GlAIcomics: a deep neural network classifier for spectroscopy-augmented mass spectrometric glycans data.

Carbohydrate sequencing is a formidable task identified as a strategic goal in modern biochemistry. It relies on identifying a large number of isomers and their connectivity with high accuracy. Recently, gas phase vibrational laser spectroscopy combined with mass spectrometry tools have been proposed as a very promising sequencing approach. However, its use as a generic analytical tool relies on the development of recognition techniques that can analyse complex vibrational fingerprints for a large number of monomers. In this study, we used a Bayesian deep neural network model to automatically identify and classify vibrational fingerprints of several monosaccharides. We report high performances of the obtained trained algorithm (GlAIcomics), that can be used to discriminate contamination and identify a molecule with a high degree of confidence. It opens the possibility to use artificial intelligence in combination with spectroscopy-augmented mass spectrometry for carbohydrates sequencing and glycomics applications.

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 not only on the value and potentials of such tools in all areas of knowledge and information acquisition and distribution but also on 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 plagiarizing academic writing in the case of researchers and administrators. Within this framework, we are interested in testing the boundaries of the LLM ChatGPT (www.openai.com) in areas of our scientific interest and expertise and in analyzing 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: (i) the strengths and limitations of the ChatGPT model to provide relevant and (most importantly) correct scientific information, (ii) the format(s) and complexity of the query required to obtain the desired output, and (iii) strategies to integrate LLMs in teaching and learning.

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.

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 site-specific glycosylation of recombinant viral spike mimetics of B.1.351 (Beta), P.1 (Gamma), B.1.617.2 (Delta), B.1.1.529 (Omicron). The P.1 strain exhibits two additional N-linked glycan sites compared to the other variants analyzed and we investigate the impact of these glycans by molecular dynamics. The acquired 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 protein surface.

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.

Principles of SARS-CoV-2 glycosylation.

The structure and post-translational processing of the SARS-CoV-2 spike glycoprotein (S) is intimately associated with the function of the virus and of sterilising vaccines. The surface of the S protein is extensively modified by glycans, and their biosynthesis is driven by both the wider cellular context, and importantly, the underlining protein structure and local glycan density. Comparison of virally derived S protein with both recombinantly derived and adenovirally induced proteins, reveal hotspots of protein-directed glycosylation that drive conserved glycosylation motifs. Molecular dynamics simulations revealed that, while the S surface is extensively shielded by N-glycans, it presents regions vulnerable to neutralising antibodies. Furthermore, glycans have been shown to influence the accessibility of the receptor binding domain and the binding to the cellular receptor. The emerging picture is one of unifying, principles of S protein glycosylation and an intimate role of glycosylation in immunogen structure and efficacy.

Fine-tuning the spike: role of the nature and topology of the glycan shield in the structure and dynamics of the 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 shield's 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, and potentially increases host cell surface localization.

SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome.

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression and replication that 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 0.1 seconds of the viral proteome. Our adaptive sampling simulations predict dramatic opening of the apo spike complex, far beyond that seen experimentally, explaining and predicting the existence of 'cryptic' epitopes. Different spike variants modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also discover 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.

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)]-Manß(1-4)-GlcNAcß(1-4)-GlcNAcß1-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.

Beyond Shielding: The Roles of Glycans in the 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 28,000,000 infections and 900,000 deaths worldwide to date. Antibody development efforts mainly revolve around the extensively glycosylated SARS-CoV-2 spike (S) protein, which mediates host cell entry by binding to the angiotensin-converting enzyme 2 (ACE2). Similar to many other viral fusion proteins, the SARS-CoV-2 spike utilizes a glycan shield to thwart the host immune response. Here, we built a full-length model of the 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 on 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 spike's 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 toward the "down" state. Additionally, end-to-end accessibility analyses outline a complete overview of the vulnerabilities of the glycan shield of the SARS-CoV-2 S protein, which may be exploited in the 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.

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

The 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-glycan 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.

SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome.

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.

Beyond Shielding: 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 spike's 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.

An atomistic perspective on antibody-dependent cellular cytotoxicity 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 γ receptors (FcγRs), fine-tuning the antibody's 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 antibody-dependent cellular cytotoxicity (ADCC) but only in the context of core-fucosylation. In this article, 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 α (1-6) arm is restrained to the protein through a network of interactions that keep the arm outstretched; meanwhile, the α (1-3) arm extends toward the solvent where a terminal sialic acid remains fully accessible. We also find that the presence of core fucose interferes with the extended sialylated α (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 FcγRs very much like a "door-stop," potentially decreasing the IgG/FcγR binding free energy. These results provide an atomistic level-of-detail framework for the design of high potency IgG1 Fc N-glycoforms.

Binding Free Energies of Conformationally Disordered Peptides Through Extensive Sampling and End-Point Methods.

The ability to obtain binding free energies from molecular simulation techniques provides a valuable support to the interpretation and design of experiments. Among all methods available, the most widely used equilibrium free energy methods range from highly accurate and computationally expensive perturbation theory-based methods, such as free energy perturbation (FEP), or thermodynamic integration (TI), through end-point methods, such as molecular mechanics with generalized Born and surface area solvation (MM/GBSA) or MM/PBSA, when the Poisson-Boltzmann method is used instead of GB, and linear interaction energy (LIE) methods, to scoring functions, which are relatively simple empirical functions widely used as part of molecular docking protocols. Because the use of FEP and TI approaches is restricted to cases where the perturbation leading from an initial to final state is negligible or minimal, their application to cases where large conformational changes are involved between bound and unbound states is rather complex, if not prohibitive in terms of convergence. Here we describe a protocol that involves the use of extensive conformational sampling through molecular dynamics (MD) in combination with end-point methods (MM/GB(PB)SA) with an additional quasi-harmonic entropy component, for the calculation of the relative binding free energies of highly flexible, or intrinsically disordered, peptides to a structured receptor.

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 and inflammatory properties. Indeed, while core-fucosylation of IgG Fc-glycans greatly affects the antibody-dependent cell-mediated cytotoxicity 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 simulations in excess of 62 µs of cumulative simulation time, on the effect of sequence on the structure and dynamics of increasingly larger, complex biantennary N-glycoforms isolated from the protein, 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 unlinked N-glycans, galactosylation of the α(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 accessible, outstretched α(1-3) arm in both isolated, and Fc-bound N-glycans.

Aminoquinoline Fluorescent Labels Obstruct Efficient Removal of N-Glycan Core α(1-6) Fucose by Bovine Kidney α-l-Fucosidase (BKF).

Here we report evidence that new aminoquinoline N-glycan fluorescent labels interfere with the release of core α(1-6) fucose from N-glycans by bovine kidney α-l-fucosidase (BKF). BKF is a commonly employed exoglycosidase for core α(1-6) fucose determination. Molecular simulations of the bound and unbound Fuc-α(1-6)-GlcNAc, where GlcNAc is situated at the reducing end for all N-glycans, suggest that the reduced BKF activity may be due to a nonoptimal fit of the highest populated conformers in the BKF active binding site at room temperature. Population analysis and free energy estimates suggest that an enhanced flexibility of the labeled sugar, which facilitates recognition and binding, can be achievable with extended reaction conditions. We provide these experimental conditions using a sequential exoglycosidase digestion array using high concentrations of BKF.

Role of the XPA protein in the NER pathway: A perspective on the function of structural disorder in macromolecular assembly.

Lack of structure is often an essential functional feature of protein domains. The coordination of macromolecular assemblies in DNA repair pathways is yet another task disordered protein regions are highly implicated in. Here I review the available experimental and computational data and within this context discuss the functional role of structure and disorder in one of the essential scaffolding proteins in the nucleotide excision repair (NER) pathway, namely Xeroderma pigmentosum complementation group A (XPA). From the analysis of the current knowledge, in addition to protein-protein docking and secondary structure prediction results presented for the first time herein, a mechanistic framework emerges, where XPA builds the NER pre-incision complex in a modular fashion, as "beads on a string", where the protein-protein interaction "beads", or modules, are interconnected by disordered link regions. This architecture is ideal to avoid the expected steric hindrance constraints of the DNA expanded bubble. Finally, the role of the XPA structural disorder in binding affinity modulation and in the sequential binding of NER core factors in the pre-incision complex is also discussed.

A chromatin-independent role of Polycomb-like 1 to stabilize p53 and promote cellular quiescence.

Polycomb-like proteins 1-3 (PCL1-3) are substoichiometric components of the Polycomb-repressive complex 2 (PRC2) that are essential for association of the complex with chromatin. However, it remains unclear why three proteins with such apparent functional redundancy exist in mammals. Here we characterize their divergent roles in both positively and negatively regulating cellular proliferation. We show that while PCL2 and PCL3 are E2F-regulated genes expressed in proliferating cells, PCL1 is a p53 target gene predominantly expressed in quiescent cells. Ectopic expression of any PCL protein recruits PRC2 to repress the INK4A gene; however, only PCL2 and PCL3 confer an INK4A-dependent proliferative advantage. Remarkably, PCL1 has evolved a PRC2- and chromatin-independent function to negatively regulate proliferation. We show that PCL1 binds to and stabilizes p53 to induce cellular quiescence. Moreover, depletion of PCL1 phenocopies the defects in maintaining cellular quiescence associated with p53 loss. This newly evolved function is achieved by the binding of the PCL1 N-terminal PHD domain to the C-terminal domain of p53 through two unique serine residues, which were acquired during recent vertebrate evolution. This study illustrates the functional bifurcation of PCL proteins, which act in both a chromatin-dependent and a chromatin-independent manner to regulate the INK4A and p53 pathways.