. The same trend was also obtained for the substitution of acetyl group in the hydroxyl group. MD results have also predicted that acetic anhydride forms a stronger interaction with cellobiose than with the lignin model, and these findings were in agreement with the DFT results.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

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

Comparative ligand structural analytics illustrated on variably glycosylated MUC1 antigen-antibody binding

When faced with the investigation of the preferential binding of a series of ligands against a known target, the solution is not always evident from single structure analysis. An ensemble of structures generated from computer simulations is valuable; however, visual analysis of the extensive structural data can be overwhelming. Rapid analysis of trajectory data, with tools available in the Galaxy platform, can be used to understand key features and compare differences that inform the preferential ligand structure that favors binding. We illustrate this informatics approach by investigating the in-silico binding of a peptide and glycopeptide epitope of the glycoprotein Mucin 1 (MUC1) binding with the antibody AR20.5. To study the binding, we performed molecular dynamics simulations using OpenMM and then used the Galaxy platform for data analysis. The same analysis tools are applied to each of the simulation trajectories and this process was streamlined by using Galaxy workflows. The conformations of the antigens were analyzed using root-mean-square deviation, end-to-end distance, Ramachandran plots, and hydrogen bonding analysis. Additionally, RMSF and clustering analysis were carried out. These analyses were used to rapidly assess key features of the system, interrogate the dynamic structure of the ligand, and determine the role of glycosylation on the conformational equilibrium. The glycopeptide conformations in solution change relative to the peptide; thus a partially pre-structuring is seen prior to binding. Although the bound conformation of peptide and glycopeptide is similar, the glycopeptide fluctuates less and resides in specific conformers for more extended periods. This structural analysis which gives a high-level view of the features in the system under observation, could be readily applied to other binding problems as part of a general strategy in drug design or mechanistic analysis.

Modeling PrPSc Generation Through Deformed Templating

Deformed templating is the process by which self-replicating protein conformations with a given cross-β folding pattern can seed formation of an alternative self-replicating state with different cross-β folding pattern. In particular, uninfectious but propagative PrP amyloid can transform into a bona fide infectious conformer, PrP^Sc through deformed templating. The process can take many rounds of replication (if taking place in vitro) or even several passages of the evolving PrP conformers through successive brains if in vivo, through experimental transmission. In all cases, deformed templating involves a forced conversion in which there is a mismatch between the template and the substrate and/or the templating environment, typically a recombinant PrP amyloid, adept at converting recombinant PrP under denaturing conditions (e.g., presence of chaotropic agents), encountering a glycosylated, GPI-anchored PrP^C substrate under physiological conversion conditions. Deformed templating is characterized by emergence of intermediate conformers that exhibit biochemical characteristics that are intermediate between those of the initial PrP amyloid and the final PrP^Sc conformers. Here, we took advantage of the recent elucidation of the structure of a PrP amyloid by cryo-EM and the availability of a physically plausible atomistic model of PrP^Sc that we have recently proposed. Using modeling and Molecular Dynamics (MD) approaches, we built a complete molecular modelization of deformed templating, including an atomistic model of a glycosylated intermediate conformer and a modified model of PrP^Sc. Among other unanticipated outcomes, our results show that fully glycosylated PrP can be stacked in-register, and how 4-rung β-solenoid (4RβS) PrP architectures can share key structural motifs with parallel-in register intermolecular sheet (PIRIBS) PrP amyloids. Our results shed light on the mechanisms of prion replication.

Cholesterol binding to the sterol-sensing region of Niemann Pick C1 protein confines dynamics of its N-terminal domain

Lysosomal accumulation of cholesterol is a hallmark of Niemann Pick type C (NPC) disease caused by mutations primarily in the lysosomal membrane protein NPC1. NPC1 contains a transmembrane sterol-sensing domain (SSD), which is supposed to regulate protein activity upon cholesterol binding, but the mechanisms underlying this process are poorly understood. Using atomistic simulations, we show that in the absence of cholesterol in the SSD, the luminal domains of NPC1 are highly dynamic, resulting in the disengagement of the NTD from the rest of the protein. The disengaged NPC1 adopts a flexed conformation that approaches the lipid bilayer, and could represent a conformational state primed to receive a sterol molecule from the soluble lysosomal cholesterol carrier NPC2. The binding of cholesterol to the SSD of NPC1 allosterically suppresses the conformational dynamics of the luminal domains resulting in an upright NTD conformation. The presence of an additional 20% cholesterol in the membrane has negligible impact on this process. The additional presence of an NTD-bound cholesterol suppresses the flexing of the NTD. We propose that cholesterol acts as an allosteric effector, and the modulation of NTD dynamics by the SSD-bound cholesterol constitutes an allosteric feedback mechanism in NPC1 that controls cholesterol abundance in the lysosomal membrane.

Cholesterol is absorbed from LDL particles in esterified form, and is broken down to free cholesterol in the lysosomes of cells, from where cholesterol must be transported to other cellular compartments such as the plasma membrane. The Niemann Pick type C (NPC) diseases arise from deficient cholesterol transport and result from mutations in the cholesterol transport protein NPC1. Using computer simulations, we show that cholesterol, when bound to one part of NPC1, can control the structural transitions of an 8-nm distant, different part of NPC1 protein called the N-terminal domain (NTD). Such long-range control of protein conformations (allostery), controls a wide range of cellular functions mediated by proteins. Fundamental molecular insights into the function of the NPC1 protein can potentially lead to better pharmaceutical interventions for the NPC diseases.

Computational tools for drawing, building and displaying carbohydrates: a visual guide

Drawing and visualisation of molecular structures are some of the most common tasks carried out in structural glycobiology, typically using various software. In this perspective article, we outline developments in the computational tools for the sketching, visualisation and modelling of glycans. The article also provides details on the standard representation of glycans, and glycoconjugates, which helps the communication of structure details within the scientific community. We highlight the comparative analysis of the available tools which could help researchers to perform various tasks related to structure representation and model building of glycans. These tools can be useful for glycobiologists or any researcher looking for a ready to use, simple program for the sketching or building of glycans.

Dissecting the conformation of glycans and their interactions with proteins

The use of in silico strategies to develop the structural basis for a rational optimization of glycan-protein interactions remains a great challenge. This problem derives, in part, from the lack of technologies to quantitatively and qualitatively assess the complex assembling between a glycan and the targeted protein molecule. Since there is an unmet need for developing new sugar-targeted therapeutics, many investigators are searching for technology platforms to elucidate various types of molecular interactions within glycan-protein complexes and aid in the development of glycan-targeted therapies. Here we discuss three important technology platforms commonly used in the assessment of the complex assembly of glycosylated biomolecules, such as glycoproteins or glycosphingolipids: Biacore analysis, molecular docking, and molecular dynamics simulations. We will also discuss the structural investigation of glycosylated biomolecules, including conformational changes of glycans and their impact on molecular interactions within the glycan-protein complex. For glycoproteins, secreted protein acidic and rich in cysteine (SPARC), which is associated with various lung disorders, such as chronic obstructive pulmonary disease (COPD) and lung cancer, will be taken as an example showing that the core fucosylation of N-glycan in SPARC regulates protein-binding affinity with extracellular matrix collagen. For glycosphingolipids (GSLs), Globo H ceramide, an important tumor-associated GSL which is being actively investigated as a target for new cancer immunotherapies, will be used to demonstrate how glycan structure plays a significant role in enhancing angiogenesis in tumor microenvironments.

Atomistic structure and dynamics of the human MHC-I peptide-loading complex

The major histocompatibility complex class-I (MHC-I) peptide-loading complex (PLC) is a cornerstone of the human adaptive immune system, being responsible for processing antigens that allow killer T cells to distinguish between healthy and compromised cells. Based on a recent low-resolution cryo-electron microscopy (cryo-EM) structure of this large membrane-bound protein complex, we report an atomistic model of the PLC and study its conformational dynamics on the multimicrosecond time scale using all-atom molecular dynamics (MD) simulations in an explicit lipid bilayer and water environment (1.6 million atoms in total). The PLC has a layered structure, with two editing modules forming a flexible protein belt surrounding a stable, catalytically active core. Tapasin plays a central role in the PLC, stabilizing the MHC-I binding groove in a conformation reminiscent of antigen-loaded MHC-I. The MHC-I-linked glycan steers a tapasin loop involved in peptide editing toward the binding groove. Tapasin conformational dynamics are also affected by calreticulin through a conformational selection mechanism that facilitates MHC-I recruitment into the complex.

Structural and functional analysis of female sex hormones against SARS-Cov2 cell entry

Emerging evidence suggests that males are more susceptible to severe infection by the SARS-CoV-2 virus than females. A variety of mechanisms may underlie the observed gender-related disparities including differences in sex hormones. However, the precise mechanisms by which female sex hormones may provide protection against SARS-CoV-2 infectivity remains unknown. Here we report new insights into the molecular basis of the interactions between the SARS-CoV-2 spike (S) protein and the human ACE2 receptor. We further observed that glycosylation of the ACE2 receptor enhances SARS-CoV-2 infectivity. Importantly estrogens can disrupt glycan-glycan interactions and glycan-protein interactions between the human ACE2 and the SARS-CoV2 thereby blocking its entry into cells. In a mouse model, estrogens reduced ACE2 glycosylation and thereby alveolar uptake of the SARS-CoV-2 spike protein. These results shed light on a putative mechanism whereby female sex hormones may provide protection from developing severe infection and could inform the development of future therapies against COVID-19.

Cryo-EM structure of the complete and ligand-saturated insulin receptor ectodomain

Glucose homeostasis and growth essentially depend on the hormone insulin engaging its receptor. Despite biochemical and structural advances, a fundamental contradiction has persisted in the current understanding of insulin ligand-receptor interactions. While biochemistry predicts two distinct insulin binding sites, 1 and 2, recent structural analyses have resolved only site 1. Using a combined approach of cryo-EM and atomistic molecular dynamics simulation, we present the structure of the entire dimeric insulin receptor ectodomain saturated with four insulin molecules. Complementing the previously described insulin-site 1 interaction, we present the first view of insulin bound to the discrete insulin receptor site 2. Insulin binding stabilizes the receptor ectodomain in a T-shaped conformation wherein the membrane-proximal domains converge and contact each other. These findings expand the current models of insulin binding to its receptor and of its regulation. In summary, we provide the structural basis for a comprehensive description of ligand-receptor interactions that ultimately will inform new approaches to structure-based drug design.

Identifying Drug Targets in Pancreatic Ductal Adenocarcinoma Through Machine Learning, Analyzing Biomolecular Networks, and Structural Modeling

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death and has an extremely poor prognosis. Thus, identifying new disease-associated genes and targets for PDAC diagnosis and therapy is urgently needed. This requires investigations into the underlying molecular mechanisms of PDAC at both the systems and molecular levels. Herein, we developed a computational method of predicting cancer genes and anticancer drug targets that combined three independent expression microarray datasets of PDAC patients and protein-protein interaction data. First, Support Vector Machine–Recursive Feature Elimination was applied to the gene expression data to rank the differentially expressed genes (DEGs) between PDAC patients and controls. Then, protein-protein interaction networks were constructed based on the DEGs, and a new score comprising gene expression and network topological information was proposed to identify cancer genes. Finally, these genes were validated by “druggability” prediction, survival and common network analysis, and functional enrichment analysis. Furthermore, two integrins were screened to investigate their structures and dynamics as potential drug targets for PDAC. Collectively, 17 disease genes and some stroma-related pathways including extracellular matrix-receptor interactions were predicted to be potential drug targets and important pathways for treating PDAC. The protein-drug interactions and hinge sites predication of ITGAV and ITGA2 suggest potential drug binding residues in the Thigh domain. These findings provide new possibilities for targeted therapeutic interventions in PDAC, which may have further applications in other cancer types.

Computer simulations of protein-membrane systems

The interactions between proteins and membranes play critical roles in signal transduction, cell motility, and transport, and they are involved in many types of diseases. Molecular dynamics (MD) simulations have greatly contributed to our understanding of protein-membrane interactions, promoted by a dramatic development of MD-related software, increasingly accurate force fields, and available computer power. In this chapter, we present available methods for studying protein-membrane systems with MD simulations, including an overview about the various all-atom and coarse-grained force fields for lipids, and useful software for membrane simulation setup and analysis. A large set of case studies is discussed.

Umbrella Visualization: A method of analysis dedicated to glycan flexibility with UnityMol

N-glycosylation is a post-translational modification heavily impacting protein functions. Some alterations of glycosylation, such as sialic acid hydrolysis, are related to protein dysfunction. Because of their high flexibility and the many reactive groups of the glycan chains, studying glycans with in vitro methods is a challenging task. Molecular dynamics is a useful tool and probably the only one in biology able to overcome this problem and gives access to conformational information through exhaustive sampling. To better decipher the impact of N-glycans, the analysis and visualization of their influence over time on protein structure is a prerequisite. We developed the Umbrella Visualization, a graphical method that assigns the glycan intrinsic flexibility during a molecular dynamics trajectory. The density plot generated by this method brought relevant informations regarding glycans dynamics and flexibility, but needs further development in order to integrate an accurate description of the protein topology and its interactions. We propose here to transform this analysis method into a visualization mode in UnityMol. UnityMol is a molecular editor, viewer and prototyping platform, coded in C#. The new representation of glycan chains presented in this study takes into account both the main positions adopted by each antenna of a glycan and their statistical relevance. By displaying the collected data on the protein surface, one is then able to investigate the protein/glycan interactions.

The current structural glycome landscape and emerging technologies

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

Comprehensive Evaluation of the Efficiency of Yeast Cell Wall Extract to Adsorb Ochratoxin A and Mitigate Accumulation of the Toxin in Broiler Chickens

Ochratoxin A (OTA) is a common mycotoxin contaminant in animal feed. When absorbed from the gastrointestinal tract, OTA has a propensity for pathological effects on animal health and deposition in animal tissues. In this study, the potential of yeast cell wall extracts (YCWE) to adsorb OTA was evaluated using an in vitro method in which consecutive animal digestion events were simulated. Low pH markedly increased OTA binding to YCWE, which was reversed with a pH increased to 6.5. Overall, in vitro analysis revealed that 30% of OTA was adsorbed to YCWE. Additional computational molecular modelling revealed that change in pH alters the OTA charge and modulates the interaction with the YCWE β-d-glucans. The effectiveness of YCWE was tested in a 14-day broiler chicken trial. Birds were subjected to five dietary treatments; with and without OTA, and OTA combined with YCWE at three dosages. At the end of the trial, liver OTA deposition was evaluated. Data showed a decrease of up to 30% in OTA deposits in the liver of broilers fed both OTA and YCWE. In the case of OTA, a tight correlation between the mitigation efficacy of YCWE between in vitro and in vivo model could be observed.

Removal of N-linked glycans in cellobiohydrolase Cel7A from Trichoderma reesei reveals higher activity and binding affinity on crystalline cellulose

BACKGROUND

Cellobiohydrolase from glycoside hydrolase family 7 is a major component of commercial enzymatic mixtures for lignocellulosic biomass degradation. For many years, Trichoderma reesei Cel7A (TrCel7A) has served as a model to understand structure-function relationships of processive cellobiohydrolases. The architecture of TrCel7A includes an N-glycosylated catalytic domain, which is connected to a carbohydrate-binding module through a flexible, O-glycosylated linker. Depending on the fungal expression host, glycosylation can vary not only in glycoforms, but also in site occupancy, leading to a complex pattern of glycans, which can affect the enzyme's stability and kinetics.

RESULTS

Two expression hosts, Aspergillus oryzae and Trichoderma reesei, were utilized to successfully express wild-types TrCel7A (WT _Ao and WT _Tr ) and the triple N-glycosylation site deficient mutants TrCel7A N45Q, N270Q, N384Q (ΔN-glyc _Ao and ΔN-glyc _Tr ). Also, we expressed single N-glycosylation site deficient mutants TrCel7A (N45Q _Ao , N270Q _Ao , N384Q _Ao ). The TrCel7A enzymes were studied by steady-state kinetics under both substrate- and enzyme-saturating conditions using different cellulosic substrates. The Michaelis constant (K _M ) was consistently found to be lowered for the variants with reduced N-glycosylation content, and for the triple deficient mutants, it was less than half of the WTs' value on some substrates. The ability of the enzyme to combine productively with sites on the cellulose surface followed a similar pattern on all tested substrates. Thus, site density (number of sites per gram cellulose) was 30-60% higher for the single deficient variants compared to the WT, and about twofold larger for the triple deficient enzyme. Molecular dynamic simulation of the N-glycan mutants TrCel7A revealed higher number of contacts between CD and cellulose crystal upon removal of glycans at position N45 and N384.

CONCLUSIONS

The kinetic changes of TrCel7A imposed by removal of N-linked glycans reflected modifications of substrate accessibility. The presence of N-glycans with extended structures increased K _M and decreased attack site density of TrCel7A likely due to steric hindrance effect and distance between the enzyme and the cellulose surface, preventing the enzyme from achieving optimal conformation. This knowledge could be applied to modify enzyme glycosylation to engineer enzyme with higher activity on the insoluble substrates.

Glycosylator: a Python framework for the rapid modeling of glycans

BACKGROUND

Carbohydrates are a class of large and diverse biomolecules, ranging from a simple monosaccharide to large multi-branching glycan structures. The covalent linkage of a carbohydrate to the nitrogen atom of an asparagine, a process referred to as N-linked glycosylation, plays an important role in the physiology of many living organisms. Most software for glycan modeling on a personal desktop computer requires knowledge of molecular dynamics to interface with specialized programs such as CHARMM or AMBER. There are a number of popular web-based tools that are available for modeling glycans (e.g., GLYCAM-WEB (http:// https://dev.glycam.org/gp/ ) or Glycosciences.db ( http://www.glycosciences.de/ )). However, these web-based tools are generally limited to a few canonical glycan conformations and do not allow the user to incorporate glycan modeling into their protein structure modeling workflow.

RESULTS

Here, we present Glycosylator, a Python framework for the identification, modeling and modification of glycans in protein structure that can be used directly in a Python script through its application programming interface (API) or through its graphical user interface (GUI). The GUI provides a straightforward two-dimensional (2D) rendering of a glycoprotein that allows for a quick visual inspection of the glycosylation state of all the sequons on a protein structure. Modeled glycans can be further refined by a genetic algorithm for removing clashes and sampling alternative conformations. Glycosylator can also identify specific three-dimensional (3D) glycans on a protein structure using a library of predefined templates.

CONCLUSIONS

Glycosylator was used to generate models of glycosylated protein without steric clashes. Since the molecular topology is based on the CHARMM force field, new complex sugar moieties can be generated without modifying the internals of the code. Glycosylator provides more functionality for analyzing and modeling glycans than any other available software or webserver at present. Glycosylator will be a valuable tool for the glycoinformatics and biomolecular modeling communities.

CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates

Characterizing glycans and glycoconjugates in the context of three-dimensional structures is important in understanding their biological roles and developing efficient therapeutic agents. Computational modeling and molecular simulation have become an essential tool complementary to experimental methods. Here, we present a computational tool, Glycan Modeler for in silico N-/O-glycosylation of the target protein and generation of carbohydrate-only systems. In our previous study, we developed Glycan Reader, a web-based tool for detecting carbohydrate molecules from a PDB structure and generation of simulation system and input files. As integrated into Glycan Reader in CHARMM-GUI, Glycan Modeler (Glycan Reader & Modeler) enables to generate the structures of glycans and glycoconjugates for given glycan sequences and glycosylation sites using PDB glycan template structures from Glycan Fragment Database (http://glycanstructure.org/fragment-db). Our benchmark tests demonstrate the universal applicability of Glycan Reader & Modeler to various glycan sequences and target proteins. We also investigated the structural properties of modeled glycan structures by running 2-μs molecular dynamics simulations of HIV envelope protein. The simulations show that the modeled glycan structures built by Glycan Reader & Modeler have the similar structural features compared to the ones solved by X-ray crystallography. We also describe the representative examples of glycoconjugate modeling with video demos to illustrate the practical applications of Glycan Reader & Modeler. Glycan Reader & Modeler is freely available at http://charmm-gui.org/input/glycan.

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.

CHARMM-GUI Membrane Builder for Complex Biological Membrane Simulations with Glycolipids and Lipoglycans

Glycolipids (such as glycoglycerolipids, glycosphingolipids, and glycosylphosphatidylinositol) and lipoglycans (such as lipopolysaccharides (LPS), lipooligosaccharides (LOS), mycobacterial lipoarabinomannan, and mycoplasma lipoglycans) are typically found on the surface of cell membranes and play crucial roles in various cellular functions. Characterizing their structure and dynamics at the molecular level is essential to understand their biological roles, but systematic generation of glycolipid and lipoglycan structures is challenging because of great variations in lipid structures and glycan sequences (i.e., carbohydrate types and their linkages). To facilitate the generation of all-atom glycolipid/LPS/LOS structures, we have developed Glycolipid Modeler and LPS Modeler in CHARMM-GUI ( http://www.charmm-gui.org ), a web-based interface that simplifies building of complex biological simulation systems. In addition, we have incorporated these modules into Membrane Builder so that users can readily build a complex symmetric or asymmetric biological membrane system with various glycolipids and LPS/LOS. These tools are expected to be useful in innovative and novel glycolipid/LPS/LOS modeling and simulation research by easing tedious and intricate steps in modeling complex biological systems and shall provide insight into structures, dynamics, and underlying mechanisms of complex glycolipid-/LPS-/LOS-containing biological membrane systems.

Glucosylceramide modifies the LPS-induced inflammatory response in macrophages and the orientation of the LPS/TLR4 complex in silico

Toll-like receptor 4 (TLR4) is activated by bacterial lipopolysaccharide (LPS), which drives the production of proinflammatory cytokines. Earlier studies have indicated that cholesterol- and glycosphingolipid-rich subregions of the plasma membrane (lipid domains) are important for TLR4-mediated signaling. We report that inhibition of glucosylceramide (GluCer) synthase, which resulted in decreased concentrations of the glycosphingolipid GluCer in lipid domains, reduced the LPS-induced inflammatory response in both mouse and human macrophages. Atomistic molecular dynamics simulations of the TLR4 dimer complex (with and without LPS in its MD-2 binding pockets) in membranes (in the presence and absence of GluCer) showed that: (1) LPS induced a tilted orientation of TLR4 and increased dimer integrity; (2) GluCer did not affect the integrity of the LPS/TLR4 dimer but reduced the LPS-induced tilt; and (3) GluCer increased electrostatic interactions between the membrane and the TLR4 extracellular domain, which could potentially modulate the tilt. We also showed that GCS inhibition reduced the interaction between TLR4 and the intracellular adaptor protein Mal. We conclude that the GluCer-induced effects on LPS/TLR4 orientation may influence the signaling capabilities of the LPS/TLR4 complex by affecting its interaction with downstream signaling proteins.

Recent development of boronic acid-based fluorescent sensors

As Lewis acids, boronic acids can bind with 1,2- or 1,3-diols in aqueous solution reversibly and covalently to form five or six cyclic esters, thus resulting in significant fluorescence changes. Based on this phenomenon, boronic acid compounds have been well developed as sensors to recognize carbohydrates or other substances. Several reviews in this area have been reported before, however, novel boronic acid-based fluorescent sensors have emerged in large numbers in recent years. This paper reviews new boron-based sensors from the last five years that can detect carbohydrates such as glucose, ribose and sialyl Lewis A/X, and other substances including catecholamines, reactive oxygen species, and ionic compounds. And emerging electrochemically related fluorescent sensors and functionalized boronic acid as new materials including nanoparticles, smart polymer gels, and quantum dots were also involved. By summarizing and discussing these newly developed sensors, we expect new inspiration in the design of boronic acid-based fluorescent sensors.

As Lewis acids, boronic acids can bind with 1,2- or 1,3-diols in aqueous solution reversibly and covalently to form five or six cyclic esters, thus resulting in significant fluorescence changes.