Oligosaccharide model of the vascular endothelial glycocalyx in physiological flow.

Experiments have consistently revealed the pivotal role of the endothelial glycocalyx layer in vasoregulation and the layer's contribution to mechanotransduction pathways. However, the exact mechanism by which the glycocalyx mediates fluid shear stress remains elusive. This study employs atomic-scale molecular simulations with the aim of investigating the conformational and orientation properties of highly flexible oligosaccharide components of the glycocalyx and their suitability as transduction molecules under hydrodynamic loading. Fluid flow was shown to have nearly no effect on the conformation populations explored by the oligosaccharide, in comparison with static (diffusion) conditions. However, the glycan exhibited a significant orientation change, when compared to simple diffusion, aligning itself with the flow direction. It is the tethered end of the glycan, an asparagine amino acid, which experienced conformational changes as a result of this flow-induced bias. Our results suggest that shear flow through the layer can have an impact on the conformational properties of saccharide-decorated transmembrane proteins, thus acting as a mechanosensor.

Combining 3D structure with glycan array data provides insight into the origin of glycan specificity.

Defining how a glycan-binding protein (GBP) specifically selects its cognate glycan from among the ensemble of glycans within the cellular glycome is an area of intense study. Powerful insight into recognition mechanisms can be gained from 3D structures of GBPs complexed to glycans; however, such structures remain difficult to obtain experimentally. Here an automated 3D structure generation technique, called computational carbohydrate grafting, is combined with the wealth of specificity information available from glycan array screening. Integration of the array data with modeling and crystallography allows generation of putative co-complex structures that can be objectively assessed and iteratively altered until a high level of agreement with experiment is achieved. Given an accurate model of the co-complexes, grafting is also able to discern which binding determinants are active when multiple potential determinants are present within a glycan. In some cases, induced fit in the protein or glycan was necessary to explain the observed specificity, while in other examples a revised definition of the minimal binding determinants was required. When applied to a collection of 10 GBP-glycan complexes, for which crystallographic and array data have been reported, grafting provided a structural rationalization for the binding specificity of >90% of 1223 arrayed glycans. A webtool that enables researchers to perform computational carbohydrate grafting is available at www.glycam.org/gr (accessed 03 March 2016).

Extension and validation of the GLYCAM force field parameters for modeling glycosaminoglycans.

Glycosaminoglycans (GAGs) are an important class of carbohydrates that serve critical roles in blood clotting, tissue repair, cell migration and adhesion, and lubrication. The variable sulfation pattern and iduronate ring conformations in GAGs influence their polymeric structure and nature of interaction. This study characterizes several heparin-like GAG disaccharides and tetrasaccharides using NMR and molecular dynamics simulations to assist in the development of parameters for GAGs within the GLYCAM06 force field. The force field additions include parameters and charges for a transferable sulfate group for O- and N-sulfation, neutral (COOH) forms of iduronic and glucuronic acid, and Δ4,5-unsaturated uronate (ΔUA) residues. ΔUA residues frequently arise from the enzymatic digestion of heparin and heparin sulfate. Simulations of disaccharides containing ΔUA reveal that the presence of sulfation on this residue alters the relative populations of 1H2 and 2H1 ring conformations. Simulations of heparin tetrasaccharides containing N-sulfation in place of N-acetylation on glucosamine residues influence the ring conformations of adjacent iduronate residues.

Les glycosaminoglycanes (GAG) sont une classe importante d'hydrates de carbone qui jouent un rôle crucial dans la coagulation sanguine, la réparation des tissus, la migration et l'adhérence cellulaires, et la lubrification. La disposition variable des groupes sulfate et la conformation du cycle de l'iduronate des GAG influent sur leur structure polymérique et sur la nature des interactions. Dans la présente étude, nous caractérisons divers GAG disaccharidiques et tétrasaccharidiques semblables à l'héparine par RMN et modélisation de dynamique moléculaire en vue de contribuer à la détermination de paramètres pour les GAG dans le champ de force GLYCAM06. Les éléments additionnels au champ de force comprennent les paramètres et les charges associés à un groupe sulfate transférable lors de la O-sulfatation et de la N-sulfatation, les formes neutres (COOH) des acides iduronique et glucuronique et les résidus uronate Δ4,5-insaturés (ΔUA). Des résidus ΔUA sont souvent formés lors de la digestion enzymatique de l'héparine et du sulfate d'héparine. Des modélisations de disaccharides contenant des ΔUA révèlent que la présence de groupes sulfate sur ces résidus modifie les populations relatives des conformations de cycle 1H2 et 2H1. Les modelisations de tétrasaccharides à base d'héparine présentant une N-sulfatation au lieu d'une N-acétylation des résidus glucosamine influent sur les conformations de cycle des résidus iduronate adjacents. [Traduit par la Rédaction].

Calculating binding free energies for protein-carbohydrate complexes.

A variety of computational techniques may be applied to compute theoretical binding free energies for protein-carbohydrate complexes. Elucidation of the intermolecular interactions, as well as the thermodynamic effects, that contribute to the relative strength of receptor binding can shed light on biomolecular recognition, and the resulting initiation or inhibition of a biological process. Three types of free energy methods are discussed here, including MM-PB/GBSA, thermodynamic integration, and a non-equilibrium alternative utilizing SMD. Throughout this chapter, the well-known concanavalin A lectin is employed as a model system to demonstrate the application of these methods to the special case of carbohydrate binding.

Importance of ligand conformational energies in carbohydrate docking: Sorting the wheat from the chaff.

Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand-specific conformational energies. Here, we develop a set of Carbohydrate Intrinsic (CHI) energy functions that quantify the conformational properties of oligosaccharides, based on the values of their glycosidic torsion angles. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide-protein complexes in the protein data bank. Addition of CHI energies to the standard docking scores in Autodock 3, 4.2, and Vina consistently improves pose ranking of oligosaccharides docked to a set of anticarbohydrate antibodies. The CHI energy functions are also independent of docking algorithm, and with minor modifications, may be incorporated into both theoretical modeling methods, and experimental NMR or X-ray structure refinement programs.

Computational screening of the human TF-glycome provides a structural definition for the specificity of anti-tumor antibody JAA-F11.

Recombinant antibodies are of profound clinical significance; yet, anti-carbohydrate antibodies are prone to undesirable cross-reactivity with structurally related-glycans. Here we introduce a new technology called Computational Carbohydrate Grafting (CCG), which enables a virtual library of glycans to be assessed for protein binding specificity, and employ it to define the scope and structural origin of the binding specificity of antibody JAA-F11 for glycans containing the Thomsen-Friedenreich (TF) human tumor antigen. A virtual library of the entire human glycome (GLibrary-3D) was constructed, from which 1,182 TF-containing human glycans were identified and assessed for their ability to fit into the antibody combining site. The glycans were categorized into putative binders, or non-binders, on the basis of steric clashes with the antibody surface. The analysis employed a structure of the immune complex, generated by docking the TF-disaccharide (Galß1-3GalNAcα) into a crystal structure of the JAA-F11 antigen binding fragment, which was shown to be consistent with saturation transfer difference (STD) NMR data. The specificities predicted by CCG were fully consistent with data from experimental glycan array screening, and confirmed that the antibody is selective for the TF-antigen and certain extended core-2 type mucins. Additionally, the CCG analysis identified a limited number of related putative binding motifs, and provided a structural basis for interpreting the specificity. CCG can be utilized to facilitate clinical applications through the determination of the three-dimensional interaction of glycans with proteins, thus augmenting drug and vaccine development techniques that seek to optimize the specificity and affinity of neutralizing proteins, which target glycans associated with diseases including cancer and HIV.

Metabolism of vertebrate amino sugars with N-glycolyl groups: resistance of α2-8-linked N-glycolylneuraminic acid to enzymatic cleavage.

The sialic acid (Sia) N-acetylneuraminic acid (Neu5Ac) and its hydroxylated derivative N-glycolylneuraminic acid (Neu5Gc) differ by one oxygen atom. CMP-Neu5Gc is synthesized from CMP-Neu5Ac, with Neu5Gc representing a highly variable fraction of total Sias in various tissues and among different species. The exception may be the brain, where Neu5Ac is abundant and Neu5Gc is reported to be rare. Here, we confirm this unusual pattern and its evolutionary conservation in additional samples from various species, concluding that brain Neu5Gc expression has been maintained at extremely low levels over hundreds of millions of years of vertebrate evolution. Most explanations for this pattern do not require maintaining neural Neu5Gc at such low levels. We hypothesized that resistance of α2-8-linked Neu5Gc to vertebrate sialidases is the detrimental effect requiring the relative absence of Neu5Gc from brain. This linkage is prominent in polysialic acid (polySia), a molecule with critical roles in vertebrate neural development. We show that Neu5Gc is incorporated into neural polySia and does not cause in vitro toxicity. Synthetic polymers of Neu5Ac and Neu5Gc showed that mammalian and bacterial sialidases are much less able to hydrolyze α2-8-linked Neu5Gc at the nonreducing terminus. Notably, this difference was not seen with acid-catalyzed hydrolysis of polySias. Molecular dynamics modeling indicates that differences in the three-dimensional conformation of terminal saccharides may partly explain reduced enzymatic activity. In keeping with this, polymers of N-propionylneuraminic acid are sensitive to sialidases. Resistance of Neu5Gc-containing polySia to sialidases provides a potential explanation for the rarity of Neu5Gc in the vertebrate brain.

Carbohydrate force fields.

Carbohydrates present a special set of challenges to the generation of force fields. First, the tertiary structures of monosaccharides are complex merely by virtue of their exceptionally high number of chiral centers. In addition, their electronic characteristics lead to molecular geometries and electrostatic landscapes that can be challenging to predict and model. The monosaccharide units can also interconnect in many ways, resulting in a large number of possible oligosaccharides and polysaccharides, both linear and branched. These larger structures contain a number of rotatable bonds, meaning they potentially sample an enormous conformational space. This article briefly reviews the history of carbohydrate force fields, examining and comparing their challenges, forms, philosophies, and development strategies. Then it presents a survey of recent uses of these force fields, noting trends, strengths, deficiencies, and possible directions for future expansion.

Computational glycoscience: characterizing the spatial and temporal properties of glycans and glycan-protein complexes.

Modern computational methods offer the tools to provide insight into the structural and dynamic properties of carbohydrate-protein complexes, beyond that provided by experimental structural biology. Dynamic properties such as the fluctuation of inter-molecular hydrogen bonds, the residency times of bound water molecules, side chain motions and ligand flexibility may be readily determined computationally. When taken with respect to the unliganded states, these calculations can also provide insight into the entropic and enthalpic changes in free energy associated with glycan binding. In addition, virtual ligand screening may be employed to predict the three dimensional (3D) structures of carbohydrate-protein complexes, given 3D structures for the components. In principle, the 3D structure of the protein may itself be derived by modeling, leading to the exciting--albeit high risk--realm of virtual structure prediction. This latter approach is appealing, given the difficulties associated with generating experimental 3D structures for some classes of glycan binding proteins; however, it is also the least robust. An unexpected outcome of the development of algorithms for modeling carbohydrate-protein interactions has been the discovery of errors in reported experimental 3D structures and a heightened awareness of the need for carbohydrate-specific computational tools for assisting in the refinement and curation of carbohydrate-containing crystal structures. Here we present a summary of the basic strategies associated with employing classical force field based modeling approaches to problems in glycoscience, with a focus on identifying typical pitfalls and limitations. This is not an exhaustive review of the current literature, but hopefully will provide a guide for the glycoscientist interested in modeling carbohydrates and carbohydrate-protein complexes, as well as the computational chemist contemplating such tasks.

Extension of the GLYCAM06 Biomolecular Force Field to Lipids, Lipid Bilayers and Glycolipids.

GLYCAM06 is a generalisable biomolecular force field that is extendible to diverse molecular classes in the spirit of a small-molecule force field. Here we report parameters for lipids, lipid bilayers and glycolipids for use with GLYCAM06. Only three lipid-specific atom types have been introduced, in keeping with the general philosophy of transferable parameter development. Bond stretching, angle bending, and torsional force constants were derived by fitting to quantum mechanical data for a collection of minimal molecular fragments and related small molecules. Partial atomic charges were computed by fitting to ensemble-averaged quantum-computed molecular electrostatic potentials.In addition to reproducing quantum mechanical internal rotational energies and experimental valence geometries for an array of small molecules, condensed-phase simulations employing the new parameters are shown to reproduce the bulk physical properties of a DMPC lipid bilayer. The new parameters allow for molecular dynamics simulations of complex systems containing lipids, lipid bilayers, glycolipids, and carbohydrates, using an internally consistent force field. By combining the AMBER parameters for proteins with the GLYCAM06 parameters, it is also possible to simulate protein-lipid complexes and proteins in biologically relevant membrane-like environments.