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A 43 Ca nuclear magnetic resonance perspective on octacalcium phosphate and its hybrid derivatives
Author(s) -
Laurencin Danielle,
Li Yang,
Duer Melinda J.,
Iuga Dinu,
Gervais Christel,
Bonhomme Christian
Publication year - 2021
Publication title -
magnetic resonance in chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 72
eISSN - 1097-458X
pISSN - 0749-1581
DOI - 10.1002/mrc.5149
Subject(s) - chemistry , octacalcium phosphate , magic angle spinning , nmr spectra database , solid state nuclear magnetic resonance , nuclear magnetic resonance spectroscopy , density functional theory , crystallography , spectral line , nuclear magnetic resonance , phosphate , computational chemistry , stereochemistry , organic chemistry , physics , astronomy
43 Ca nuclear magnetic resonance (NMR) spectroscopy has been extensively applied to the detailed study of octacalcium phosphate (OCP), Ca 8 (HPO 4 ) 2 (PO 4 ) 4 .5H 2 O, and hybrid derivatives involving intercalated metabolic acids (viz., citrate, succinate, formate, and adipate). Such phases are of importance in the development of a better understanding of bone structure. High‐resolution 43 Ca magic angle spinning (MAS) experiments, including double‐rotation (DOR) 43 Ca NMR, as well as 43 Ca{ 1 H} rotational echo DOR (REDOR) and 31 P{ 43 Ca} REAPDOR NMR spectra, were recorded on a 43 Ca‐labeled OCP phase at very high magnetic field (20 T), and complemented by ab initio calculations of NMR parameters using the Gauge‐Including Projector Augmented Wave–density functional theory (GIPAW‐DFT) method. This enabled a partial assignment of the eight inequivalent Ca 2+ sites of OCP. Natural‐abundance 43 Ca MAS NMR spectra were then recorded for the hybrid organic–inorganic derivatives, revealing changes in the 43 Ca lineshape. In the case of the citrate derivative, these could be interpreted on the basis of computational models of the structure. Overall, this study highlights the advantages of combining high‐resolution 43 Ca NMR experiments and computational modeling for studying complex hybrid biomaterials.