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.

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.

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.

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.

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.

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.

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.

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.

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.

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.