Biology subjects

Fadda, E.

Publications and source records attributed to Fadda, E..

18 recordsLinked to original sources

bioRxiv2026

How the terminal glucoside of the N-glycan donor affects the catalytic efficiency of the eukaryotic oligosaccharyltransferase

The eukaryotic oligosaccharyltransferase (OST) is the enzyme responsible for initiating N-glycosylation of secreted proteins by transferring a pre-assembled lipid-linked oligosaccharide (LLO) donor to target asparagine residues most often found within N-x-S/T consensus sequences, or sequons. OST preferentially selects LLO donors with a distinctive glucoside Glc-(1-2)-Glc-(1-3)-Glc-(1-3)-capping the A-branch. After the N-glycosylation reaction, this motif is cleaved in a stepwise manner from the immature N-glycan structure before the folded glycoprotein exits the endoplasmic reticulum quality control (ERQC) cycle. While the -Glc-(1-3)-Glc-(1-3)-disaccharide is an important flag regulating binding to the calreticulin/calnexin chaperones, the terminal Glc-(1-2)-is removed immediately after OST catalysis, suggesting that its biological function may be directly linked to the OST catalytic efficiency. To understand how and why this capping motif affects the OST N-glycosylation efficiency, we rebuilt 3D models of the yeast OST in complex with an acceptor peptide and LLO donors substrates with and without terminal Glc-(1-2)-, and analysed their stability and dynamics with all-atom molecular dynamics (MD) simulations through both conventional, and Gaussian-accelerated (GaMD) sampling schemes. Our results indicate that the terminal Glc-(1-2)-is essential to anchor the full-length LLO donor to the OST through a complex network of intermolecular contacts extending from the catalytic site to distal subdomains. We show how this contact network is crucial to preserve the LLO catalytically productive alignment of its reducing end. We also show that the removal of the terminal Glc-(1-2)-leads to an increased flexibility of the LLO, which displaces the reducing end and redistributes the conformational ensemble towards misaligned states, which are less catalytically productive. These results provide a mechanistic basis linking the catalytic efficiency of the eukaryotic OST to the distinctive glucosylated structure of the LLO donor.

biophysics↗

bioRxiv2026

Integrating glycosylation in de novo protein design with ReGlyco Binder Design Filter

Artificial Intelligence (AI)-based methods for 3D protein structure prediction are revolutionising structural biology, rapidly giving users a 3D perspective on any molecular architecture and protein-protein interaction (PPI) virtually on-demand. Regardless of the inherent limitations of the various methods to date, the continuous improvement of the algorithms, and the broad availability of open access (OA) web servers, software packages and databases are bound to accelerate biopharmaceuticals discovery. Within this context, the development of computational pipelines for the de novo design of target-specific protein binders is especially exciting. As it stands, these processes are still rather inefficient and expensive, rapidly outputting thousands of designs relatively quickly, which translate into meagre yields. Here we show how the explicit integration of glycosylation as a filter in the 3D de novo design pipeline of biologics can significantly improve efficiency and reduce laboratory costs with minimal additional computational resources. As a proof-of-concept, we used the GlycoShape database and ReGlyco tools (https://glycoshape.org) to filter the results of an open competition launched by Adaptyv Bio in October 2025 for the design of binders as inhibitors against the heavily glycosylated Nipah virus glycoprotein (NiV-G) (https://proteinbase.com/competitions/adaptyv-nipah-competition). Screening of the 1,201 selected designs in block with ReGlyco allows users to eliminate 20% of the confirmed non-binders from the pool in approximately 3 hours on a dual-core CPU. Refinement with a rotamer search enabled flags 11% of non-binders prior to experiment and catches all but 5 confirmed binders from the given predicted 3D complexes. The availability of alternative binding poses improves this score. We complement this analysis with a demo OA colab notebook (https://colab.research.google.com/github/Ojas-Singh/GlycoShape-Resources/blob/main/colab/ReGlyco_Binder_Design_filter.ipynb) to illustrate our workflow. In this demo users can design mini binders against human erythropoietin (hEPO) by integrating GlycoShape resources with the RFdiffusion3 (RFD3) pipeline from the Institute for Protein Design (IDP).

bioinformatics↗

bioRxiv2025

The Ligand Preference of LRP1 is Regulated by O-glycans

Low-density lipoprotein receptor (LDLR) and LDLR-related proteins (LRPs) are endocytic receptors serving as essential physiological regulators of multiple processes including cholesterol clearance, protein reabsorption and neuronal protein trafficking. We originally discovered O-glycans in linkers of the ligand-binding domains of LDLR/LRP receptors and showed that these play critical roles for uptake of LDL by LDLR and albumin by LRP2. Remarkably, these linker O-glycans are introduced exclusively by GALNT11, one out of 20 polypeptide GalNAc-transferase isoenzymes. Here, we investigate the role of linker O-glycans on the large ([~]600 kDa) and widely expressed multiligand LRP1 receptor implicated in diseases including neuropathies. In genetically engineered cell models we activated endogenous full-coding LRP1 with and without O-glycans and demonstrate that while the uptake of certain ligands, such as RAP and ApoE, was unaffected by O-glycans, the uptake of the neurotoxic molecules tau and amyloid beta was altered and in opposite directions. This demonstrates that O-glycans in ligand-binding domains can differentially modulate ligand affinity and specificity of LRP1. Our findings highlight an overlooked regulatory mechanism of endocytic receptors and identify the ligand repertoire of LRP1 as being influenced by O-glycans, with potential implications for neurodegenerative disease.

molecular biology↗

bioRxiv2025

Regulation of N-glycosylation efficiency by eukaryotic oligosaccharyltransferase

Oligosaccharyltransferase (OST) catalyses the key step of N-glycosylation, transferring immature N-glycans to select Asn residues in nascent proteins in the endoplasmic reticulum (ER). Asn are more likely to be glycosylated in the context of a "glycosylation sequon", N-x-S/T (x=P), but not every sequon is glycosylated. Tight positive and negative regulation of site-specific N-glycosylation across the glycoproteome is essential because some Asn require glycosylation for productive protein folding or function, while others must remain unglycosylated. Despite its importance, the underlying bases for this regulation are illdefined. Here we characterise the molecular determinants regulating OST catalytic efficiency. We identify preferred substrates of OST, and show that the local sequence determines glycosylation efficiency by fine-tuning binding to an extended groove in OST along an eight residue stretch centered at the Asn acceptor. Tight control of OST activity is achieved through a switch, set ON when a peptide binds with high complementarity to the groove, triggering release of the assisting base Glu350 for catalysis. Based on analysis of buried sequons, we identify sequence characteristics associated with inherently non-preferred acceptor substrates for OST, and show these have a high propensity for local secondary structure incompatible with the optimal conformation of a peptide bound to OST. Finally, we validate these mechanisms by examining the determinants of efficient glycosylation at a variably glycosylated Asn in a set of human Fabs. These mechanistic and functional insights show how local protein sequence controls glycosylation occupancy with immediate implications in secretory protein function and evolution, pathogen immunity and epistasis, and in engineering protein sequences for the desired degree of site-specific glycosylation.

biochemistry↗

bioRxiv2025

The unique molecular recognition features of Siglec-10: structural insights into sialoglycan and antibody interactions

Siglec-10 is a sialic acid-binding immunoglobulin-like lectin implicated in immune regulation, yet the molecular basis for ligand recognition and how this is functionally linked to immune modulation remains poorly defined. Herein, we present a multidisciplinary study encompassing structural, biochemical, and cellular approaches to elucidate Siglec-10-carbohydrate interactions and their functional consequences. The crystal structure of the extracellular domain of Siglec-10 in complex with 2-6 sialyllactose revealed the presence of two key arginine residues within the Siglec-10 binding site that interact with the carboxyl group of sialic acid, the canonical R119 and R127, suggesting potential dual contributions to ligand engagement. Saturation Transfer Difference (STD)-Nuclear Magnetic Resonance (NMR) confirmed that R119 is essential for sialoglycan binding in solution, whereas R127 appears dispensable for interactions with glycans under these conditions. In contrast, cell-based binding assays using primary human T cells and engineered monocytic lines demonstrated that both arginine residues (R119 and R127) are critical for cellular recognition, revealing a context-dependent interaction. By obtaining direct images at a molecular resolution of 6-7 nm, super-resolution microscopy further revealed glycan-independent dimerization of the Siglec-10 receptor on the surface of human monocytes. Ligand blockade mediated by anti-Siglec-10 mAb (clone S10A) restores CAR-T cell cytotoxicity in vitro, supporting its role as an immune checkpoint receptor. Finally, although CD24 was not identified as a Siglec-10 ligand on T cells, proximity labeling and mass spectrometry uncovered other sialylated glycoproteins that may mediate this interaction. Together, these results identify Siglec-10 as a modulatory receptor with structural and functional features distinct from other Siglec family members and highlight its potential for therapeutic targeting in cancer immunotherapy.

molecular biology↗

bioRxiv2025

Role of N-glycosylation as a determinant of ATG9A conformations and activity

In this study we investigate the effects of glycosylation at position N99 on the structural dynamics and lipid scrambling activity of ATG9A, a key autophagy protein, using microsecond all-atom molecular dynamics (MD) simulations. ATG9A is an integral membrane protein involved in autophagosome biogenesis, and glycosylation at N99 is known to play a critical, yet poorly understood role in its function. The MD simulations revealed that the hydrophilic central cavity of ATG9A supports lipid reorientation and partial transbilayer movements, consistent with its lipid scrambling activity observed experimentally. N-glycosylation at N99 was found to enhance cooperative interactions between protomers, facilitating lipid insertion and traversal within the central cavity. These findings align with the proposed mechanism of ATG9A role in lipid redistribution across the phagophore membrane during autophagy. However, mutagenesis experiments that abolish N-glycosylation in ATG9A (ATG9AN99A and ATG9AN99D mutants) did not show a significant change in autophagy flux, suggesting that further experimental approaches, such as lipid scramblase assays, are needed to pinpoint the function of glycosylation. In this study we also observed an asymmetric protomer conformations in ATG9A, contrasting with symmetric structures obtained from cryo-EM, suggesting that the structural heterogeneity of the protein could be further explored in cryo-EM datasets. Overall, the study highlights the importance of incorporating glycosylation in computational studies of membrane proteins and offers valuable insights into the molecular mechanisms of lipid transport in autophagy, with potential implications for other lipid scramblases and flippases.

biophysics↗

bioRxiv2024

The molecular basis of immunosuppression by soluble CD52 is defined by interactions of N-linked and O-linked glycans with HMGB1 Box B

AbstractHuman soluble CD52 is a short glycopeptide comprising 12 amino acids (GQNDTSQTSSPS) which functions as an immune regulator by sequestering the pro-inflammatory high mobility group box protein 1 (HMGB1) and supressing immune responses. Recombinant CD52 has been shown to act as a broad anti-inflammatory agent, dampening both adaptive and innate immune responses. This short glycopeptide is heavily glycosylated, with a complex sialylated N-linked glycan at N3 and reported O- linked glycosylation possible on several serine and threonine residues. Previously we demonstrated that specific glycosylation features of CD52 are essential for its immunosuppressive function, with terminal -2,3-linked sialic acids required for binding to the inhibitory SIGLEC-10 receptor leading to T-cell suppression. Using high resolution mass spectrometry, we have further characterised the N- and O-linked glycosylation of Expi293 recombinantly produced CD52 at a glycopeptide and released glycan level, accurately determining glycan heterogeneity of both N- and O-linked glycosylation, and localising the site of O-glycosylation to T8 with high confidence and direct spectral evidence. This detailed knowledge of CD52 glycosylation informed the construction of a model system, which we analysed by molecular dynamics simulations to understand the mechanism of recognition and define interactions between bioactive CD52, HMGB1 and the SIGLEC-10 receptor. Our results confirm the essential role of glycosylation, more specifically hyper-sialylation, in the function of CD52, and identify at the atomistic level specific interactions between CD52 glycans and the Box B domain of HMGB1 that determine recognition, and the stability of the CD52/HMGB1 complex. These insights will inform the development of synthetic CD52 as an immunotherapeutic agent.

molecular biology↗

bioRxiv2023

Restoring Protein Glycosylation with GlycoShape

During the past few years, we have been witnessing a revolution in structural biology. Leveraging on technological and computational advances, scientists can now resolve biomolecular structures at the atomistic level of detail by cryogenic electron microscopy (cryo-EM) and predict 3D structures from sequence alone by machine learning (ML). One technique often supports the other to provide the view of atoms in molecules required to capture the function of molecular machines. An example of the extraordinary impact of these advances on scientific discovery and on public health is given by how structural information supported the rapid development of COVID-19 vaccines based on the SARS-CoV-2 spike (S) glycoprotein. Yet, none of these new technologies can capture the details of the dense coat of glycans covering S, which is responsible for its natural, biologically active structure and function and ultimately for viral evasion. Indeed, glycosylation, the most abundant post-translational modification of proteins, is largely invisible through experimental structural biology and in turn it cannot be reproduced by ML, because of the lack of data to learn from. Molecular simulations through high-performance computing (HPC) can fill this crucial information gap, yet the computational resources, the users skills and the long timescales involved limit applications of molecular modelling to single study cases. To broaden access to structural information on glycans, here we introduce GlycoShape (https://glycoshape.org) an open access (OA) glycan structure database and toolbox designed to restore glycoproteins to their native functional form by supplementing the structural information available on proteins in public repositories, such as the RCSB PDB (www.rcsb.org) and AlphaFold Protein Structure Database (https://alphafold.ebi.ac.uk/), with the missing glycans derived from over 1 ms of cumulative sampling from molecular dynamics (MD) simulations. The GlycoShape Glycan Database (GDB) currently counts over 435 unique glycans principally covering the human glycome and with additional structures, fragments, and epitopes from other eukaryotic and prokaryotic organisms. The GDB feeds into Re-Glyco, a bespoke algorithm in GlycoShape designed to rapidly restore the natural glycosylation to protein 3D structures and to predict N-glycosylation occupancy, where unknown. Ultimately, integration of GlycoShape with other OA protein structure databases can provide a step-change in scientific discovery, from the structural and functional characterization of the active form of biomolecules, all the way down to pharmacological applications and drug discovery.

biophysics↗

bioRxiv2023

ASM Variants in the Spotlight: A Structure-Based Atlas for Unraveling Pathogenic Mechanisms in Lysosomal Acid Sphingomyelinase

Lysosomal acid sphingomyelinase (ASM), a critical enzyme in lipid metabolism encoded by the SMPD1 gene, plays a crucial role in sphingomyelin hydrolysis in lysosomes. ASM deficiency leads to acid sphingomyelinase deficiency, a rare genetic disorder with diverse clinical manifestations, and the protein can be found mutated in other diseases. We employed a structure-based framework to comprehensively understand the functional implications of ASM variants, integrating pathogenicity predictions with molecular insights derived from molecular dynamics simulations in a lysosomal membrane environment. Our analysis, encompassing over 400 variants, establishes a structural atlas of missense variants of lysosomal ASM, associating mechanistic indicators with pathogenic potential. Our study highlights variants that influence structural stability or exert local and long-range effects at functional sites. To validate our predictions, we compared them to available experimental data on residual catalytic activity in 135 ASM variants. Notably, our findings also suggest applications of the resulting data for identifying cases suited for enzyme replacement therapy. This comprehensive approach enhances the understanding of ASM variants and provides valuable insights for potential therapeutic interventions.

bioinformatics↗

bioRxiv2023

Predicting glycan structure from tandem mass spectrometry via deep learning

Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry data is a bottleneck in glycomics, preventing high-throughput endeavors and relegating glycomics to a few experts. Trained on a newly curated set of 300,000 annotated MS/MS spectra, we present CandyCrunch, a dilated residual neural network predicting glycan structure from raw LC-MS/MS data in seconds (Top1 Accuracy: 87.7%). We developed an open-access Python-based workflow of raw data conversion and prediction, followed by automated curation and fragment annotation, with predictions recapitulating and extending expert annotation. We demonstrate that this can be used for de novo annotation, diagnostic fragment identification, and high-throughput glycomics. For maximum impact, this entire pipeline is tightly interlaced with our glycowork platform and can be easily tested at https://colab.research.google.com/github/BojarLab/CandyCrunch/blob/main/CandyCru nch.ipynb. We envision CandyCrunch to democratize structural glycomics and the elucidation of biological roles of glycans.

bioinformatics↗

bioRxiv2023

Can ChatGPT pass Glycobiology?

The release of text-generating applications based on interactive Large Language Models (LLMs) in late 2022 triggered an unprecedented and ever-growing interest worldwide. The almost instantaneous success of LLMs stimulated lively discussions in public media and in academic fora alike on the value and potentials of such tools in all areas of knowledge and information acquisition and distribution, but also about the dangers posed by their uncontrolled and indiscriminate use. This conversation is now particularly active in the higher education sector, where LLMs are seen as a potential threat to academic integrity at all levels, from facilitating cheating by students in assignments, to plagiarising academic writing in the case of researchers and administrators. Within this framework, we were interested in testing the boundaries of the LLM ChatGPT (www.openai.com) in areas of our scientific interest and expertise, and in analysing the results from different perspectives, i.e. of a final year BSc student, of a research scientist, and of a lecturer in higher education. To this end, in this paper we present and discuss a systematic evaluation on how ChatGPT addresses progressively complex scientific writing tasks and exam-type questions in Carbohydrate Chemistry and Glycobiology. The results of this project allowed us to gain insight on, 1) the strengths and limitations of the ChatGPT model to provide relevant and (most importantly) correct scientific information, 2) the format(s) and complexity of the query required to obtain the desired output, and 3) strategies to integrate LLMs in teaching and learning.

scientific communication and education↗

bioRxiv2022

Natural variations within the glycan shield of SARS-CoV-2 impact viral spike dynamics

The emergence of SARS-CoV-2 variants alters the efficacy of existing immunity, whether arisen naturally or through vaccination. Understanding the structure of the viral spike assists in determining the impact of mutations on the antigenic surface. One class of mutation impacts glycosylation attachment sites, which have the capacity to influence the antigenic structure beyond the immediate site of attachment. Here, we compare the glycosylation of a recombinant viral spike mimetic of the P.1 (Gamma) strain, which exhibits two additional N-linked glycan sites compared to the equivalent mimetic of the Wuhan strain. We determine the site-specific glycosylation of these variants and investigate the impact of these glycans by molecular dynamics. The N188 site is shown to exhibit very limited glycan maturation, consistent with limited enzyme accessibility. Structural modeling and molecular dynamics reveal that N188 is located within a cavity by the receptor binding domain, which influences the dynamics of these attachment domains. These observations suggest a mechanism whereby mutations affecting viral glycosylation sites have a structural impact across the antigenic surface.

molecular biology↗

bioRxiv2021

Fine-tuning the Spike: Role of the nature and topology of the glycan shield structure and dynamics of SARS-CoV-2 S

The dense glycan shield is an essential feature of the SARS-CoV-2 spike (S) architecture, key to immune evasion and to the activation of the prefusion conformation. Recent studies indicate that the occupancy and structures of the SARS-CoV-2 S glycans depend not only on the nature of the host cell, but also on the structural stability of the trimer; a point that raises important questions about the relative competence of different glycoforms. Moreover, the functional role of the glycan shield in the SARS-CoV-2 pathogenesis suggests that the evolution of the sites of glycosylation is potentially intertwined with the evolution of the protein sequence to affect optimal activity. Our results from multi-microsecond molecular dynamics simulations indicate that the type of glycosylation at N234, N165 and N343 greatly affects the stability of the receptor binding domain (RBD) open conformation, and thus its exposure and accessibility. Furthermore, our results suggest that the loss of glycosylation at N370, a newly acquired modification in the SARS-CoV-2 S glycan shields topology, may have contributed to increase the SARS-CoV-2 infectivity as we find that N-glycosylation at N370 stabilizes the closed RBD conformation by binding a specific cleft on the RBD surface. We discuss how the absence of the N370 glycan in the SARS-CoV-2 S frees the RBD glycan binding cleft, which becomes available to bind cell-surface glycans, potentially increases host cell surface localization.

biophysics↗

bioRxiv2020

Citizen Scientists Create an Exascale Computer to Combat COVID-19

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression, and replication, which depend on the structure and dynamics of its constituent proteins. Many protein structures have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate an unprecedented 0.1 seconds of the viral proteome. Our simulations capture dramatic opening of the apo Spike complex, far beyond that seen experimentally, which explains and successfully predicts the existence of cryptic epitopes. Different Spike homologues modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also observe dramatic conformational changes across the proteome, which reveal over 50 cryptic pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas.

biophysics↗

bioRxiv2020

Shielding and Beyond: The Roles of Glycans in SARS-CoV-2 Spike Protein

The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 15,000,000 infections and 600,000 deaths worldwide to date. Antibody development efforts mainly revolve around the extensively glycosylated SARS-CoV-2 spike (S) protein, which mediates the host cell entry by binding to the angiotensin-converting enzyme 2 (ACE2). Similar to many other viruses, the SARS-CoV-2 spike utilizes a glycan shield to thwart the host immune response. Here, we built a full-length model of glycosylated SARS-CoV-2 S protein, both in the open and closed states, augmenting the available structural and biological data. Multiple microsecond-long, all-atom molecular dynamics simulations were used to provide an atomistic perspective on the roles of glycans, and the protein structure and dynamics. We reveal an essential structural role of N-glycans at sites N165 and N234 in modulating the conformational dynamics of the spikes receptor binding domain (RBD), which is responsible for ACE2 recognition. This finding is corroborated by biolayer interferometry experiments, which show that deletion of these glycans through N165A and N234A mutations significantly reduces binding to ACE2 as a result of the RBD conformational shift towards the "down" state. Additionally, end-to-end accessibility analyses outline a complete overview of the vulnerabilities of the glycan shield of SARS-CoV-2 S protein, which may be exploited by therapeutic efforts targeting this molecular machine. Overall, this work presents hitherto unseen functional and structural insights into the SARS-CoV-2 S protein and its glycan coat, providing a strategy to control the conformational plasticity of the RBD that could be harnessed for vaccine development.

biophysics↗

bioRxiv2020

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

N-glycosylation is one of the most abundant and diverse post-translational modifications of proteins, implicated in protein folding and structural stability, and mediating interactions with receptors and with the environment. All N-glycans share a common core from which linear or branched arms stem from, with functionalization specific to different species and to the cells health and disease state. This diversity generates a rich collection of structures, all diversely able to trigger molecular cascades and to activate pathways, which also include adverse immunogenic responses. These events are inherently linked to the N-glycans 3D architecture and dynamics, which remain for the large part unresolved and undetected because of their intrinsic structural disorder. In this work we use molecular dynamics (MD) simulations to provide insight into N-glycans 3D structure by analysing the effects of a set of very specific modifications found in plants and invertebrate N-glycans, which are immunogenic in humans. We also compare these structural motifs and combine them with mammalian N-glycans motifs to devise strategies for the control of the N-glycan 3D structure through sequence. Our results suggest that the N-glycans architecture can be described in terms of the local spatial environment of groups of monosaccharides. We define these "glycoblocks" as self-contained 3D units, uniquely identified by the nature of the residues they comprise, their linkages and structural/dynamic features. This alternative description of glycans 3D architecture can potentially lead to an easier prediction of sequence-to-structure relationships in complex carbohydrates, with important implications in glycoengineering design.

biophysics↗

bioRxiv2019

An atomistic perspective on ADCC quenching by core-fucosylation of IgG1 Fc N-glycans from enhanced sampling molecular dynamics

The immunoglobulin type G (IgG) Fc N-glycans are known to modulate the interaction with membrane-bound Fc {gamma} receptors (Fc{gamma}Rs), fine-tuning the antibodys effector function in a sequence-dependent manner. Particularly interesting in this respect are the roles of galactosylation, which levels are linked to autoimmune conditions and aging, of core fucosylation, which is known to reduce significantly the antibody-dependent cellular cytotoxicity (ADCC), and of sialylation, which also reduces ADCC but only in the context of core-fucosylation. In this work we provide an atomistic level perspective through enhanced sampling computer simulations, based on replica exchange molecular dynamics (REMD), to understand the molecular determinants linking the Fc N-glycans sequence to the observed IgG1 function. Our results indicate that the two symmetrically opposed N-glycans interact extensively through their core trimannose residues. At room temperature the terminal galactose on the (1-6) arm is restrained to the protein through a network of interactions that keep the arm outstretched, meanwhile the (1-3) arm extends towards the solvent where a terminal sialic acid remains fully accessible. We also find that the presence of core fucose interferes with the extended sialylated (1-3) arm, altering its conformational propensity and as a consequence of steric hindrance, significantly enhancing the Fc dynamics. Furthermore, structural analysis shows that the core fucose position within the Fc core obstructs the access of N162 glycosylated Fc{gamma}Rs very much like a \"door-stop\", potentially decreasing the IgG/Fc{gamma}R binding free energy. All of these factors could represent important clues to understand at the molecular level the dramatic reduction of ADCC as a result of core fucosylation and provide an atomistic level-of-detail framework for the design of high potency IgG1 Fc N-glycoforms.

biophysics↗

bioRxiv2018

Sequence-to-structure dependence of isolated IgG Fc complex biantennary N-glycans: A molecular dynamics study

Fc glycosylation of human immunoglobulins G (IgGs) is essential for their structural integrity and activity. Interestingly, the specific nature of the Fc glycoforms is known to modulate the IgG effector function. Indeed, while core-fucosylation of IgG Fc-glycans greatly affects the antibody-dependent cell-mediated cytotoxicity (ADCC) function, with obvious repercussions in the design of therapeutic antibodies, sialylation can reverse the antibody inflammatory response, and galactosylation levels have been linked to aging, to the onset of inflammation, and to the predisposition to rheumatoid arthritis. Within the framework of a structure-to-function relationship, we have studied the role of the N-glycan sequence on its intrinsic conformational propensity. Here we report the results of a systematic study, based on extensive molecular dynamics (MD) simulations in excess of 62 {micro}s of cumulative simulation time, on the effect of sequence on the structure and dynamics of increasingly larger, complex biantennary N-glycoforms, i.e. from chitobiose to the larger N-glycan species commonly found in the Fc region of human IgGs. Our results show that while core fucosylation and sialylation do not affect the intrinsic dynamics of the isolated (unbound) N-glycans, galactosylation of the (1-6) arm shifts dramatically its conformational equilibrium from an outstretched to a folded conformation. These findings are in agreement with and can help rationalize recent experimental evidence showing a differential recognition of positional isomers in glycan array data and also the preference of sialyltransferase for the more reachable, outstretched (1-3) arm in both isolated and Fc-bound N-glycans.

biophysics↗