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Glycosaminoglycan-Protein Interactions by Nuclear Magnetic Resonance (NMR) Spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy is one of the most utilized and informative analytical techniques for investigating glycosaminoglycan (GAG)-protein complexes. NMR methods that are commonly applied to GAG-protein systems include chemical shift perturbation, saturation transfer differenc...

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Detalles Bibliográficos
Autores principales: Pomin, Vitor H., Wang, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6225283/
https://www.ncbi.nlm.nih.gov/pubmed/30208595
http://dx.doi.org/10.3390/molecules23092314
Descripción
Sumario:Nuclear magnetic resonance (NMR) spectroscopy is one of the most utilized and informative analytical techniques for investigating glycosaminoglycan (GAG)-protein complexes. NMR methods that are commonly applied to GAG-protein systems include chemical shift perturbation, saturation transfer difference, and transferred nuclear Overhauser effect. Although these NMR methods have revealed valuable insight into the protein-GAG complexes, elucidating high-resolution structural and dynamic information of these often transient interactions remains challenging. In addition, preparation of structurally homogeneous and isotopically enriched GAG ligands for structural investigations continues to be laborious. As a result, understanding of the structure-activity relationship of GAGs is still primitive. To overcome these deficiencies, several innovative NMR techniques have been developed lately. Here, we review some of the commonly used techniques along with more novel methods such as waterLOGSY and experiments to examine structure and dynamic of lysine and arginine side chains to identify GAG-binding sites. We will also present the latest technology that is used to produce isotopically enriched as well as paramagnetically tagged GAG ligands. Recent results that were obtained from solid-state NMR of amyloid’s interaction with GAG are also presented together with a brief discussion on computer assisted modeling of GAG-protein complexes using sparse experimental data.