Glycan Conformation in the Heavily Glycosylated Protein, CEACAM1

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.

Glycan Shape, Motions, and Interactions Explored by NMR Spectroscopy

Glycans in the form of oligosaccharides, polysaccharides, and glycoconjugates are ubiquitous in nature, and their structures range from linear assemblies to highly branched and decorated constructs. Solution state NMR spectroscopy facilitates elucidation of preferred conformations and shapes of the saccharides, motions, and dynamic aspects related to processes over time as well as the study of transient interactions with proteins. Identification of intermolecular networks at the atomic level of detail in recognition events by carbohydrate-binding proteins known as lectins, unraveling interactions with antibodies, and revealing substrate scope and action of glycosyl transferases employed for synthesis of oligo- and polysaccharides may efficiently be analyzed by NMR spectroscopy. By utilizing NMR active nuclei present in glycans and derivatives thereof, including isotopically enriched compounds, highly detailed information can be obtained by the experiments. Subsequent analysis may be aided by quantum chemical calculations of NMR parameters, machine learning-based methodologies and artificial intelligence. Interpretation of the results from NMR experiments can be complemented by extensive molecular dynamics simulations to obtain three-dimensional dynamic models, thereby clarifying molecular recognition processes involving the glycans.

Integrating Electron Paramagnetic Resonance Spectroscopy and Computational Modeling to Measure Protein Structure and Dynamics

Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large-amplitude conformational transition, a coarse-grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE-MD including all intermediate states.