GLYCAM06: a generalizable biomolecular force field. Carbohydrates

Targeting host O-linked glycan biosynthesis affects Ebola virus replication efficiency and reveals differential GalNAc-T acceptor site preferences on the Ebola virus glycoprotein

Ebola virus glycoprotein (EBOV GP) is one of the most heavily O-glycosylated viral glycoproteins, yet we still lack a fundamental understanding of the structure of its large O-glycosylated mucin-like domain and to what degree the host O-glycosylation capacity influences EBOV replication. Using tandem mass spectrometry, we identified 47 O-glycosites on EBOV GP and found similar glycosylation signatures on virus-like particle- and cell lysate-derived GP. Furthermore, we performed quantitative differential O-glycoproteomics on proteins produced in wild-type HEK293 cells and cell lines ablated for the three key initiators of O-linked glycosylation, GalNAc-T1, -T2, and -T3. The data show that 12 out of the 47 O-glycosylated sites were regulated, predominantly by GalNAc-T1. Using the glycoengineered cell lines for authentic EBOV propagation, we demonstrate the importance of O-linked glycan initiation and elongation for the production of viral particles and the titers of progeny virus. The mapped O-glycan positions and structures allowed to generate molecular dynamics simulations probing the largely unknown spatial arrangements of the mucin-like domain. The data highlight targeting GALNT1 or C1GALT1C1 as a possible way to modulate O-glycan density on EBOV GP for novel vaccine designs and tailored intervention approaches.IMPORTANCEEbola virus glycoprotein acquires its extensive glycan shield in the host cell, where it is decorated with N-linked glycans and mucin-type O-linked glycans. The latter is initiated by a family of polypeptide GalNAc-transferases that have different preferences for optimal peptide substrates resulting in a spectrum of both very selective and redundant substrates for each isoform. In this work, we map the exact locations of O-glycans on Ebola virus glycoprotein and identify subsets of sites preferentially initiated by one of the three key isoforms of GalNAc-Ts, demonstrating that each enzyme contributes to the glycan shield integrity. We further show that altering host O-glycosylation capacity has detrimental effects on Ebola virus replication, with both isoform-specific initiation and elongation playing a role. The combined structural and functional data highlight glycoengineered cell lines as useful tools for investigating molecular mechanisms imposed by specific glycans and for steering the immune responses in future vaccine designs.

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

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

Amorphous solid dispersion of a binary formulation with felodipine and HPMC for 3D printed floating tablets

This study focuses on the combination of three-dimensional printing (3DP) and amorphous solid dispersion (ASD) technologies for the manufacturing of gastroretentive floating tablets. Employing hot melt extrusion (HME) and fused deposition modeling (FDM), the study investigates the development of drug-loaded filaments and 3D printed (3DP) tablets containing felodipine as model drug and hydroxypropyl methylcellulose (HPMC) as the polymeric carrier. Prior to fabrication, solubility parameter estimation and molecular dynamics simulations were applied to predict drug-polymer interactions, which are crucial for ASD formation. Physical bulk and surface characterization complemented the quality control of both drug-loaded filaments and 3DP tablets. The analysis confirmed a successful amorphous dispersion of felodipine within the polymeric matrix. Furthermore, the low infill percentage and enclosed design of the 3DP tablet allowed for obtaining low-density systems. This structure resulted in buoyancy during the entire drug release process until a complete dissolution of the 3DP tablets (more than 8 h) was attained. The particular design made it possible for a single polymer to achieve a zero-order controlled release of the drug, which is considered the ideal kinetics for a gastroretentive system. Accordingly, this study can be seen as an advancement in ASD formulation for 3DP technology within pharmaceutics.

The Legionella collagen-like protein employs a distinct binding mechanism for the recognition of host glycosaminoglycans

Bacterial adhesion is a fundamental process which enables colonisation of niche environments and is key for infection. However, in Legionella pneumophila, the causative agent of Legionnaires' disease, these processes are not well understood. The Legionella collagen-like protein (Lcl) is an extracellular peripheral membrane protein that recognises sulphated glycosaminoglycans on the surface of eukaryotic cells, but also stimulates bacterial aggregation in response to divalent cations. Here we report the crystal structure of the Lcl C-terminal domain (Lcl-CTD) and present a model for intact Lcl. Our data reveal that Lcl-CTD forms an unusual trimer arrangement with a positively charged external surface and negatively charged solvent exposed internal cavity. Through molecular dynamics simulations, we show how the glycosaminoglycan chondroitin-4-sulphate associates with the Lcl-CTD surface via distinct binding modes. Our findings show that Lcl homologs are present across both the Pseudomonadota and Fibrobacterota-Chlorobiota-Bacteroidota phyla and suggest that Lcl may represent a versatile carbohydrate-binding mechanism.

Structural and genetic basis for the binding of a mouse monoclonal antibody to Flavobacterium psychrophilum lipopolysaccharide

A mouse monoclonal antibody (mAb FL100A) previously prepared against Flavobacterium psychrophilum (Fp) CSF259-93 has now been examined for binding to lipopolysaccharides (LPS) of this strain and Fp 950106-1/1. The corresponding O-polysaccharides (O-PS) of these strains are formed by identical trisaccharide repeats composed of l-Rhamnose (l-Rha), 2-acetamido-2-deoxy-l-fucose (l-FucNAc) and 2-acetamido-4-R1-2,4-dideoxy-d-quinovose (d-Qui2NAc4NR1) where R1 represents a dihydroxyhexanamido moiety. The O-PS loci of these strains are also identical except for the gene (wzy1 or wzy2) that encodes the polysaccharide polymerase. Accordingly, adjacent O-PS repeats are joined through d-Qui2NAc4NR1 and l-Rha by wzy2-dependent α(1-2) linkages in Fp CSF259-93 versus wzy1-dependent β(1-3) linkages in Fp 950106-1/1. mAb FL100A reacted strongly with Fp CSF259-93 O-PS and LPS but weakly or not at all with Fp 950106-1/1 LPS and O-PS. Importantly, it also labelled cell surface blebs on the former but not the latter strain. Additionally, mAb binding was approximately 5-times stronger to homologous Fp CSF259-93 LPS than to LPS from a strain with a different R-group gene. A conformational epitope for mAb FL100A binding was suggested from molecular dynamic simulations of each O-PS. Thus, Fp CSF259-93 O-PS formed a stable well-defined compact helix in which the R1 groups were displayed in a regular pattern on the helix exterior while unreactive Fp 950106-1/1 O-PS adopted a flexible extended linear conformation. Taken together, the findings establish the specificity of mAb FL100A for Wzy2-linked F. psychrophilum O-PS and LPS.

Preparation and characterization of cellulose fluorescent material: Experiment and simulation

The extensive use of fossil based materials has caused serious pollution problems, the full utilization of biomass resources to prepare high value-added new materials is of great significance for the environmental protection and sustainable social development. For this purpose, this study explored the preparation process and molecular dynamics simulation of cellulose fluorescent materials. Firstly, bacterial cellulose was dissolved in a solution of NaOH and urea at low temperature, followed by a solution blending and hot pressing with hyperbranched polyamide. It was found that the addition of hyperbranched polyamide could effectively filled in the internal pores of cellulose hydrogel, thereby enhancing the fluorescence effects and tensile properties, especially the elongation at break of cellulose materials. The optimal amount of hyperbranched polyamide added was 5 wt%. Molecular dynamics simulation showed that the hydrogen bonds and interaction with cellulose increased as the concentration of hyperbranched polyamide increased.

Growing Glycans in Rosetta: Accurate de novo glycan modeling, density fitting, and rational sequon design

Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.

Rotational Dynamics of Water near Osmolytes by Molecular Dynamics Simulations

The behavior of water molecules around organic molecules has attracted considerable attention as a crucial factor influencing the properties and functions of soft matter and biomolecules. Recently, it has been suggested that the change in protein stability upon the addition of small organic molecules (osmolytes) is dominated by the change in the water dynamics caused by the osmolyte, where the dynamics of not only the directly interacting water molecules but also the long-range hydration layer affect the protein stability. However, the relation between the long-range structure of hydration water in various solutions and the water dynamics remains unclear at the molecular level. We performed density-functional tight-binding molecular dynamics simulations to elucidate the varying rotational dynamics of water molecules in 15 osmolyte solutions. A positive correlation was observed between the rotational relaxation time and our proposed normalized parameter obtained by dividing the number of hydrogen bonds between water molecules by the number of nearest-neighbor water molecules. For the 15 osmolyte solutions, an increase or a decrease in the value of the normalized parameter for the second hydration shell tended to result in water molecules with slow and fast rotational dynamics, respectively, thus illustrating the importance of the second hydration shell for the rotational dynamics of water molecules. Our simulation results are anticipated to advance the current understanding of water dynamics around organic molecules and the long-range structure of water molecules.

Enhancing Protein Solubility via Glycosylation: From Chemical Synthesis to Machine Learning Predictions

Glycosylation is a valuable tool for modulating protein solubility; however, the lack of reliable research strategies has impeded efficient progress in understanding and applying this modification. This study aimed to bridge this gap by investigating the solubility of a model glycoprotein molecule, the carbohydrate-binding module (CBM), through a two-stage process. In the first stage, an approach involving chemical synthesis, comparative analysis, and molecular dynamics simulations of a library of glycoforms was employed to elucidate the effect of different glycosylation patterns on solubility and the key factors responsible for the effect. In the second stage, a predictive mathematical formula, innovatively harnessing machine learning algorithms, was derived to relate solubility to the identified key factors and accurately predict the solubility of the newly designed glycoforms. Demonstrating feasibility and effectiveness, this two-stage approach offers a valuable strategy for advancing glycosylation research, especially for the discovery of glycoforms with increased solubility.

Interfacial Glucose to Regulate Hydrated Lipid Bilayer Properties: Influence of Concentrations

A series of atomistic molecular dynamics (MD) simulations were carried out with a hydrated 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) bilayer with the variation of glucose concentrations from 0 to 30 wt % in the presence of 0.3 M NaCl. The study suggested that although the thickness of the lipid bilayer dropped significantly with the increase in glucose concentration, it expanded laterally at high glucose levels due to the intercalation of glucose between the headgroups of adjacent lipids. We adopted the surface assessment via the grid evaluation method to compute the deviation of the bilayer's key structural features for the different amounts of glucose present. This suggested that the accumulation of glucose molecules near the headgroups influences the local lipid bilayer undulation and crimping of the lipid tails. We find that the area compressibility modulus increases with the glucose level, causing enhanced bilayer rigidity arising from the slow lateral diffusion of lipids. The restricted lipid motion at high glucose concentrations controls the sustainability of the curved bilayer surface. Calculations revealed that certain orientations of CO → of interfacial glucose with the PN → of lipid headgroups are preferred, which helps the glucose to form direct hydrogen bonds (HBs) with the lipid headgroups. Such lipid-glucose (LG) HBs relax slowly at low glucose concentrations and exhibit a higher lifetime, whereas fast structural relaxation of LG HBs with a shorter lifetime was noticed at a higher glucose level. In contrast, lipid-water (LW) HBs exhibited a higher lifetime at a higher glucose level, which gradually decreased with the glucose level lowering. The study interprets that the glucose concentration-driven LW and LG interactions are mutually inclusive. Our detailed analysis will exemplify small saccharide concentration-driven membrane stabilizing efficiency, which is, in general, helpful for drug delivery study.

The rotamer of the second-sphere histidine in AA9 lytic polysaccharide monooxygenase is pH dependent

Lytic polysaccharide monooxygenases (LPMOs) catalyze a reaction that is crucial for the biological decomposition of various biopolymers and for the industrial conversion of plant biomass. Despite the importance of LPMOs, the exact molecular-level nature of the reaction mechanism is still debated today. Here, we investigated the pH-dependent conformation of a second-sphere histidine (His) that we call the stacking histidine, which is conserved in fungal AA9 LPMOs and is speculated to assist catalysis in several of the LPMO reaction pathways. Using constant-pH and accelerated molecular dynamics simulations, we monitored the dynamics of the stacking His in different protonation states for both the resting Cu(II) and active Cu(I) forms of two fungal LPMOs. Consistent with experimental crystallographic and neutron diffraction data, our calculations suggest that the side chain of the protonated and positively charged form is rotated out of the active site toward the solvent. Importantly, only one of the possible neutral states of histidine (HIE state) is observed in the stacking orientation at neutral pH or when bound to cellulose. Our data predict that, in solution, the stacking His may act as a stabilizer (via hydrogen bonding) of the Cu(II)-superoxo complex after the LPMO-Cu(I) has reacted with O2 in solution, which, in fine, leads to H2O2 formation. Also, our data indicate that the HIE-stacking His is a poor acid/base catalyst when bound to the substrate and, in agreement with the literature, may play an important stabilizing role (via hydrogen bonding) during the peroxygenase catalysis. Our study reveals the pH titration midpoint values of the pH-dependent orientation of the stacking His should be considered when modeling and interpreting LPMO reactions, whether it be for classical LPMO kinetics or in industry-oriented enzymatic cocktails, and for understanding LPMO behavior in slightly acidic natural processes such as fungal wood decay.

Outstanding Properties of the Hydration Shell around β-d-Glucose: A Computational Study

Ab initio molecular dynamics (AIMD) simulations have been performed on aqueous solutions of four simple sugars, α-d-glucose, β-d-glucose, α-d-mannose, and α-d-galactose. Hydrogen-bonding (HB) properties, such as the number of donor- and acceptor-type HB-s, and the lengths and strengths of hydrogen bonds between sugar and water molecules, have been determined. Related electronic properties, such as the dipole moments of water molecules and partial charges of the sugar O atoms, have also been calculated. The hydrophilic and hydrophobic shells were characterized by means of spatial distribution functions. β-d-Glucose was found to form the highest number of hydrophilic and the smallest number of hydrophobic connections to neighboring water molecules. The average sugar-water H-bond length was the shortest for β-d-glucose, which suggests that these are the strongest such H-bonds. Furthermore, β-d-glucose appears to stand out in terms of the symmetry properties of both its hydrophilic and hydrophobic hydration shells. In summary, in all aspects considered here, there seems to be a correlation between the distinct characteristics of β-d-glucose reported here and its outstanding solubility in water. Admittedly, our findings represent only some of the important factors that influence the solubility.

MDverse: Shedding Light on the Dark Matter of Molecular Dynamics Simulations

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2,000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation such as temperature and simulation length, and could identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore the MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and to report and standardize metadata to reuse this valuable matter.

Identification of structural origins of complex charge heterogeneity in therapeutic ACE2Fc fusion protein facilitated by free-flow isoelectric focusing

Fc Fusion protein represents a versatile molecular platform with considerable potential as protein therapeutics of which the charge heterogeneity should be well characterized according to regulatory guidelines. Angiotensin-converting enzyme 2 Fc fusion protein (ACE2Fc) has been investigated as a potential neutralizing agent to various coronaviruses, including the lingering SARS-CoV-2, as this coronavirus must bind to ACE2 to allow for its entry into host cells. ACE2Fc, an investigational new drug developed by Henlius (Shanghai China), has passed the Phase I clinical trial, but its huge amount of charge isoforms and complicated charge heterogeneity posed a challenge to charge variant investigation in pharmaceutical development. We employed offline free-flow isoelectric focusing (FF-IEF) fractionation, followed by detailed characterization of enriched ACE2Fc fractions, to unveil the structural origins of charge heterogeneity in ACE2Fc expressed by recombinant CHO cells. We adopted a well-tuned 3-component separation medium for ACE2Fc fractionation, the highest allowable voltage to maximize the FF-IEF separation window and a mild Protein A elution method for preservation of protein structural integrity. Through peptide mapping and other characterizations, we revealed that the intricate profiles of ACE2Fc charge heterogeneity are mainly caused by highly sialylated multi-antenna N-glycosylation. In addition, based on fraction characterization and in silico glycoprotein model analysis, we discovered that the large acidic glycans at N36, N73, and N305 of ACE2Fc were able to decrease the binding activity towards Spike (S) protein of SARS-CoV-2. Our study exemplifies the value of FF-IEF in highly complex fusion protein characterization and revealed a quantitative sialylation-activity relationship in ACE2Fc.

Application of Recurrence Plot Analysis to Examine Dynamics of Biological Molecules on the Example of Aggregation of Seed Mucilage Components

The goal of the research is to describe the aggregation process inside the mucilage produced by plant seeds using molecular dynamics (MD) combined with time series algorithmic analysis based on the recurrence plots. The studied biological molecules model is seed mucilage composed of three main polysaccharides, i.e. pectins, hemicellulose, and cellulose. The modeling of biological molecules is based on the assumption that a classical-quantum passage underlies the aggregation process in the mucilage, resulting from non-covalent interactions, as they affect the macroscopic properties of the system. The applied recurrence plot approach is an important tool for time series analysis and data mining dedicated to analyzing time series data originating from complex, chaotic systems. In the current research, we demonstrated that advanced algorithmic analysis of seed mucilage data can reveal some features of the dynamics of the system, namely temperature-dependent regions with different dynamics of increments of a number of hydrogen bonds and regions of stable oscillation of increments of a number of hydrophobic-polar interactions. Henceforth, we pave the path for automatic data-mining methods for the analysis of biological molecules with the intermediate step of the application of recurrence plot analysis, as the generalization of recurrence plot applications to other (biological molecules) datasets is straightforward.

Differential Solvent DEEP-STD NMR and MD Simulations Enable the Determinants of the Molecular Recognition of Heparin Oligosaccharides by Antithrombin to Be Disentangled

The interaction of heparin with antithrombin (AT) involves a specific sequence corresponding to the pentasaccharide GlcNAc/NS6S-GlcA-GlcNS3S6S-IdoA2S-GlcNS6S (AGA*IA). Recent studies have revealed that two AGA*IA-containing hexasaccharides, which differ in the sulfation degree of the iduronic acid unit, exhibit similar binding to AT, albeit with different affinities. However, the lack of experimental data concerning the molecular contacts between these ligands and the amino acids within the protein-binding site prevents a detailed description of the complexes. Differential epitope mapping (DEEP)-STD NMR, in combination with MD simulations, enables the experimental observation and comparison of two heparin pentasaccharides interacting with AT, revealing slightly different bound orientations and distinct affinities of both glycans for AT. We demonstrate the effectiveness of the differential solvent DEEP-STD NMR approach in determining the presence of polar residues in the recognition sites of glycosaminoglycan-binding proteins.

Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations

Proteoglycans contain glycosaminoglycans (GAGs) which are negatively charged linear polymers made of repeating disaccharide units of uronic acid and hexosamine units. They play vital roles in numerous physiological and pathological processes, particularly in governing cellular communication and attachment. Depending on their sulfonation state, acetylation, and glycosidic linkages, GAGs belong to different families. The high molecular weight, heterogeneity, and flexibility of GAGs hamper their characterization at atomic resolution, but this may be circumvented via coarse-grained (CG) approaches. In this work, we report a CG model for a library of common GAG types in their isolated or proteoglycan-linked states compatible with version 2.2 (v2.2) of the widely popular CG Martini force field. The model reproduces conformational and thermodynamic properties for a wide variety of GAGs, as well as matching structural and binding data for selected proteoglycan test systems. The parameters developed here may thus be employed to study a range of GAG-containing biomolecular systems, thereby benefiting from the efficiency and broad applicability of the Martini framework.

Deciphering the Chemical Language of the Immunomodulatory Properties of Veillonella parvula Lipopolysaccharide

Veillonella parvula, prototypical member of the oral and gut microbiota, is at times commensal yet also potentially pathogenic. The definition of the molecular basis tailoring this contrasting behavior is key for broadening our understanding of the microbiota-driven pathogenic and/or tolerogenic mechanisms that take place within our body. In this study, we focused on the chemistry of the main constituent of the outer membrane of V. parvula, the lipopolysaccharide (LPS). LPS molecules indeed elicit pro-inflammatory and immunomodulatory responses depending on their chemical structures. Herein we report the structural elucidation of the LPS from two strains of V. parvula and show important and unprecedented differences in both the lipid and carbohydrate moieties, including the identification of a novel galactofuranose and mannitol-containing O-antigen repeating unit for one of the two strains. Furthermore, by harnessing computational studies, in vitro human cell models, as well as lectin binding solid-phase assays, we discovered that the two chemically diverse LPS immunologically behave differently and have attempted to identify the molecular determinant(s) governing this phenomenon. Whereas pro-inflammatory potential has been evidenced for the lipid A moiety, by contrast a plausible "immune modulating" action has been proposed for the peculiar O-antigen portion.

Molecular Insights into the Variability in Infection and Immune Evasion Capabilities of SARS-CoV-2 Variants: A Sequence and Structural Investigation of the RBD Domain

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continuously emerge, an increasing number of mutations are accumulating in the Spike protein receptor-binding domain (RBD) region. Through sequence analysis of various Variants of Concern (VOC), we identified that they predominantly fall within the ο lineage although recent variants introduce any novel mutations in the RBD. Molecular dynamics simulations were employed to compute the binding free energy of these variants with human Angiotensin-converting enzyme 2 (ACE2). Structurally, the binding interface of the ο RBD displays a strong positive charge, complementing the negatively charged binding interface of ACE2, resulting in a significant enhancement in the electrostatic potential energy for the ο variants. Although the increased potential energy is partially offset by the rise in polar solvation free energy, enhanced electrostatic potential contributes to the long-range recognition between the ο variant's RBD and ACE2. We also conducted simulations of glycosylated ACE2-RBD proteins. The newly emerged ο (JN.1) variant has added a glycosylation site at N-354@RBD, which significantly weakened its binding affinity with ACE2. Further, our interaction studies with three monoclonal antibodies across multiple SARS-CoV-2 strains revealed a diminished neutralization efficacy against the ο variants, primarily attributed to the electrostatic repulsion between the antibodies and RBD interface. Considering the characteristics of the ο variant and the trajectory of emerging strains, we propose that newly developed antibodies against SARS-CoV-2 RBD should have surfaces rich in negative potential and, postbinding, exhibit strong van der Waals interactions. These findings provide invaluable guidance for the formulation of future therapeutic strategies.

Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors

The ability Gram-negative pathogens have at adapting and protecting themselves against antibiotics has increasingly become a public health threat. Data-driven models identifying molecular properties that correlate with outer membrane (OM) permeation and growth inhibition while avoiding efflux could guide the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa. The descriptors are derived from traditional approaches quantifying the compounds' intrinsic physicochemical properties, together with, bacterium-specific from ensemble docking of compounds targeting specific MexB binding pockets, and all-atom molecular dynamics simulations in different subregions of the OM model. Using these descriptors and the measured inhibitory concentrations, we design a statistical protocol to identify predictors of OM permeation/inhibition. We find consistent rules across most of our data highlighting the role of the interaction between the compounds and the OM. An implementation of the rules uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Our analysis sheds new light on the key properties drug candidates need to effectively permeate/inhibit P. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens.

Substituted Oligosaccharides as Protein Mimics: Deep Learning Free Energy Landscapes

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

Molecular dynamics simulations of the effect of starch on transport of water and ions through graphene nanopores

CONTEXT

We use molecular dynamics simulations to unravel the molecular level mechanisms underlying the structure and dynamics of water and ions flowing through nanoporous starch-graphene membranes. Our findings indicate that there is a significant tendency for the formation of short-range order in close proximity to the graphene membrane surface. This leads to a greater concentration of water and ions, suggesting strong interactions between the membrane and the saltwater solution. Furthermore, we found that the starch-graphene membrane was most efficient in sieving out ions when the starch loading is 15 wt.%, and the pore diameter is 14 Å. At these conditions, the starch-graphene membrane showed a high water transport rate and maintained a high level of ion rejection.

METHODS

We investigated the effect of loading of starch and the pore diameter on the pressure-induced transport, structure, and dynamics of Na+, Cl-, and water using the GROMACS 2021.4 package. We further analyze the density profiles of water and ions in the context of ion-polymer and water-polymer interactions and provide mechanistic insights into the piston-induced flow of saltwater through the starch-graphene membranes using Visual Molecular Dynamics (VMD) software.

Mass Spectrometry Analysis of Glycopeptides Enriched by Anion Exchange-Mediated Methods Reveals PolyLacNAc-Extended N-Glycans in Integrins and Tetraspanins in Melanoma Cells

Glycosylation is a key modulator of the functional state of proteins. Recent developments in large-scale analysis of intact glycopeptides have enabled the identification of numerous glycan structures that are relevant in pathophysiological processes. However, one motif found in N-glycans, poly-N-acetyllactosamine (polyLacNAc), still poses a substantial challenge to mass spectrometry-based glycoproteomic analysis due to its relatively low abundance and large size. In this work, we developed approaches for the systematic mapping of polyLacNAc-elongated N-glycans in melanoma cells. We first evaluated five anion exchange-based matrices for enriching intact glycopeptides and selected two materials that provided better overall enrichment efficiency. We then tested the robustness of the methodology by quantifying polyLacNAc-containing glycopeptides as well as changes in protein fucosylation and sialylation. Finally, we applied the optimal enrichment methods to discover glycopeptides containing polyLacNAc motifs in melanoma cells and found that integrins and tetraspanins are substantially modified with these structures. This study demonstrates the feasibility of glycoproteomic approaches for identification of glycoproteins with polyLacNAc motifs.

The impact of glycosylation on the structure, function, and interactions of CD14

CD14 is an innate immune receptor that senses pathogen-associated molecular patterns, such as lipopolysaccharide, to activate the innate immune response. Although CD14 is known to be glycosylated, detailed understanding about the structural and functional significance of this modification is still missing. Herein, an NMR and MS-based study, assisted by MD simulations, has provided a 3D-structural model of glycosylated CD14. Our results reveal the existence of a key N-glycosylation site at Asn282 that exclusively contains unprocessed oligomannnose N-glycans that perfectly fit the concave cavity of the bent-solenoid shaped protein. This site is not accessible to glycosidases and is fundamental for protein folding and secretion. A second N-site at Asn151 displays mostly complex N-glycans, with the typical terminal epitopes of the host cell-line expression system (i.e. βGal, α2,3 and α2,6 sialylated βGal, here), but also particularities, such as the lack of core fucosylation. The glycan at this site points outside the protein surface, resulting in N-glycoforms fully exposed and available for interactions with lectins. In fact, NMR experiments show that galectin-4, proposed as a binder of CD14 on monocytes to induce their differentiation into macrophages-like cells, interacts in vitro with CD14 through the recognition of the terminal glycoepitopes on Asn151. This work provides key information about CD14 glycosylation, which helps to better understand its functional roles and significance. Although protein glycosylation is known to be dynamic and influenced by many factors, some of the features found herein (presence of unprocessed N-glycans and lack of core Fuc) are likely to be protein specific.

Computational insights into the circular permutation roles on ConA binding and structural stability

The mechanisms behind Concanavalin A (ConA) circular permutation have been under investigation since 1985. Although a vast amount of information is available about this lectin and its applications, the exact purpose of its processing remains unclear. To shed light on this, this study employed computer simulations to compare the unprocessed ProConA with the mature ConA. This approach aimed to reveal the importance of the post-translational modifications, especially how they affect the lectin stability and carbohydrate-binding properties. To achieve these goals, we conducted 200 ns molecular dynamics simulations and trajectory analyses on the monomeric forms of ProConA and ConA (both unbound and in complex with D-mannose and the GlcNAc2Man9 N-glycan), as well as on their oligomeric forms. Our findings reveal significant stability differences between ProConA and ConA at both the monomeric and tetrameric levels, with ProConA exhibiting consistently lower stability parameters compared to ConA. In terms of carbohydrate binding properties, however, both lectins showed remarkable similarities in their interaction profiles, contact numbers, and binding free energies with D-mannose and the high-mannose N-glycan. Overall, our results suggest that the processing of ProConA significantly enhances the stability of the mature lectin, especially in maintaining the tetrameric oligomer, without substantially affecting its carbohydrate-binding properties.

Solid Wood Modification toward Anisotropic Elastic and Insulative Foam-Like Materials

The methods used to date to produce compressible wood foam by top-down approaches generally involve the removal of lignin and hemicelluloses. Herein, we introduce a route to convert solid wood into a super elastic and insulative foam-like material. The process uses sequential oxidation and reduction with partial removal of lignin but high hemicellulose retention (process yield of 72.8%), revealing fibril nanostructures from the wood's cell walls. The elasticity of the material is shown to result from a lamellar structure, which provides reversible shape recovery along the transverse direction at compression strains of up to 60% with no significant axial deformation. The compressibility is readily modulated by the oxidation degree, which changes the crystallinity and mobility of the solid phase around the lumina. The performance of the highly resilient foam-like material is also ascribed to the amorphization of cellulosic fibrils, confirmed by experimental and computational (molecular dynamics) methods that highlight the role of secondary interactions. The foam-like wood is optionally hydrophobized by chemical vapor deposition of short-chained organosilanes, which also provides flame retardancy. Overall, we introduce a foam-like material derived from wood based on multifunctional nanostructures (anisotropically compressible, thermally insulative, hydrophobic, and flame retardant) that are relevant to cushioning, protection, and packaging.

Insights in inulin binding and inulin oligosaccharide formation by novel multi domain endo-inulinases from Botrytis cinerea

World-wide, pathogenic fungi such as Botrytis cinerea cause tremendous yield losses in terms of food production and post-harvest food decay. Many fungi produce inulin-type oligosaccharides (IOSs) from inulin through endo-inulinases which typically show a two domain structure. B.cinerea lacks a two domain endo-inulinase but contains a three domain structure instead. Genome mining revealed three and four domain (d4) enzymes in the fungal kingdom. Here, three and two domain enzymes were compared in their capacity to produce IOSs from inulin. Hill kinetics were observed in three domain enzymes as compared to Michaelis-Menten kinetics in two domain enzymes, suggesting that the N-terminal extension functions as a carbohydrate binding module. Analysis of the IOS product profiles generated from purified GF6, GF12, GF16 and GF18 inulins and extensive sugar docking approaches led to enhanced insights in the active site functioning, revealing subtle differences between the endo-inulinases from Aspergillus niger and B. cinerea. Improved insights in structure-function relationships in fungal endo-inulinases offer opportunities to develop superior enzymes for the production of specific IOS formulations to improve plant and animal health (priming agents, prebiotics).

Machine Learning-Based Interfacial Tension Equations for (H2 + CO2)-Water/Brine Systems over a Wide Range of Temperature and Pressure

Large-scale underground hydrogen storage (UHS) plays a vital role in energy transition. H2-brine interfacial tension (IFT) is a crucial parameter in structural trapping in underground geological locations and gas-water two-phase flow in subsurface porous media. On the other hand, cushion gas, such as CO2, is often co-injected with H2 to retain reservoir pressure. Therefore, it is imperative to accurately predict the (H2 + CO2)-water/brine IFT under UHS conditions. While there have been a number of experimental measurements on H2-water/brine and (H2 + CO2)-water/brine IFT, an accurate and efficient (H2 + CO2)-water/brine IFT model under UHS conditions is still lacking. In this work, we use molecular dynamics (MD) simulations to generate an extensive (H2 + CO2)-water/brine IFT databank (840 data points) over a wide range of temperature (from 298 to 373 K), pressure (from 50 to 400 bar), gas composition, and brine salinity (up to 3.15 mol/kg) for typical UHS conditions, which is used to develop an accurate and efficient machine learning (ML)-based IFT equation. Our ML-based IFT equation is validated by comparing to available experimental data and other IFT equations for various systems (H2-brine/water, CO2-brine/water, and (H2 + CO2)-brine/water), rendering generally good performance (with R2 = 0.902 against 601 experimental data points). The developed ML-based IFT equation can be readily applied and implemented in reservoir simulations and other UHS applications.

Dissecting the Conformational Stability of a Glycan Hairpin

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

MA'AT Analysis: Unbiased Multi-State Conformational Modeling of Exocyclic Hydroxymethyl Group Conformation in Methyl Aldohexopyranosides

MA'AT analysis (J. Chem. Inf. Model. 2022, 62, 3135-3141) has been applied to model exocyclic hydroxymethyl group conformation in methyl β-D-glucopyranoside (βGlcOMe), methyl β-D-galactopyranoside (βGalOMe), and methyl β-D-mannopyranoside (βManOMe) in an unbiased manner. Using up to eight NMR J-couplings sensitive to rotation about the C5-C6 bond (torsion angle ω), two-state models of ω were obtained that are qualitatively consistent with the relative populations of the gg, gt, and tg rotamers reported previously. MA'AT analysis gave consistent unbiased gt ⇌ tg models of ω in βGalOMe, with gt more populated than tg and mean values of ω for each population similar to those obtained from aqueous 1-μs MD simulation. Using different combinations of J-couplings had little effect on the βGalOMe model in terms of the mean values of ω and circular standard deviations (CSDs). In contrast, MA'AT analysis of ω in βGlcOMe and βManOMe produced more than one two-state model independent of the ensemble of J-values used in the analyses. These models were characterized by gg ⇌ gt conformer exchange as expected, but the mean values of ω in both conformers varied significantly in the different fits, especially for the gg rotamer. Constrained (biased) MA'AT analyses in which only staggered geometries about ω were allowed gave RMSDs slightly larger than those obtained from the unbiased fits, precluding an assignment of an unbiased model. It is unclear why MA'AT analysis gives consistent and predictable unbiased models of ω in βGalOMe but not in βGlcOMe and βManOMe. One possibility is that the distribution of ω in one or both of the gg and gt conformers in the latter does not conform to a von Mises function (i.e., is not Gaussian-like), but rather to a broad and/or flat distribution that cannot be fit by the current version of MA'AT. Nevertheless, the results of this study provide new evidence of the ability of MA'AT analysis to treat multi-state conformational exchange using only experimental NMR data, extending recent MA'AT applications to furanosyl ring pseudorotation (Biochemistry 2022, 61, 239-251).

Multiscale structure changes and mechanism of polyphenol-amylose complexes modulated by polyphenolic structures

This study was designed to investigate the effect of polyphenolic structure on the interaction strength and process between polyphenols (gallic acid (GA), epigallocatechin gallate (EGCG) and tannic acid (TA)) and amylose (AM). The results of Fourier transform infrared spectroscopy, isothermal titration calorimetry, X-ray photoelectron spectroscopy and molecular dynamic simulation (MD) suggested that the interactions between the three polyphenols and AM were noncovalent, spontaneous, low-energy and driven by enthalpy, which would be enhanced with increasing amounts of pyrogallol groups in the polyphenols. The results of turbidity, particle size and appearance of the complex solution showed that the interaction process between polyphenols and AM could be divided into three steps and would be advanced by increasing the number of pyrogallol groups in the polyphenols. At the same time, MD was intuitively employed to exhibit the interaction process between amylose and polyphenols, and it revealed that the interaction induced the aggregation of amylose and that the agglomeration degree of amylose increased with increasing number of pyrogallol groups at polyphenols. Last, the SEM and TGA results showed that TA/AM complexes had the tightest structure and the highest thermal stability (TA/AM˃EGCG/AM˃GA/AM), which could be attributed to TA having five pyrogallol groups.

Evolution of Phosphorylase Activity in an Ancestral Glycosyltransferase

The reconstruction of ancestral sequences can offer a glimpse into the fascinating process of molecular evolution by exposing the adaptive pathways that shape the proteins found in nature today. Here, we track the evolution of the carbohydrate-active enzymes responsible for the synthesis and turnover of mannogen, a critical carbohydrate reserve in Leishmania parasites. Biochemical characterization of resurrected enzymes demonstrated that mannoside phosphorylase activity emerged in an ancestral bacterial mannosyltransferase, and later disappeared in the process of horizontal gene transfer and gene duplication in Leishmania. By shuffling through plausible historical sequence space in an ancestral mannosyltransferase, we found that mannoside phosphorylase activity could be toggled on through various combinations of mutations at positions outside of the active site. Molecular dynamics simulations showed that such mutations can affect loop rigidity and shield the active site from water molecules that disrupt key interactions, allowing α-mannose 1-phosphate to adopt a catalytically productive conformation. These findings highlight the importance of subtle distal mutations in protein evolution and suggest that the vast collection of natural glycosyltransferases may be a promising source of engineering templates for the design of tailored phosphorylases.

Mechanistic insights into ligand dissociation from the SARS-CoV-2 spike glycoprotein

The COVID-19 pandemic, driven by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spurred an urgent need for effective therapeutic interventions. The spike glycoprotein of the SARS-CoV-2 is crucial for infiltrating host cells, rendering it a key candidate for drug development. By interacting with the human angiotensin-converting enzyme 2 (ACE2) receptor, the spike initiates the infection of SARS-CoV-2. Linoleate is known to bind the spike glycoprotein, subsequently reducing its interaction with ACE2. However, the detailed mechanisms underlying the protein-ligand interaction remain unclear. In this study, we characterized the pathways of ligand dissociation and the conformational changes associated with the spike glycoprotein by using ligand Gaussian accelerated molecular dynamics (LiGaMD). Our simulations resulted in eight complete ligand dissociation trajectories, unveiling two distinct ligand unbinding pathways. The preference between these two pathways depends on the gate distance between two α-helices in the receptor binding domain (RBD) and the position of the N-linked glycan at N343. Our study also highlights the essential contributions of K417, N121 glycan, and N165 glycan in ligand unbinding, which are equally crucial in enhancing spike-ACE2 binding. We suggest that the presence of the ligand influences the motions of these residues and glycans, consequently reducing accessibility for spike-ACE2 binding. These findings enhance our understanding of ligand dissociation from the spike glycoprotein and offer significant implications for drug design strategies in the battle against COVID-19.

Family 3 CBM improves the biochemical properties, substrate hydrolysis and coconut oil extraction by hemicellulolytic and holocellulolytic chimeras

To understand the influence of family 3 Carbohydrate Binding Module (hereafter CBM3), single (GH5 cellulase; CelB, CelBΔCBM), bi-chimeric [GH26 endo-mannanase (ManB-1601) and GH11 endo-xylanase (XynB); ManB-XynB [1], ManB-XynB-CBM] and tri-chimeric [ManB-XynB-CelB [1], ManB-XynB-CelBΔCBM] enzyme variants (fused or deleted of CBM) were produced and purified to homogeneity. CBM3 did not alter the pH and temperature optima of bi- and tri-chimeric enzymes but improved the pH and temperature stability of ManB in CBM variants of bi-/tri-chimeric enzymes. Truncation of CBM in CelB shifted the pH optimum and increased the melting temperature (Tm 65 ℃). CBM3 improved both substrate affinity (Km) and catalytic efficiency (kcat/Km) of fused enzymes in tri-chimera and CelB but only Km for bi-chimera. Far-UV CD of CelB and bi- and tri-chimeric enzymes suggested that CBM3 improved the α-helical content and compactness in the native state but did not prevent disintegration of secondary structural contents at acidic pH. Steady-state fluorescence studies suggested that under acidic conditions CBM3 prevented the exposure of hydrophobic patches in bi-chimeric protein but could not avert the opening up of chimeric enzyme structure. Aqueous enzyme assisted treatment of mature coconut kernel using single, bi- and tri-chimeric enzymes led to cracks, peeling and fracturing of the matrix and improved the oil yield by up to 22%.

Structural changes of layer-by-layer self-assembled starch-based nanocapsules in the gastrointestinal tract: Implications for their M cell-targeting delivery and transport efficiency

Characterizing the structural changes of cell-targeting delivery carriers in gastrointestinal tract (GIT) is crucial for understanding their effectiveness in cell targeting and transport. Herein, RGD peptide-grafted carboxymethyl starch (CMS) and cationic quaternary ammonium starch (QAS) were utilized to fabricate quintet-layered nanocapsules loaded with ovalbumin (OVA). The aim was to improve delivery and transportation efficiency, specifically targeting M cells. The research analyzed the impact of pH and enzyme variations in GIT on the structure of nanocapsules, interactions between carriers and the release behavior of OVA. Results showed that the size of nanocapsules increased from 229.2 to 479.8 nm and the zeta potential decreased from -1.08 to -33.33 mV during oral delivery. This was evident in TEM images, showing a more relaxed core-shell structure. Isothermal titration calorimetry and molecular dynamic simulation indicated that pH changes primarily affected the electrostatic interaction between carriers. Increasing pH led to reduced affinity constants, and around 84.42 % of OVA was successfully delivered to M cells. Moreover, the transport efficiency of nanocapsules to M cells was five times greater than that of Caco-2 cells. This suggests the feasibility of developing a nanocapsules delivery system capable of adapting to pH changes in GIT by regulating electrostatic interactions between carriers.

Improved lipase performance by covalent immobilization of Candida antarctica lipase B on amino acid modified microcrystalline cellulose as green renewable support

Development of immobilized lipase with excellent catalytic performance and low cost is the major challenge for large-scale industrial applications. In this study, green renewable microcrystalline cellulose (MCC) that was hydrophobically modified with D-alanine (Ala) or L-lysine (Lys) was used for immobilizing Candida antarctica lipase B (CALB). The improved catalytic properties were investigated by experimental and computational methods. CALB immobilized on MCC-Ala with higher hydrophobicity showed better catalytic activity than CALB@MCC-Lys because the increased flexibility of the lid region of CALB@MCC-Ala favored the formation of open conformation. Additionally, the low root mean square deviation and the high β-sheet and α-helix contents of CALB@MCC-Ala indicated that the structure became more stable, leading to a significantly enhanced stability (54.80% and 90.90% relative activity at 70 °C and pH 9.0, respectively) and good reusability (48.92% activity after 5 cycles). This study provides a promising avenue to develop immobilized lipase with high catalytic properties for industry applications.

Rapid simulation of glycoprotein structures by grafting and steric exclusion of glycan conformer libraries

Most membrane proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, shielding potentially large fractions of protein surface. High glycan conformational freedom hinders complete structural elucidation of glycoproteins. Computer simulations may be used to model glycosylated proteins but require hundreds of thousands of computing hours on supercomputers, thus limiting routine use. Here, we describe GlycoSHIELD, a reductionist method that can be implemented on personal computers to graft realistic ensembles of glycan conformers onto static protein structures in minutes. Using molecular dynamics simulation, small-angle X-ray scattering, cryoelectron microscopy, and mass spectrometry, we show that this open-access toolkit provides enhanced models of glycoprotein structures. Focusing on N-cadherin, human coronavirus spike proteins, and gamma-aminobutyric acid receptors, we show that GlycoSHIELD can shed light on the impact of glycans on the conformation and activity of complex glycoproteins.

The conformational dynamics of Hepatitis C Virus E2 glycoprotein with the increasing number of N-glycosylation unraveled by molecular dynamics simulations

The Hepatitis C Virus (HCV), responsible for causing hepatitis and a significant contributor to liver disorders, presents a challenge for treatment due to its high genetic variability. Despite efforts, there is still no effective medication available for this virus. One of the promising targets for drug development involves targeting glycoprotein E2. However, our understanding of the dynamic behavior of E2 and its associated glycans remains limited. In this study, we investigated the dynamic characteristics of E2 with varying degrees of glycosylation using all-atom molecular dynamics simulations. We also explored glycan's interactions with the protein and among themselves. An overall increase in correlation between the vital protein regions was observed with an increase in glycan number. The protein dynamics is followed by the analysis of glycan dynamics, where the flexibility of the individual glycans was analyzed in their free and bound state, which revealed a decrease in their fluctuation in some cases. Furthermore, we generated the free energy landscape of individual N-glycan linkages in both free and bound states and observed both increases and decreases in flexibility, which can be attributed to the formation and breakage of hydrogen bonds with amino acids. Finally, we found that for a high glycosylation system, glycans interact with glycoprotein and form hydrogen bonds among themselves. Moreover, the hydrogen bond profiles of a given glycan can vary when influenced by other glycans. In summary, our study provides valuable insights into the dynamics of the core region of HCV E2 glycoprotein and its associated glycans.Communicated by Ramaswamy H. Sarma.

Elucidating the glycan-binding specificity and structure of Cucumis melo agglutinin, a new R-type lectin

Plant lectins have garnered attention for their roles as laboratory probes and potential therapeutics. Here, we report the discovery and characterization of Cucumis melo agglutinin (CMA1), a new R-type lectin from melon. Our findings reveal CMA1's unique glycan-binding profile, mechanistically explained by its 3D structure, augmenting our understanding of R-type lectins. We expressed CMA1 recombinantly and assessed its binding specificity using multiple glycan arrays, covering 1,046 unique sequences. This resulted in a complex binding profile, strongly preferring C2-substituted, beta-linked galactose (both GalNAc and Fuca1-2Gal), which we contrasted with the established R-type lectin Ricinus communis agglutinin 1 (RCA1). We also report binding of specific glycosaminoglycan subtypes and a general enhancement of binding by sulfation. Further validation using agglutination, thermal shift assays, and surface plasmon resonance confirmed and quantified this binding specificity in solution. Finally, we solved the high-resolution structure of the CMA1 N-terminal domain using X-ray crystallography, supporting our functional findings at the molecular level. Our study provides a comprehensive understanding of CMA1, laying the groundwork for further exploration of its biological and therapeutic potential.

Unraveling Molecular Recognition of Glycan Ligands by Siglec-9 via NMR Spectroscopy and Molecular Dynamics Modeling

Human sialic-acid-binding immunoglobulin-like lectin-9 (Siglec-9) is a glycoimmune checkpoint receptor expressed on several immune cells. Binding of Siglec-9 to sialic acid containing glycans (sialoglycans) is well documented to modulate its functions as an inhibitory receptor. Here, we first assigned the amino acid backbone of the Siglec-9 V-set domain (Siglec-9d1), using well-established triple resonance three-dimensional nuclear magnetic resonance (NMR) methods. Then, we combined solution NMR and molecular dynamic simulation methods to decipher the molecular details of the interaction of Siglec-9 with the natural ligands α2,3 and α2,6 sialyl lactosamines (SLN), sialyl Lewis X (sLeX), and 6-O sulfated sLeX and with two synthetically modified sialoglycans that bind with high affinity. As expected, Neu5Ac is accommodated between the F and G β-strands at the canonical sialic acid binding site. Addition of a heteroaromatic scaffold 9N-5-(2-methylthiazol-4-yl)thiophene sulfonamide (MTTS) at the C9 position of Neu5Ac generates new interactions with the hydrophobic residues located at the G-G' loop and the N-terminal region of Siglec-9. Similarly, the addition of the aromatic substituent (5-N-(1-benzhydryl-1H-1,2,3-triazol-4-yl)methyl (BTC)) at the C5 position of Neu5Ac stabilizes the conformation of the long and flexible B'-C loop present in Siglec-9. These results expose the underlying mechanism responsible for the enhanced affinity and specificity for Siglec-9 for these two modified sialoglycans and sheds light on the rational design of the next generation of modified sialoglycans targeting Siglec-9.

Glycosaminoglycan-mimetic infernan grafted with poly(N-isopropylacrylamide): Toward a thermosensitive polysaccharide

Glycosaminoglycans (GAGs) are essential constituents of the cell surface and extracellular matrix, where they are involved in several cellular processes through their interactions with various proteins. For successful tissue regeneration, developing an appropriate matrix supporting biological activities of cells in a similar manner than GAGs remains still challenging. In this context, this study aims to design a thermosensitive polysaccharide that could further be used as hydrogel for tissue engineering applications. For this purpose, infernan, a marine bacterial exopolysaccharide (EPS) endowed with GAG-mimetic properties was grafted with a thermosensitive polymer, poly(N-isopropylacrylamide) (pNIPAM). Eight grafted polysaccharides were obtained by varying EPS/pNIPAM molar ratio and the molecular weight of pNIPAM. Their physicochemical characteristics and their thermosensitive properties were determined using a multi-technique, experimental approach. In parallel, molecular dynamics and Monte Carlo simulations were applied at two different scales to elucidate, respectively, the molecular conformation of grafted infernan chain and their ability to form an infinite network undergoing a sol-gel transition near the percolation, a necessary condition in hydrogel formation. It comes out from this study that thermosensitive infernan was successfully developed and its potential use in tissue regeneration as a hydrogel scaffold will further be assessed.

Computational Procedure for Predicting Excipient Effects on Protein-Protein Affinities

Protein-protein interactions lie at the center of many biological processes and are a challenge in formulating biological drugs, such as antibodies. A key to mitigating protein association is to use small-molecule additives, i.e., excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials, and a thermodynamic perturbation theory. In a proof of principle, this method successfully ranks the order of four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting the effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.

The structure of a C. neoformans polysaccharide motif recognized by protective antibodies: A combined NMR and MD study

Cryptococcus neoformans is a fungal pathogen responsible for cryptococcosis and cryptococcal meningitis. The C. neoformans' capsular polysaccharide and its shed exopolysaccharide function both as key virulence factors and to protect the fungal cell from phagocytosis. Currently, a glycoconjugate of these polysaccharides is being explored as a vaccine to protect against C. neoformans infection. In this study, NOE and J-coupling values from NMR experiments were consistent with a converged structure of the synthetic decasaccharide, GXM10-Ac3, calculated from MD simulations. GXM10-Ac3 was designed as an extension of glucuronoxylomannan (GXM) polysaccharide motif (M2) which is common in the clinically predominant serotype A strains and is recognized by protective forms of GXM-specific monoclonal antibodies. The M2 motif is a hexasaccharide with a three-residue α-mannan backbone, modified by β-(1→2)-xyloses (Xyl) on the first two mannoses (Man) and a β-(1→2)-glucuronic acid (GlcA) on the third Man. Combined NMR and MD analyses reveal that GXM10-Ac3 adopts an extended structure, with Xyl/GlcA branches alternating sides along the α-mannan backbone. O-acetyl esters also alternate sides and are grouped in pairs. MD analysis of a twelve M2-repeating unit polymer supports the notion that the GXM10-Ac3 structure is uniformly represented throughout the polysaccharide. This derived GXM model displays high flexibility while maintaining a structural identity, yielding insights to further explore intermolecular interactions between polysaccharides, interactions with anti-GXM mAbs, and the cryptococcal polysaccharide architecture.

Ion transport mechanisms in pectin-containing EC-LiTFSI electrolytes

Using all-atom molecular dynamics simulations, we report the structure and ion transport characteristics of a new class of solid polymer electrolytes that contain the biodegradable and mechanically stable biopolymer pectin. We used highly conducting ethylene carbonate (EC) as a solvent for simulating lithium-trifluoromethanesulfonimide (LiTFSI) salt containing different weight percentages of pectin. Our simulations reveal that the pectin chains reduce the coordination number of lithium ions around their counterions (and vice versa) because of stronger lithium-pectin interactions compared to lithium-TFSI interactions. Furthermore, the pectin is found to promote smaller ionic aggregates over larger ones, in contrast to the results typically reported for liquid and polymer electrolytes. We observed that the loading of pectin in EC-LiTFSI electrolytes increases their viscosity (η) and relaxation timescales (τc), indicating higher mechanical stability, and, consequently, a decrease of the mean squared displacement, diffusion coefficient (D), and Nernst-Einstein conductivity (σNE). Interestingly, while the lithium diffusivities are related to the ion-pair relaxation timescales as D+ ∼ τc-3.1, the TFSI- diffusivities exhibit excellent correlations with ion-pair relaxation timescales as D- ∼ τc-0.95. On the other hand, the NE conductivities are dictated by distinct transport mechanisms and scales with ion-pair relaxation timescales as σNE ∼ τc-1.85.

Mapping secondary substrate-binding sites on the GH11 xylanase from Bacillus subtilis

Xylanases are of significant interest for biomass conversion technologies. Here, we investigated the allosteric regulation of xylan hydrolysis by the Bacillus subtilis GH11 endoxylanase. Molecular dynamics simulations (MDS) in the presence of xylobiose identified binding to the active site and two potential secondary binding sites (SBS) around surface residues Asn54 and Asn151. Arabinoxylan titration experiments with single cysteine mutants N54C and N151C labeled with the thiol-reactive fluorophore acrylodan or the ESR spin-label MTSSL validated the MDS results. Ligand binding at the SBS around Asn54 confirms previous reports, and analysis of the second SBS around N151C discovered in the present study includes residues Val98/Ala192/Ser155/His156. Understanding the regulation of xylanases contributes to efforts for industrial decarbonization and to establishing a sustainable energy matrix.

Hyaluronan-arginine enhanced and dynamic interaction emerges from distinctive molecular signature due to electrostatics and side-chain specificity

Hyaluronan is a natural carbohydrate polymer with a negative charge that fosters gel-like conditions crucial for its cellular functions and industrial applications. As a recognized ligand for proteins, understanding their mutual interactions provides solid ground to tune hyaluronan's gel properties using biocompatible peptides. This work employs NMR and molecular dynamics simulations to identify molecular motifs relevant to hyaluronan-peptide interactions using arginine, lysine, and glycine oligopeptides. Arginine-rich peptides exhibit the strongest binding to hyaluronan according to chemical shift perturbation measurements, followed distantly by the similarly charged lysine. This difference highlights the significance of electrostatics and the peculiarities of the guanidinium side chain in arginine, capable of non-polar interactions that further stabilize the binding. Additional nuclear Overhauser effect measurements do not show stable interaction partners, precluding strong and well-defined complexes. Finally, molecular simulations support our findings and show an extended but significant interaction region, especially for arginine, responsible for the observed enhanced binding, which can also promote cross-linking of hyaluronan polymers. Our findings pave the way for optimizing biocompatible peptides to alter hyaluronan gels' properties efficiently and also explain why hyaluronan-protein interaction typically involves positively charged arginine-rich regions also capable of forming hydrogen bonds and non-polar interactions.

Characterization of Various Noncovalent Polyphenol-Starch Complexes and Their Prebiotic Activities during In Vitro Digestion and Fermentation

This study explores the structural characterization of six noncovalent polyphenol-starch complexes and their prebiotic activities during in vitro digestion and fermentation. Ferulic acid, caffeic acid, gallic acid, isoquercetin, astragalin, and hyperin were complexed with sweet potato starch (SPS). The polyphenols exhibited high binding capacity (>70%) with SPS. A partial release of flavonoids from the complexes was observed via in vitro digestion, while the phenolic acids remained tightly bound. Molecular dynamics (MD) simulation revealed that polyphenols altered the spatial configuration of polysaccharides and intramolecular hydrogen bonds formed. Additionally, polyphenol-SPS complexes exerted inhibitory effects on starch digestion compared to gelatinized SPS, owing to the increase in resistant starch fraction. It revealed that the different complexes stimulated the growth of Lactobacillus rhamnosus and Bifidobacterium bifidum, while inhibiting the growth of Escherichia coli. Moreover, in vitro fermentation experiments revealed that complexes were utilized by the gut microbiota, resulting in the production of short-chain fatty acids and a decrease in pH. In addition, the polyphenol-SPS complexes altered the composition of gut microbiota by promoting the growth of beneficial bacteria and decreasing pathogenic bacteria. Polyphenol-SPS complexes exhibit great potential for use as a prebiotic and exert dual beneficial effects on gut microbiota.

SIRAH Late Harvest: Coarse-Grained Models for Protein Glycosylation

Glycans constitute one of the most complex families of biological molecules. Despite their crucial role in a plethora of biological processes, they remain largely uncharacterized because of their high complexity. Their intrinsic flexibility and the vast variability associated with the many combination possibilities have hampered their experimental determination. Although theoretical methods have proven to be a valid alternative to the study of glycans, the large size associated with polysaccharides, proteoglycans, and glycolipids poses significant challenges to a fully atomistic description of biologically relevant glycoconjugates. On the other hand, the exquisite dependence on hydrogen bonds to determine glycans' structure makes the development of simplified or coarse-grained (CG) representations extremely challenging. This is particularly the case when glycan representations are expected to be compatible with CG force fields that include several molecular types. We introduce a CG representation able to simulate a wide variety of polysaccharides and common glycosylation motifs in proteins, which is fully compatible with the CG SIRAH force field. Examples of application to N-glycosylated proteins, including antibody recognition and calcium-mediated glycan-protein interactions, highlight the versatility of the enlarged set of CG molecules provided by SIRAH.

Enhancing solubility and stability of piperine using β-cyclodextrin derivatives: computational and experimental investigations

Piperine (PP), a natural alkaloid found in black pepper, possesses significant bioactivities. However, its use in pharmaceutical applications is hindered by low water solubility and susceptibility to UV light degradation. To overcome these challenges, we investigated the potential of β-cyclodextrin (βCD) and its derivatives with dimethyl (DMβCD), hydroxy-propyl (HPβCD) and sulfobutyl-ether (SBEβCD) substitutions to enhance the solubility and stability of PP. This study employed computational and experimental approaches to examine the complexation between PP and βCDs. The results revealed the formation of two types of inclusion complexes: the P-form and M-form involving the insertion of piperidine moiety and the methylene-di-oxy-phenyl moiety, respectively. These complexes primarily rely on van der Waals interactions. Among the three derivatives, the PP/SBEβCD complex exhibited the highest stability followed by HPβCD, as attributed to maximum atom contacts and minimal solvent accessibility. Solubility studies confirmed the formation of inclusion complexes in a 1:1 ratio. Notably, the stability constant of the inclusion complex was approximately two-fold higher with SBEβCD and HPβCD compared to βCD. The DSC thermograms provided confirmation of the formation of the inclusion complex between the host and guest. These findings highlight the potential of βCD derivatives to effectively encapsulate PP, improving its solubility and presenting new opportunities for its pharmaceutical applications.Communicated by Ramaswamy H. Sarma.

Structure-Guided Approach for the Development of MUC1-Glycopeptide-Based Cancer Vaccines with Predictable Responses

Mucin-1 (MUC1) glycopeptides are exceptional candidates for potential cancer vaccines. However, their autoantigenic nature often results in a weak immune response. To overcome this drawback, we carefully engineered synthetic antigens with precise chemical modifications. To be effective and stimulate an anti-MUC1 response, artificial antigens must mimic the conformational dynamics of natural antigens in solution and have an equivalent or higher binding affinity to anti-MUC1 antibodies than their natural counterparts. As a proof of concept, we have developed a glycopeptide that contains noncanonical amino acid (2S,3R)-3-hydroxynorvaline. The unnatural antigen fulfills these two properties and effectively mimics the threonine-derived antigen. On the one hand, conformational analysis in water shows that this surrogate explores a landscape similar to that of the natural variant. On the other hand, the presence of an additional methylene group in the side chain of this analog compared to the threonine residue enhances a CH/π interaction in the antigen/antibody complex. Despite an enthalpy-entropy balance, this synthetic glycopeptide has a binding affinity slightly higher than that of its natural counterpart. When conjugated with gold nanoparticles, the vaccine candidate stimulates the formation of specific anti-MUC1 IgG antibodies in mice and shows efficacy comparable to that of the natural derivative. The antibodies also exhibit cross-reactivity to selectively target, for example, human breast cancer cells. This investigation relied on numerous analytical (e.g., NMR spectroscopy and X-ray crystallography) and biophysical techniques and molecular dynamics simulations to characterize the antigen-antibody interactions. This workflow streamlines the synthetic process, saves time, and reduces the need for extensive, animal-intensive immunization procedures. These advances underscore the promise of structure-based rational design in the advance of cancer vaccine development.