GROMOS 53A6GLYC, an Improved GROMOS Force Field for Hexopyranose-Based Carbohydrates

All-atom molecular dynamics simulations of polymer and polyelectrolyte brushes

Densely grafted polymer and polyelectrolyte (PE) brushes, owing to their significant abilities to functionalize surfaces for a plethora of applications in sensing, diagnostics, current rectification, surface wettability modification, drug delivery, and oil recovery, have attracted significant attention over the past several decades. Unfortunately, most of the attention has primarily focused on understanding the properties of the grafted polymer and the PE chains with little attention devoted to studying the behavior of the brush-supported ions (counterions needed to screen the PE chains) and water molecules. Over the past few years, our group has been at the forefront of addressing this gap: we have employed all-atom molecular dynamics (MD) simulations for studying a wide variety of polymer and PE brush systems with specific attention to unraveling the properties and behavior of the brush-supported water molecules and ions. Our findings have revealed some of the most fascinating properties of such brush-supported ions and water molecules, including the most remarkable control of nanofluidic transport afforded by the specific ion and water responses induced by the PE brushes grafted on the inner walls of the nanochannel. This feature article aims to summarize some of our key contributions associated with such atomistic simulations of polymer and PE brushes and brush-supported water molecules and counterions.

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.

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 Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence

Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth, with rational drug design is promising. Rational drug design uses structural data and computational tools to study protein binding sites and protein interfaces to design inhibitors that can change these interactions, thereby potentially leading to therapeutic approaches. Artificial intelligence (AI), such as machine learning (ML) and deep learning (DL), has advanced drug discovery and design by providing computational resources and methods. Quantum chemistry is essential for drug reactivity, toxicology, drug screening, and quantitative structure-activity relationship (QSAR) properties. This review discusses the methodologies and challenges of identifying and characterizing hot spots and binding sites. It also explores the strategies and applications of artificial-intelligence-based rational drug design technologies that target proteins and protein-protein interaction (PPI) binding hot spots. It provides valuable insights for drug design with therapeutic implications. We have also demonstrated the pathological conditions of heat shock protein 27 (HSP27) and matrix metallopoproteinases (MMP2 and MMP9) and designed inhibitors of these proteins using the drug discovery paradigm in a case study on the discovery of drug molecules for cancer treatment. Additionally, the implications of benzothiazole derivatives for anticancer drug design and discovery are deliberated.

The SAMPL9 host-guest blind challenge: an overview of binding free energy predictive accuracy

We report the results of the SAMPL9 host-guest blind challenge for predicting binding free energies. The challenge focused on macrocycles from pillar[n]-arene and cyclodextrin host families, including WP6, and bCD and HbCD. A variety of methods were used by participants to submit binding free energy predictions. A machine learning approach based on molecular descriptors achieved the highest accuracy (RMSE of 2.04 kcal mol-1) among the ranked methods in the WP6 dataset. Interestingly, predictions for WP6 obtained via docking tended to outperform all methods (RMSE of 1.70 kcal mol-1), most of which are MD based and computationally more expensive. In general, methods applying force fields achieved better correlation with experiments for WP6 opposed to the machine learning and docking models. In the cyclodextrin-phenothiazine challenge, the ATM approach emerged as the top performing method with RMSE less than 1.86 kcal mol-1. Correlation metrics of ranked methods in this dataset were relatively poor compared to WP6. We also highlight several lessons learned to guide future work and help improve studies on the systems discussed. For example, WP6 may be present in other microstates other than its -12 state in the presence of certain guests. Machine learning approaches can be used to fine tune or help train force fields for certain chemistry (i.e. WP6-G4). Certain phenothiazines occupy distinct primary and secondary orientations, some of which were considered individually for accurate binding free energies. The accuracy of predictions from certain methods while starting from a single binding pose/orientation demonstrates the sensitivity of calculated binding free energies to the orientation, and in some cases the likely dominant orientation for the system. Computational and experimental results suggest that guest phenothiazine core traverses both the secondary and primary faces of the cyclodextrin hosts, a bulky cationic side chain will primarily occupy the primary face, and the phenothiazine core substituent resides at the larger secondary face.

Understanding Self-Assembly and Molecular Packing in Methylcellulose Aqueous Solutions Using Multiscale Modeling and Simulations

We present a multiscale molecular dynamics (MD) simulation study on self-assembly in methylcellulose (MC) aqueous solutions. First, using MD simulations with a new coarse-grained (CG) model of MC chains in implicit water, we establish how the MC chains self-assemble to form fibrils and fibrillar networks and elucidate the MC chains' packing within the assembled fibrils. The CG model for MC is extended from a previously developed model for unsubstituted cellulose and captures the directionality of H-bonding interactions between the -OH groups. The choice and placement of the CG beads within each monomer facilitates explicit modeling of the exact degree and position of methoxy substitutions in the monomers along the MC chain. CG MD simulations show that with increasing hydrophobic effect and/or increasing H-bonding strength, the commercial MC chains (with degree of methoxy substitution, DS, ∼1.8) assemble from a random dispersed configuration into fibrils. The assembled fibrils exhibit consistent fibril diameters regardless of the molecular weight and concentration of MC chains, in agreement with past experiments. Most MC chains' axes are aligned with the fibril axis, and some MC chains exhibit twisted conformations in the fibril. To understand the molecular driving force for the twist, we conduct atomistic simulations of MC chains preassembled in fibrils (without any chain twists) in explicit water at 300 and 348 K. These atomistic simulations also show that at DS = 1.8, MC chains adopt twisted conformations, with these twists being more prominent at higher temperatures, likely as a result of shielding of hydrophobic methyl groups from water. For MC chains with varying DS, at 348 K, atomistic simulations show a nonmonotonic effect of DS on water-monomer contacts. For 0.0 < DS < 0.6, the MC monomers have more water contacts than at DS = 0.0 or DS > 0.6, suggesting that with few methoxy substitutions, the MC chains are effectively hydrophilic, letting the water molecules diffuse into the fibril to participate in H-bonds with the MC chains' remaining -OH groups. At DS > 0.6, the MC monomers become increasingly hydrophobic, as seen by decreasing water contacts around each monomer. We conclude based on the atomistic observations that MC chains with lower degrees of substitutions (DS ≤ 0.6) should exhibit solubility in water over broader temperature ranges than DS ∼ 1.8 chains.

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.

Theoretical models of staurosporine and analogs uncover detailed structural information in biological solution

Staurosporine and its analogs (STA-analogs) are indolocarbazoles (ICZs) compounds able to inhibit kinase proteins in a non-specific way, while present antimicrobial and cytostatic properties. The knowledge of molecular features associated to the complexation, including the ligand shape in solution and thermodynamics of complexation, is substantial to the development of new bioactive ICZs with improved therapeutic properties. In this context, the empirical approach of GROMOS force field is able to accurately reproduce condensed phase physicochemical properties of molecular systems after parameterization. Hence, through parameterization under GROMOS force field and molecular simulations, we assessed STA-analogs dynamics in aqueous solution, as well as its interaction with water to probe conformational and structural features involved in complexation to therapeutic targets. The coexistence of multiple conformers observed in simulations, and confirmed by metadynamics calculations, expanding the conformational space knowledge of these ligands with potential implications in understanding the ligand conformational selection during complexation. Also, changes in availability to H-bonding concerning the different substituents and water can reflect on effects at complexation free energy due to variation at the desolvation energetic costs. Based on these results, we expect the obtained structural data provide systemic framework for rational chemical modification of STA-analogs.

Mechanistic Investigation of tert-Butanol's Impact on Biopharmaceutical Formulations: When Experiments Meet Molecular Dynamics

The use of tert-butyl alcohol for the lyophilization of pharmaceuticals has seen an uptick over the past years. Its advantages include increased solubility of hydrophobic drugs, enhanced product stability, shorter reconstitution time, and decreased processing time. While the mechanisms of protein stabilization exerted by cryo- and lyo-protectants are well known when water is the solvent of choice, little is known for organic solvents. This work investigates the interactions between two model proteins, namely, lactate dehydrogenase and myoglobin, and various excipients (mannitol, sucrose, 2-hydroxypropyl-β-cyclodextrin and Tween 80) in the presence of tert-butyl alcohol. We thermally characterized mixtures of these components by differential scanning calorimetry and freeze-drying microscopy. We also spectroscopically evaluated the protein recovery after freezing and freeze-drying. We additionally performed molecular dynamics simulations to elucidate the interactions in ternary mixtures of the herein-investigated excipients, tert-butyl alcohol and the proteins. Both experiments and simulations revealed that tert-butyl alcohol had a detrimental impact on the recovery of the two investigated proteins, and no combination of excipients yielded a satisfactory recovery when the organic solvent was present within the formulation. Simulations suggested that the denaturing effect of tert-butyl alcohol was related to its propensity to accumulate in the proximity of the peptide surface, especially near positively charged residues.

Revisiting the structural basis for biological activity of GMI-1070, a sialyl Lewisx mimetic

When it comes to the treatment of pathologies in which aberrant cell adhesion and extravasation from the bloodstream have been implicated, the selectins represent a central therapeutic target. In this context, the present work investigates the conformational landscape of two prototypes for the design of new antineoplasic and anti-inflammatory agents: the natural selectin ligand sialyl Lewis^x and its mimetic GMI-1070. Accordingly, a series of unbiased molecular dynamics simulations at the microsecond scale using GROMOS 53A6 (GLYC), CHARMM36m and GLYCAM06 force fields were employed, together with ConfID, an analytical method for the characterization of conformational populations of small molecules. Our results for sialyl Lewis^x are in agreement with and expand upon prior work. As for the mimetic, our results indicate that, in spite of its conformational restriction, GMI-1070's behavior in solution deviates from what had been proposed, highlighting thus some features that could be optimized, as the development of sialyl Lewis^x mimetics continues, and new candidates emerge.

Capillary forces exerted by a water bridge on cellulose nanocrystals: the effect of an external electric field

Capillary forces play an important role during the dewatering and drying of nanocellulosic materials. Traditional moisture removal techniques, such as heating, have been proved to be deterimental to the properties of these materials and hence, there is a need to develop novel dewatering techniques without affecting the desired properties of materials. It is, therefore, important to explore novel methods for dewatering these high-added-value materials without negatively influencing their properties. In this context, we explore the effect of electric field on the capillary forces developed by a liquid-water bridge between two cellulosic surfaces, which may be formed during the water removal process following its displacement from the interfibrillar spaces. All-atom molecular dynamics (MD) simulations have been used to study the influence of an externally applied electric field on the capillary force exerted by a water bridge. Our results suggest that the equilibrium contact angle of water and the capillary force exerted by the water bridge between two nanocellulosic surfaces depend on the magnitude and direction of the externally applied electric fields. Hence, an external electric field can be applied to manipulate the capillary forces between two particles. The close agreement between the capillary forces measured through MD simulations and those calculated through classical equations indicates that, within the range of the electric field applied in this study, Young-Laplace equations can be safely employed to predict the capillary forces between two particles. The present study provides insights into the use of electric fields for drying of nanocellulosic materials.

CADD, AI and ML in drug discovery: A comprehensive review

Computer-aided drug design (CADD) is an emerging field that has drawn a lot of interest because of its potential to expedite and lower the cost of the drug development process. Drug discovery research is expensive and time-consuming, and it frequently took 10-15 years for a drug to be commercially available. CADD has significantly impacted this area of research. Further, the combination of CADD with Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies to handle enormous amounts of biological data has reduced the time and cost associated with the drug development process. This review will discuss how CADD, AI, ML, and DL approaches help identify drug candidates and various other steps of the drug discovery process. It will also provide a detailed overview of the different in silico tools used and how these approaches interact.

Impact of Polarization on the Ring Puckering Dynamics of Hexose Monosaccharides

Analysis of crystal structures of hexose monosaccharides α-d-mannose (α-MAN), β-d-mannose (β-MAN), α-d-glucose (α-GLC), β-d-glucose (β-GLC), α-d-galactose (α-GAL), β-d-galactose (β-GAL), α-d-altrose (α-ALT), β-d-altrose (β-ALT), α-d-idose (α-IDO), and β-d-idose (β-IDO) reveals that the monosaccharide ring adopts multiple ring conformations. These ring conformations can be broadly classified as chair, half-chair, envelope, boat, and skew-boat conformations. The ability of the monosaccharide ring to adopt multiple conformations has been closely tied with their bioactivity. However, it has been difficult to capture the dynamic information of these conformations from experimental studies. Even from simulations, capturing these different conformations is challenging because of the energy barriers involved in the transitions between the stable ⁴C₁ and ¹C₄ chair forms. In this study, we analyze the influence of the polarizable force field on the ring dynamics of five major types of unsubstituted aldohexoses─glucose, mannose, galactose, altrose, and idose─and their anomers. We simulate microsecond trajectories to capture the influence of the CHARMM36 additive and polarizable carbohydrate force fields on the ring dynamics. The microsecond trajectories allow us to comment on the issues associated with equilibrium molecular dynamics simulations. Further, we use the extended system adaptive biasing force (eABF) method to compare the conformational sampling efficiencies of the additive and polarizable force fields. Our studies reveal that inclusion of polarization enhances the sampling of ring conformations and lowers the energy barriers between the ⁴C₁ and ¹C₄ conformations. Overall, the CHARMM36 additive force field is observed to be rigid and favor the ⁴C₁ conformations. Although the inclusion of polarizability results in enhancing ring flexibility, we observe sampling that does not agree with experimental results, warranting a revision of the polarizable Drude parameters.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

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

Atomic-Resolution Experimental Structural Biology and Molecular Dynamics Simulations of Hyaluronan and Its Complexes

This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of atomic-resolution explicit-solvent molecular dynamics simulations on these and other hyaluronan and hyaluronan-containing systems. Advances in accurate molecular mechanics force fields, simulation methods and software, and computer hardware have supported a recent flourish in such simulations, such that the simulation publications now outnumber the structural biology publications by an order of magnitude. In addition to supplementing the experimental structural biology with computed dynamic and thermodynamic information, the molecular dynamics studies provide a wealth of atomic-resolution information on hyaluronan-containing systems for which there is no atomic-resolution structural biology either available or possible. Examples of these summarized in this review include hyaluronan pairing with other hyaluronan molecules and glycosaminoglycans, with ions, with proteins and peptides, with lipids, and with drugs and drug-like molecules. Despite limitations imposed by present-day computing resources on system size and simulation timescale, atomic-resolution explicit-solvent molecular dynamics simulations have been able to contribute significant insight into hyaluronan's flexibility and capacity for intra- and intermolecular non-covalent interactions.

Extension of the CHARMM Classical Drude Polarizable Force Field to N- and O-Linked Glycopeptides and Glycoproteins

Molecular dynamic simulations are an effective tool to study complex molecular systems and are contingent upon the availability of an accurate and reliable molecular mechanics force field. The Drude polarizable force field, which allows for the explicit treatment of electronic polarization in a computationally efficient fashion, has been shown to reproduce experimental properties that were difficult or impossible to reproduce with the CHARMM additive force field, including peptide folding cooperativity, RNA hairpin structures, and DNA base flipping. Glycoproteins are essential components of glycoconjugate vaccines, antibodies, and many pharmaceutically important molecules, and an accurate polarizable force field that includes compatibility between the protein and carbohydrate aspect of the force field is essential to study these types of systems. In this work, we present an extension of the Drude polarizable force field to glycoproteins, including both N- and O-linked species. Parameter optimization focused on the dihedral terms using a reweighting protocol targeting NMR solution J-coupling data for model glycopeptides. Validation of the model include eight model glycopeptides and four glycoproteins with multiple N- and O-linked glycosylations. The new glycoprotein carbohydrate force field can be used in conjunction with the remainder of Drude polarizable force field through a variety of MD simulation programs including GROMACS, OPENMM, NAMD, and CHARMM and may be accessed through the Drude Prepper module in the CHARMM-GUI.

Multifaceted Computational Modeling in Glycoscience

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

Molecular simulations of complex carbohydrates and glycoconjugates

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

Novel Hydrazone Derivatives of 3-Bromopyruvate: Synthesis, Evaluation of the Cytotoxic Effects, Molecular Docking and ADME Studies

A series of 3-bromopyruvate (3-BP) derivatives were synthesized to develop new potent anticancer agents. The chemical structures of the compounds were characterized using FT-IR, ¹ H-, ¹³ C-NMR spectroscopy, and elemental analysis (CHN). Their cytotoxic activities were investigated against four cancer cell lines, including colon (SW1116), breast (MDA-MB-231), lung (A549), and liver (HepG2) cancer cell lines. Among the synthesized compounds, 3b showed promising cytotoxic activity compared to 3-BP, with IC₅₀ values of 16.3 μM, 19.1 μM, 27.8 μM, and 14.5 μM against A549, MDA-MB-231, SW1116 and, HepG2 cell lines, respectively. Furthermore, the effect of these compounds on MCF-10A (a normal breast cell lines) was investigated to determine their selectivity between tumorigenic and non-tumorigenic cells. Since the 3-BP inhibits hexokinase II (HK II), molecular docking of 3-BP derivatives was carried out using AutoDock 4.2. The binding energies of these derivatives were greater than 3-BP, indicating that they had a higher affinity for HK II. For validation of docking, a 40 ns MD simulation was performed. SwissADME was used to predict pharmacokinetics, drug-likeness, and ADME parameters of the screened compounds. The results demonstrated that these derivatives are suitable candidates for developing orally potent HK II inhibitors.

Heparin-Assisted Amyloidogenesis Uncovered through Molecular Dynamics Simulations

Glycosaminoglycans (GAGs), in particular, heparan sulfate and heparin, are found colocalized with Aβ amyloid. They have been shown to enhance fibril formation, suggesting a possible pathological connection. We have investigated heparin's assembly of the KLVFFA peptide fragment using molecular dynamics simulation, to gain a molecular-level mechanistic understanding of how GAGs enhance fibril formation. The simulations reveal an exquisite process wherein heparin accelerates peptide assembly by first "gathering" the peptide molecules and then assembling them. Heparin does not act as a mere template but is tightly coupled to the peptides, yielding a composite protofilament structure. The strong intermolecular interactions suggest composite formation to be a general feature of heparin's interaction with peptides. Heparin's chain flexibility is found to be essential to its fibril promotion activity, and the need for optimal heparin chain length and concentration has been rationalized. These insights yield design rules (flexibility; chain-length) and protocol guidance (heparin:peptide molar ratio) for developing effective heparin mimetics and other functional GAGs.

Nek1-inhibitor and temozolomide-loaded microfibers as a co-therapy strategy for glioblastoma treatment

Malignant glioblastoma (GB) is the predominant primary brain tumour in adults, but despite the efforts towards novel therapies, the median survival of GB patients has not significantly improved in the last decades. Therefore, localised approaches that treat GB straight into the tumour site provide an alternative to enhance chemotherapy bioavailability and efficacy, reducing systemic toxicity. Likewise, the discovery of protein targets, such as the NIMA-related kinase 1 (Nek1), which was previously shown to be associated with temozolomide (TMZ) resistance in GB, has stimulated the clinical development of target therapy approaches to treat GB patients. In this study, we report an electrospun polyvinyl alcohol (PVA) microfiber (MF) brain-implant prepared for the controlled release of Nek1 protein inhibitor (iNek1) and TMZ or TMZ-loaded nanoparticles. The formulations revealed adequate stability and drug loading, which prolonged the drugs' release allowing a sustained exposure of the GB cells to the treatment and enhancing the drugs' therapeutic effects. TMZ-loaded MF provided the highest concentration of TMZ within the brain of tumour-bearing rats, and it was statistically significant when compared to TMZ via intraperitoneal (IP). All animals treated with either co-therapy formulation (TMZ + iNek1 MF or TMZ nanoparticles + iNek1 MF) survived until the endpoint (60 days), whereas the Blank MF (drug-unloaded), TMZ MF and TMZ IP-treated rats' median survival was found to be 16, 31 and 25 days, respectively. The tumour/brain area ratio of the rats implanted with either MF co-therapy was found to be reduced by 5-fold when compared to Blank MF-implanted rats. Taken together, our results strongly suggest that Nek1 is an important GB oncotarget and the inhibition of Nek1's activity significantly decreases GB cells' viability and tumour size when combined with TMZ treatment.

Structural Characteristics of Glycocins: Unraveling the Role of S-Linked Carbohydrates and Other Structural Elements

Glycocins are antimicrobial peptides with glycosylations, often an S-linked monosaccharide. Their recent structure elucidation has brought forth questions about their mechanisms of action as well as the impact of S-glycosylation on their structural behavior. Here, we investigated structural characteristics of glycocins using a computational approach. Depending on the peptide's class (sublancin- or glycocin F-like), the sugar changes the peptide's flexibility. Also, the presence of glycosylation is necessary for the lack of structure of Asm1. The C-terminal tail in glycocin F-like peptides influenced their structured regions, acting like a regulator. These findings corroborate the versatility of these post-translational modifications, pointing toward their potential use in molecular engineering.

Carbohydrate Force Fields: The Role of Small Partial Atomic Charges in Preventing Conformational Collapse

Although the quality of current additive all-atom force fields for carbohydrates has been demonstrated in many applications, occasional significant differences reported for the hydrodynamic behavior of specific polysaccharides modeled with different force fields is a cause for concern. In particular, irreversible conformational collapse has been noted for some polysaccharide simulations with the GLYCAM06j force field. Here, we investigate the cause of this phenomenon through comparative simulations of a range of saccharides with both the GLYCAM06j and the CHARMM36 carbohydrate force fields. We find that conformational collapse in GLYCAM06j occurs for saccharide chains containing the deoxy sugar α-l-rhamnose after relatively long simulation intervals. Further, we explore the mechanism of conformational collapse and show that this phenomenon arises because of the anomalous low energy in GLYCAM06j (as compared to quantum mechanical calculations) of a specific orientation of α-l-Rha to α-l-Rha glycosidic linkages, which are subsequently sustained by intramolecular interactions in the saccharide chain. We identify the lack of partial charges on aliphatic hydrogens in GLYCAM as the source of this anomaly, demonstrating that addition of small partial atomic charges on the aliphatic protons in rhamnose removes the conformational collapse phenomenon. This work reveals the large cumulative impact that small partial charges may have on the dynamic behavior of polysaccharides and indicates that future reparameterization of the GLYCAM06j force field should investigate the addition of partial charges on all aliphatic hydrogens.

Aqueous Molecular Dynamics for Understanding Glycosaminoglycan Recognition by Proteins

Glycosaminoglycans (GAGs) are biopolymers that exist in most organisms. GAGs are known to bind to hundreds of proteins and partake in multiple biological processes such as growth, morphogenesis, inflammation, infection, and others. Their intrinsic structural heterogeneity and conformational variability introduce major challenges in experimental studies. On the other hand, recent advances in force field development and computational technology have yielded phenomenal opportunity to study thousands of GAG sequences simultaneously to understand recognition of target protein(s). Here, we describe experimental setup for conventional molecular dynamics simulations of GAGs to position an experimental biologist favorably in performance, analysis and interpretation of stability, specificity, and conformational properties of GAGs, while also elucidating their interactions with amino acid residues of a protein at an atomistic level in presence of water.

Pyranose Ring Puckering Thermodynamics for Glycan Monosaccharides Associated with Vertebrate Proteins

The conformational properties of carbohydrates can contribute to protein structure directly through covalent conjugation in the cases of glycoproteins and proteoglycans and indirectly in the case of transmembrane proteins embedded in glycolipid-containing bilayers. However, there continue to be significant challenges associated with experimental structural biology of such carbohydrate-containing systems. All-atom explicit-solvent molecular dynamics simulations provide a direct atomic resolution view of biomolecular dynamics and thermodynamics, but the accuracy of the results depends on the quality of the force field parametrization used in the simulations. A key determinant of the conformational properties of carbohydrates is ring puckering. Here, we applied extended system adaptive biasing force (eABF) all-atom explicit-solvent molecular dynamics simulations to characterize the ring puckering thermodynamics of the ten common pyranose monosaccharides found in vertebrate biology (as represented by the CHARMM carbohydrate force field). The results, along with those for idose, demonstrate that the CHARMM force field reliably models ring puckering across this diverse set of molecules, including accurately capturing the subtle balance between 4C1 and 1C4 chair conformations in the cases of iduronate and of idose. This suggests the broad applicability of the force field for accurate modeling of carbohydrate-containing vertebrate biomolecules such as glycoproteins, proteoglycans, and glycolipids.

Structure-guided glyco-engineering of ACE2 for improved potency as soluble SARS-CoV-2 decoy receptor

Infection and viral entry of SARS-CoV-2 crucially depends on the binding of its Spike protein to angiotensin converting enzyme 2 (ACE2) presented on host cells. Glycosylation of both proteins is critical for this interaction. Recombinant soluble human ACE2 can neutralize SARS-CoV-2 and is currently undergoing clinical tests for the treatment of COVID-19. We used 3D structural models and molecular dynamics simulations to define the ACE2 N-glycans that critically influence Spike-ACE2 complex formation. Engineering of ACE2 N-glycosylation by site-directed mutagenesis or glycosidase treatment resulted in enhanced binding affinities and improved virus neutralization without notable deleterious effects on the structural stability and catalytic activity of the protein. Importantly, simultaneous removal of all accessible N-glycans from recombinant soluble human ACE2 yields a superior SARS-CoV-2 decoy receptor with promise as effective treatment for COVID-19 patients.

Challenges and limitations in the studies of glycoproteins: A computational chemist's perspective

Experimenters face challenges and limitations while analyzing glycoproteins due to their high flexibility, stereochemistry, anisotropic effects, and hydration phenomena. Computational studies complement experiments and have been used in characterization of the structural properties of glycoproteins. However, recent investigations revealed that computational studies face significant challenges as well. Here, we introduce and discuss some of these challenges and weaknesses in the investigations of glycoproteins. We also present requirements of future developments in computational biochemistry and computational biology areas that could be necessary for providing more accurate structural property analyses of glycoproteins using computational tools. Further theoretical strategies that need to be and can be developed are discussed herein.

Fusion pores with low conductance are cation selective

Many neurotransmitters are organic ions that carry a net charge, and their release from secretory vesicles is therefore an electrodiffusion process. The selectivity of early exocytotic fusion pores is investigated by combining electrodiffusion theory, measurements of amperometric foot signals from chromaffin cells with anion substitution, and molecular dynamics simulation. The results reveal that very narrow fusion pores are cation selective, but more dilated fusion pores become anion permeable. The transition occurs around a fusion pore conductance of ~300 pS. The cation selectivity of a narrow fusion pore accelerates the release of positively charged transmitters such as dopamine, noradrenaline, adrenaline, serotonin, and acetylcholine, while glutamate release may require a more dilated fusion pore.

For transmission, a fusion pore forms when vesicle and target membranes are brought together by SNARE proteins. Delacruz et al. demonstrate that selectivity of the pore accelerates release of positively charged transmitters such as dopamine, noradrenaline, adrenaline, serotonin, and acetylcholine, while glutamate release may require a more dilated fusion pore.

Illustration of a computational pipeline for evaluating cyclodextrin host-guest complex formation through conformational capture of bullvalene

Cyclodextrins have a diverse range of applications, including as supramolecular hosts, as enzyme active-site analogs, in improving drug solubility and delivery, and in molecular selection. We have investigated their ability to form stable complexes with bullvalenes, unusual organic cage molecules that spontaneously interconvert between numerous degenerate isomers. The shape-shifting nature of substituted bullvalenes raises the potential for dynamic adaptive binding to biological targets. We tested whether β- and γ-cyclodextrins can capture particular bullvalene isomers and whether the preferred binding mode(s) differ between isomers. We first applied our computational host-guest interaction potential energy profiling to determine the best binding mode(s) of unsubstituted bullvalene and each isomer of methylenehydroxybullvalene to β- and γ-cyclodextrin. Subsequent molecular dynamics simulations of the predicted host-guest complexes showed that while unsubstituted bullvalene has a single, albeit ill-defined, binding mode with either cyclodextrin, each isomer of methylenehydroxybullvalene has two possible modes of binding to β-cyclodextrin but only a single, nebulous mode of binding to γ-cyclodextrin. Experimental determination of the binding free energy of each methylenehydroxybullvalene-cyclodextrin complex showed that methylenehydroxybullvalene is more likely to bind to β-cyclodextrin than to γ-cyclodextrin, despite its smaller cavity. Together, our results suggest that β-cyclodextrin, but not γ-cyclodextrin, shows promise for conformational capture of mono-substituted bullvalenes. More broadly, our computational pipeline should prove useful for rapid characterization of cyclodextrin host-guest complexes, avoiding the need for costly synthesis of guest molecules that are unlikely to bind stably, as well as providing detailed atomic-level insight into the nature of complexation.

A Bittersweet Computational Journey among Glycosaminoglycans

Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the “bitter” and “sweet” aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.

Thermodynamic and structural aspects of molecular recognition in mannose-binding protein complexes: a theoretical study over HRP-ArtinM association

The biomolecular recognition of D-mannose-binding lectin from Artocarpus heterophyllus (ArtinM) by Horseradish Peroxidase (HRP) mediated by glycosylation allows their application in a multitude of biological systems. The present work describes the use of molecular dynamics (MD) to assess the Gibbs free energy associated with the formation of a ArtinM-HRP conjugate mediated by a glycosylation molecule. For the enthalpy term, we applied the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method and for the vibrational entropy term, we use the quasi-harmonic approximation. Our results show that, even without glycosylation, the binding free energy between ArtinM and HRP is - 196.154 kJmol^- 1, an extremely high affinity with low selectivity, originated mainly through the van der Waals energy terms. The binding free energy between ArtinM and the glycosylated HRP (gHRP) was calculated at - 66.156 kJmol^- 1, an absolute and considerably lower value, however, originated from electrostatic energy terms, which increases the selectivity of molecular recognition. Our work has shown that the HRP active site region has a high affinity and low selectivity for other biomolecules. The presence of glycosylation plays a role in increasing this selectivity for this region. Thus, we conclude that performing mutagenesis of amino acid residues near the entrance of the catalytic site, can improve the activity of non-glycosylated HRPs. This illustrates new insights that can be applied to carbohydrate-based immunochemistry.

Wettability of cellulose surfaces under the influence of an external electric field

HYPOTHESIS

Interfacial tensions play an important role in dewatering of hydrophilic materials like nanofibrillated cellulose, and are affected by the molecular organization of water at the interface. Application of an electric field influences the orientation of water molecules along the field direction. Hence, it should be possible to alter the interfacial free energies to tune the wettability of cellulose surface through application of an external electric field thus, aiding the dewatering process.

SIMULATIONS

Molecular dynamics simulations of cellulose surface in contact with water under the influence of an external electric field have been conducted with GLYCAM-06 forcefield. The effect of variation in electric field intensity and directions on the spreading coefficient has been addressed via orientational preference of water molecules and interfacial free energy analyses.

FINDINGS

The application of electric field influences the interfacial free energy difference at the cellulose-water interface. The spreading coefficient increases with the electric field directed parallel to the cellulose-water interface while it decreases in the perpendicular electric field. Variation in interfacial free energies seems to explain the change in contact angle adequately in presence of an electric field. The wettability of cellulose surface can be tuned by the application of an external electric field.

Rotational Profiler: A Fast, Automated, and Interactive Server to Derive Torsional Dihedral Potentials for Classical Molecular Simulations

Rotational Profiler provides an analytical algorithm to compute sets of classical torsional dihedral parameters by fitting an empirical energy profile to a reference one that can be obtained experimentally or by quantum-mechanical methods. The resulting profiles are compatible with the functional forms in the most widely used biomolecular force fields (e.g., GROMOS, AMBER, OPLS, and CHARMM). The linear least-squares regression method is used to generate sets of parameters that best satisfy the fitting. Rotational Profiler is free to use, analytical, and force field/package independent. The formalism is herein described, and its usage, in an interactive and automated manner, is made available as a Web server at http://rotprof.lncc.br.

Out of Sight, Out of Mind: The Effect of the Equilibration Protocol on the Structural Ensembles of Charged Glycolipid Bilayers

Molecular dynamics (MD) simulations represent an essential tool in the toolbox of modern chemistry, enabling the prediction of experimental observables for a variety of chemical systems and processes and majorly impacting the study of biological membranes. However, the chemical diversity of complex lipids beyond phospholipids brings new challenges to well-established protocols used in MD simulations of soft matter and requires continuous assessment to ensure simulation reproducibility and minimize unphysical behavior. Lipopolysaccharides (LPS) are highly charged glycolipids whose aggregation in a lamellar arrangement requires the binding of numerous cations to oppositely charged groups deep inside the membrane. The delicate balance between the fully hydrated carbohydrate region and the smaller hydrophobic core makes LPS membranes very sensitive to the choice of equilibration protocol. In this work, we show that the protocol successfully used to equilibrate phospholipid bilayers when applied to complex lipopolysaccharide membranes occasionally leads to a small expansion of the simulation box very early in the equilibration phase. Although the use of a barostat algorithm controls the system dimension and particle distances according to the target pressure, fluctuation in the fleeting pressure occasionally enables a few water molecules to trickle into the hydrophobic region of the membrane, with spurious solvent buildup. We show that this effect stems from the initial steps of NPT equilibration, where initial pressure can be fairly high. This can be solved with the use of a stepwise-thermalization NVT/NPT protocol, as demonstrated for atomistic MD simulations of LPS/DPPE and lipid-A membranes in the presence of different salts using an extension of the GROMOS forcefield within the GROMACS software. This equilibration protocol should be standard procedure for the generation of consistent structural ensembles of charged glycolipids starting from atomic coordinates not previously pre-equilibrated. Although different ways to deal with this issue can be envisioned, we investigated one alternative that could be readily available in major MD engines with general users in mind.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

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

Molecular dynamic simulation: Conformational properties of single-stranded curdlan in aqueous solution

Recently, molecular dynamic simulation technique has been proved to be a powerful tool providing structural insights for better understanding the functionality of carbohydrates. Here, by using molecular dynamic simulation method we investigated the detailed conformational properties of the single-stranded curdlan with 12 glucose units. The results showed that the right-handed 6/1 helix structure was thermodynamically the most stable conformation in solution. The formation of the helix conformation was determined by many factors such as the glycosidic linkage, explicit water solvation and hydrogen bonds. When temperature was increased, the representative helix conformation was found becoming unstable giving rise to metastable conformations because when water mobility was accelerated with temperature, the hydrogen bonding strength between the curdlan chain and water went down, breaking the continuity of the hydrogen bonding network of water and hydroxyl groups. When the number of repeating glucose units varied from 6 to 24, the major helix conformation remained, but the conformational properties of longer chains were more apparently aff ;ected by chain flexibility.

Extending the Martini Coarse-Grained Force Field to N-Glycans

Glycans play a vital role in a large number of cellular processes. Their complex and flexible nature hampers structure-function studies using experimental techniques. Molecular dynamics (MD) simulations can help in understanding dynamic aspects of glycans if the force field parameters used can reproduce key experimentally observed properties. Here, we present optimized coarse-grained (CG) Martini force field parameters for N-glycans, calibrated against experimentally derived binding affinities for lectins. The CG bonded parameters were obtained from atomistic (ATM) simulations for different glycan topologies including high mannose and complex glycans with various branching patterns. In the CG model, additional elastic networks are shown to improve maintenance of the overall conformational distribution. Solvation free energies and octanol-water partition coefficients were also calculated for various N-glycan disaccharide combinations. When using standard Martini nonbonded parameters, we observed that glycans spontaneously aggregated in the solution and required down-scaling of their interactions for reproduction of ATM model radial distribution functions. We also optimized the nonbonded interactions for glycans interacting with seven lectin candidates and show that a relatively modest scaling down of the glycan-protein interactions can reproduce free energies obtained from experimental studies. These parameters should be of use in studying the role of glycans in various glycoproteins and carbohydrate binding proteins as well as their complexes, while benefiting from the efficiency of CG sampling.

Rigorous analysis of free solution glycosaminoglycan dynamics using simple, new tools

Heparin/heparan sulfates (H/HS) are ubiquitous biopolymers that interact with many proteins to induce a range of biological functions. Unfortunately, how these biopolymers recognize their preferred protein targets remain poorly understood. It is suggested that computational simulations offer attractive avenues but a number of challenges, e.g., difficulty of selecting a comprehensive force field, few simple tools to interpret data, among others, remain. This work addresses several such challenges so as to help ease the implementation and analysis of computational experiments. First, this work presents a rigorous comparison of two different recent force fields, CHARMM36 and GLYCAM06, for H/HS studies. Second, it introduces two new straightforward parameters, i.e., end-to-end distance and minimum volume enclosing ellipsoid, to understand the myriad conformational forms of oligosaccharides that evolve over time in water. Third, it presents an application to elucidate the number and nature of inter and intramolecular, nondirect bridging water molecules, which help stabilize unique forms of H/HS. The results show that nonspecialists can use either CHARMM36 or GLYCAM06 force fields because both gave comparable results, albeit with small differences. The comparative study shows that the HS hexasaccharide samples a range of conformations with nearly equivalent energies, which could be the reason for its recognition by different proteins. Finally, analysis of the nondirect water bridges across the dynamics trajectory shows their importance in stabilization of certain conformational forms, which may become important for protein recognition. Overall, the work aids nonspecialists employ computational studies for understanding the solution behavior of H/HS.

Balanced polarizable Drude force field parameters for molecular anions: phosphates, sulfates, sulfamates, and oxides

Polarizable force fields are emerging as a more accurate alternative to additive force fields in terms of modeling and simulations of a variety of chemicals including biomolecules. Explicit treatment of induced polarization in charged species such as phosphates and sulfates offers the potential for achieving an improved atomistic understanding of the physical forces driving their interactions with their environments. To help achieve this, in this study we present balanced Drude polarizable force field parameters for molecular ions including phosphates, sulfates, sulfamates, and oxides. Better balance was primarily achieved in the relative values of minimum interaction energies and distances of the anionic model compounds with water at the Drude and quantum mechanical (QM) model chemistries. Parametrization involved reoptimizing available parameters as well as extending the force field to new molecules with the goal of achieving self-consistency with respect to the Lennard-Jones and electrostatic parameters targeting QM and experimental hydration free energies. The resulting force field parameters achieve consistent treatment across the studied anions, facilitating more balanced simulations of biomolecules and small organic molecules in the context of the classical Drude polarizable force field. Graphical abstract.

NWChem: Past, present, and future

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

Aggregation of Lipid A Variants: A Hybrid Particle-Field Model

Lipid A is one of the three components of bacterial lipopolysaccharides constituting the outer membrane of Gram-negative bacteria, and is recognized to have an important biological role in the inflammatory response of mammalians. Its biological activity is modulated by the number of acyl-chains that are present in the lipid and by the dielectric medium, i.e., the type of counter-ions, through electrostatic interactions. In this paper, we report on a coarse-grained model of chemical variants of Lipid A based on the hybrid particle-field/molecular dynamics approach (hPF-MD). In particular, we investigate the stability of Lipid A bilayers for two different hexa- and tetra-acylated structures. Comparing particle density profiles along bilayer cross-sections, we find good agreement between the hPF-MD model and reference all-atom simulation for both chemical variants of Lipid A. hPF-MD models of constituted bilayers composed by hexa-acylated Lipid A in water are stable within the simulation time. We further validate our model by verifying that the phase behavior of Lipid A/counterion/water mixtures is correctly reproduced. In particular, hPF-MD simulations predict the correct self-assembly of different lamellar and micellar phases from an initially random distribution of Lipid A molecules with counterions in water. Finally, it is possible to observe the spontaneous formation and stability of Lipid A vesicles by fusion of micellar aggregates.

The Lazy Life of Lipid-Linked Oligosaccharides in All Life Domains

Lipid-linked oligosaccharides (LLOs) play an important role in the N-glycosylation pathway as the donor substrate of oligosaccharyltransferases (OSTs), which are responsible for the en bloc transfer of glycan chains onto a nascent polypeptide. The lipid component of LLO in both eukarya and archaea consists of a dolichol, and an undecaprenol in prokarya, whereas the number of isoprene units may change between species. Given the potential relevance of LLOs and their related enzymes to diverse biotechnological applications, obtaining reliable LLO models from distinct domains of life could support further studies on complex formation and their processing by OSTs, as well as protein engineering on such systems. In this work, molecular modeling techniques, such as quantum mechanics calculations, molecular dynamics simulations, and metadynamics were employed to study eukaryotic (Glc₃-Man₉-GlcNAc₂-PP-Dolichol), bacterial (Glc₁-GalNAc₅-Bac₁-PP-Undecaprenol), and archaeal (Glc₁-Man1-Gal₁-Man1-Glc₁-Gal₁-Glc₁-P-Dolichol) LLOs in membrane bilayers. Microsecond molecular dynamics simulations and metadynamics calculations of LLOs revealed that glycan chains are more prone to interact with the membrane lipid head groups, while the PP linkages are positioned at the lipid phosphate head groups level. The dynamics of isoprenoid chains embedded within the bilayer are described, and membrane dynamics and related properties are also investigated. Overall, there are similarities regarding the structure and dynamics of the eukaryotic, the bacterial, and the archaeal LLOs in bilayers, which can support the comprehension of their association with OSTs. These data may support future studies on the transferring mechanism of the oligosaccharide chain to an acceptor protein.

Current Status of Carbohydrates Information in the Protein Data Bank

Carbohydrates are well known for their physicochemical, biological, functional, and therapeutic characteristics. Unfortunately, their chemical nature imposes severe challenges for the structural elucidation of these phenomena, impairing not only the depth of our understanding of carbohydrates but also the development of new biotechnological and therapeutic applications based on these molecules. In the recent past, the amount of structural information, obtained mainly from X-ray crystallography, has increased progressively, as well as its quality. In this context, the current work presents a global analysis of the carbohydrate information available in the Protein Data Bank (PDB). From high quality structures, it is clear that most of the data are highly concentrated on a few sets of residue types, on their monosaccharidic forms, and connected by a small diversity of glycosidic linkages. The geometries of these linkages can be mostly associated with the types of linkages instead of residues, while the level of puckering distortion was characterized, quantified, and located in a pseudorotational equilibrium landscape, not only to local minima but also to transitional states. These qualitative and quantitative analyses offer a global picture of the carbohydrate structural content in the PDB, potentially supporting the building of new models for carbohydrate-related biological phenomena at the atomistic level, including new developments on force field parameters.

An NMR and MD study of complexes of bacteriophage lambda lysozyme with tetra- and hexa-N-acetylchitohexaose

The X-ray structure of lysozyme from bacteriophage lambda (λ lysozyme) in complex with the inhibitor hexa-N-acetylchitohexaose (NAG6) (PDB: 3D3D) has been reported previously showing sugar units from two molecules of NAG6 bound in the active site. One NAG6 is bound with four sugar units in the ABCD sites and the other with two sugar units in the E'F' sites potentially representing the cleavage reaction products; each NAG6 cross links two neighboring λ lysozyme molecules. Here we use NMR and MD simulations to study the interaction of λ lysozyme with the inhibitors NAG4 and NAG6 in solution. This allows us to study the interactions within the complex prior to cleavage of the polysaccharide. 1 HN and 15 N chemical shifts of λ lysozyme resonances were followed during NAG4/NAG6 titrations. The chemical shift changes were similar in the two titrations, consistent with sugars binding to the cleft between the upper and lower domains; the NMR data show no evidence for simultaneous binding of a NAG6 to two λ lysozyme molecules. Six 150 ns MD simulations of λ lysozyme in complex with NAG4 or NAG6 were performed starting from different conformations. The simulations with both NAG4 and NAG6 show stable binding of sugars across the D/E active site providing low energy models for the enzyme-inhibitor complexes. The MD simulations identify different binding subsites for the 5th and 6th sugars consistent with the NMR data. The structural information gained from the NMR experiments and MD simulations have been used to model the enzyme-peptidoglycan complex.