How and why plants and human N-glycans are different: Insight from molecular dynamics into the "glycoblocks" architecture of complex carbohydrates

Syntactic sugars: crafting a regular expression framework for glycan structures

Motivation

Structural analysis of glycans poses significant challenges in glycobiology due to their complex sequences. Research questions such as analyzing the sequence content of the α1-6 branch in N-glycans, are biologically meaningful yet can be hard to automate.

Results

Here, we introduce a regular expression system, designed for glycans, feature-complete, and closely aligned with regular expression formatting. We use this to annotate glycan motifs of arbitrary complexity, perform differential expression analysis on designated sequence stretches, or elucidate branch-specific binding specificities of lectins in an automated manner. We are confident that glycan regular expressions will empower computational analyses of these sequences.

Availability and implementation

Our regular expression framework for glycans is implemented in Python and is incorporated into the open-source glycowork package (version 1.1+). Code and documentation are available at https://github.com/BojarLab/glycowork/blob/master/glycowork/motif/regex.py.

Effects of glycans and hinge on dynamics in the IgG1 Fc

The crystallizable fragment (Fc) domain of immunoglobulin subclass IgG1 antibodies is engineered for a wide variety of pharmaceutical applications. Two important structural variables in Fc constructs are the hinge region connecting the Fc to the antigen binding fragments (Fab) and the glycans present in various glycoforms. These components affect receptor binding interactions that mediate immune activation. To design new antibody drugs, a robust in silico method for linking stability to structural changes is necessary. In this work, all-atom simulations were used to compare the dynamic behavior of the four structural variants arising from presence or absence of the hinge and glycans. We expressed the simplest of these constructs, the 'minimal Fc' with no hinge and no glycans, in Escherichia coli and report its crystal structure. The 'maximal Fc' that includes full hinge and G0F/G1F glycans is based on a previously reported structure, Protein Data Bank (PDB) ID: 5VGP. These, along with two intermediate structures (with only the glycans or with only the hinge) were used to independently measure the stability effects of the two structural variables using umbrella sampling simulations. Principal component analysis (PCA) was used to determine free energy effects along the Fc's dominant mode of motion. This work provides a comprehensive picture of the effects of hinge and glycans on Fc dynamics and stability.Communicated by Ramaswamy H. Sarma.

Identification and characterization of an α-1,3 mannosidase from Elizabethkingia meningoseptica and its potential attenuation impact on allergy associated with cross-reactive carbohydratedeterminant

Core α-1,3 mannose is structurally near the core xylose and core fucose on core pentasaccharide from plant and insect glycoproteins. Mannosidase is a useful tool for characterization the role of core α-1,3 mannose in the composition of glycan related epitope, especially for those epitopes in which core xylose and core fucose are involved. Through functional genomic analysis, we identified a glycoprotein α-1,3 mannosidase and named it MA3. We used MA3 to treat allergen horseradish peroxidase (HRP) and phospholipase A2 (PLA2) separately. The results showed that after MA3 removed α-1,3 mannose on HRP, the reactivity of HRP with anti-core xylose polyclonal antibody almost disappeared. And the reactivity of MA3-treated PLA2 with anti-core fucose polyclonal antibody decreased partially. In addition, when PLA2 was conducted enzyme digestion by MA3, the reactivity between PLA2 and allergic patients' sera diminished. These results demonstrated that α-1,3 mannose was an critical component of glycan related epitope.

On scientific understanding with artificial intelligence

An oracle that correctly predicts the outcome of every particle physics experiment, the products of every possible chemical reaction or the function of every protein would revolutionize science and technology. However, scientists would not be entirely satisfied because they would want to comprehend how the oracle made these predictions. This is scientific understanding, one of the main aims of science. With the increase in the available computational power and advances in artificial intelligence, a natural question arises: how can advanced computational systems, and specifically artificial intelligence, contribute to new scientific understanding or gain it autonomously? Trying to answer this question, we adopted a definition of 'scientific understanding' from the philosophy of science that enabled us to overview the scattered literature on the topic and, combined with dozens of anecdotes from scientists, map out three dimensions of computer-assisted scientific understanding. For each dimension, we review the existing state of the art and discuss future developments. We hope that this Perspective will inspire and focus research directions in this multidisciplinary emerging field.

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.

Molecular simulations of complex carbohydrates and glycoconjugates

Complex carbohydrates (glycans) are the most abundant and versatile biopolymers in nature. The broad diversity of biochemical functions that carbohydrates cover is a direct consequence of the variety of 3D architectures they can adopt, displaying branched or linear arrangements, widely ranging in sizes, and with the highest diversity of building blocks of any other natural biopolymer. Despite this unparalleled complexity, a common denominator can be found in the glycans' inherent flexibility, which hinders experimental characterization, but that can be addressed by high-performance computing (HPC)-based molecular simulations. In this short review, I present and discuss the state-of-the-art of molecular simulations of complex carbohydrates and glycoconjugates, highlighting methodological strengths and weaknesses, important insights through emblematic case studies, and suggesting perspectives for future developments.

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.

Conformational preferences of triantennary and tetraantennary hybrid N-glycans in aqueous solution: Insights from 20 μs long atomistic molecular dynamic simulations

In the current study, we have investigated the conformational dynamics of a triantennary (N-glycan1) and tetraantennary (N-glycan2) hybrid N-glycans found on the surface of the HIV glycoprotein using 20 μs long all-atom molecular dynamics (MD) simulations. The main objective of the present study is to elucidate the influence of adding a complex branch on the overall glycan structural dynamics. Our investigation suggests that the average RMSD value increases when a complex branch is added to N-glycan1. However, the RMSD distribution is relatively wider in the case of N-glycan1 compared to N-glycan2, which indicates that multiple complex branches restrict the conformational variability of glycans. A similar observation is obtained from the principal component analysis of both glycans. All the puckering states (⁴C₁ to ¹C₄) of each monosaccharide except mannose are sampled in our simulations, although the ⁴C₁ chair form is energetically more favorable than ¹C₄. In N-glycan1, the 1-6 linkage in the mannose branch [Man(9)-α(1-6)-Man(5)] stays in the gauche-gauche cluster, whereas it moves towards trans-gauche in N-glycan2. For both glycans, mannose branches are more flexible than the complex branches, and adding a complex branch does not influence the dynamics of the mannose branches. We have noticed that the end-to-end distance of the complex branch shortens by ∼ 10 Å in the presence of another complex branch. This suggests that in the presence of an additional complex branch, the other complex branch adopts a close folded structure. All these conformational changes involve the selective formation of inter-residue and water-mediated hydrogen-bond networks.

Changes in glycosyl inositol phosphoceramides during the cell cycle of the red alga Galdieria sulphuraria

Sphingolipids are significant component of plant-cell plasma membranes, as well as algal membranes, and mediate various biological processes. One of these processes is the change in lipid content during the cell cycle. This change is key to understanding cell viability and proliferation. There are relatively few papers describing highly glycosylated glycosyl inositol phosphorylceramide (GIPC) due to problems associated with the extractability of GIPCs and their analysis, especially in algae. After alkaline hydrolysis of total lipids from the red alga Galdieria sulphuraria, GIPCs were measured by high-resolution tandem mass spectrometry and fragmentation of precursor ions in an Orbitrap mass spectrometer in order to elucidate the structures of molecular species. Fragmentation experiments such as tandem mass spectrometry in the negative ion mode were performed to determine both the ceramide group and polar head structures. Measurement of mass spectra in the negative regime was possible because the phosphate group stabilizes negative molecular ions [M-H]^-. ANALYSIS: of GIPCs at various stages of the cell cycle provided information on their abundance. It was found that, depending on the phases of the cell cycle, in particular during division, the uptake of all three components of GIPC, i.e., long-chain amino alcohols, fatty acids, and polar heads, changes. Structural modifications of the polar headgroup significantly increased the number of molecular species. Analysis demonstrated a convex characteristic for molecular species with only one saccharide (hexose or hexuronic acid) as the polar head. For two carbohydrates, the course of Hex-HexA was linear, while for HexA-HexA it was concave. The same was true for GIPC with three and four monosaccharides.

The Role of Fucose-Containing Glycan Motifs Across Taxonomic Kingdoms

The extraordinary diversity of glycans leads to large differences in the glycomes of different kingdoms of life. Yet, while most monosaccharides are solely found in certain taxonomic groups, there is a small set of monosaccharides with widespread distribution across nearly all domains of life. These general monosaccharides are particularly relevant for glycan motifs, as they can readily be used by commensals and pathogens to mimic host glycans or hijack existing glycan recognition systems. Among these, the monosaccharide fucose is especially interesting, as it frequently presents itself as a terminal monosaccharide, primed for interaction with proteins. Here, we analyze fucose-containing glycan motifs across all taxonomic kingdoms. Using a hereby presented large species-specific glycan dataset and a plethora of methods for glycan-focused bioinformatics and machine learning, we identify characteristic as well as shared fucose-containing glycan motifs for various taxonomic groups, demonstrating clear differences in fucose usage. Even within domains, fucose is used differentially based on an organism’s physiology and habitat. We particularly highlight differences in fucose-containing motifs between vertebrates and invertebrates. With the example of pathogenic and non-pathogenic Escherichia coli strains, we also demonstrate the importance of fucose-containing motifs in molecular mimicry and thereby pathogenic potential. We envision that this study will shed light on an important class of glycan motifs, with potential new insights into the role of fucosylated glycans in symbiosis, pathogenicity, and immunity.

Rapid Automated Annotation and Analysis of N-Glycan Mass Spectrometry Imaging Data Sets Using NGlycDB in METASPACE

Imaging N-glycan spatial distribution in tissues using mass spectrometry imaging (MSI) is emerging as a promising tool in biological and clinical applications. However, there is currently no high-throughput tool for visualization and molecular annotation of N-glycans in MSI data, which significantly slows down data processing and hampers the applicability of this approach. Here, we present how METASPACE, an open-source cloud engine for molecular annotation of MSI data, can be used to automatically annotate, visualize, analyze, and interpret high-resolution mass spectrometry-based spatial N-glycomics data. METASPACE is an emerging tool in spatial metabolomics, but the lack of compatible glycan databases has limited its application for comprehensive N-glycan annotations from MSI data sets. We created NGlycDB, a public database of N-glycans, by adapting available glycan databases. We demonstrate the applicability of NGlycDB in METASPACE by analyzing MALDI-MSI data from formalin-fixed paraffin-embedded (FFPE) human kidney and mouse lung tissue sections. We added NGlycDB to METASPACE for public use, thus, facilitating applications of MSI in glycobiology.

Oligomannose N-Glycans 3D Architecture and Its Response to the FcγRIIIa Structural Landscape

Oligomannoses are evolutionarily the oldest class of N-glycans, where the arms of the common pentasaccharide unit, i.e., Manα(1-6)-[Manα(1-3)]-Manβ(1-4)-GlcNAcβ(1-4)-GlcNAcβ1-Asn, are functionalized exclusively with branched arrangements of mannose (Man) monosaccharide units. In mammalian species oligomannose N-glycans can have up to 9 Man; meanwhile structures can grow to over 200 units in yeast mannan. The highly dynamic nature, branching complexity, and 3D structure of oligomannoses have been recently highlighted for their roles in immune escape and infectivity of enveloped viruses, such as HIV-1 and SARS-CoV2. The architectural features that allow these N-glycans to perform their functions are yet unclear, due to their intrinsically disordered nature that hinders their structural characterization. In this work we will discuss the results of over 54 μs of cumulative sampling by molecular dynamics (MD) simulations of differently processed, free (not protein-linked) oligomannose N-glycans common in vertebrates. We then discuss the effects of a protein surface on their structural equilibria based on over 4 μs cumulative MD sampling of the fully glycosylated CD16a Fc γ receptor (FcγRIIIa), where the type of glycosylation is known to modulate its binding affinity for IgG1s, regulating the antibody-dependent cellular cytotoxicity (ADCC). Our results show that the protein's structural constraints shift the oligomannoses conformational ensemble to promote conformers that satisfy the steric requirements and hydrogen bonding networks demanded by the protein's surface landscape. More importantly, we find that the protein does not actively distort the N-glycans into structures not populated in the unlinked forms in solution. Ultimately, the highly populated conformations of the Man5 linked glycans support experimental evidence of high levels of hybrid complex forms at N45 and show a specific presentation of the arms at N162, which may be involved in mediating binding affinity to the IgG1 Fc.