Abstract
Apiose is a naturally occurring, uncommon branched-chain pentose found in plant cell walls as part of the complex polysaccharide Rhamnogalacturonan II (RG-II). The structural elucidation of the three-dimensional structure of RG-II by nuclear magnetic resonance (NMR) spectroscopy is significantly complicated by the ability of apiose to cross-link via borate ester linkages to form RG-II dimers. Here, we developed a computational approach to gain insight into the structure–spectra relationships of apio–borate complexes in an effort to complement experimental assignments of NMR signals in RG-II. Our protocol involved structure optimizations using density functional theory (DFT) followed by isotropic magnetic shielding constant calculations using the gauge-invariant atomic orbital (GIAO) approach to predict chemical shifts. We evaluated the accuracy of 23 different functional–basis set (FBS) combinations with and without implicit solvation for predicting the experimental 1H and 13C shifts of a methyl apioside and its three borate derivatives. The computed NMR predictions were evaluated on the basis of the overall shift accuracy, relative shift ordering, and the ability to distinguish between dimers and monomers. We demonstrate that the consideration of implicit solvation during geometry optimizations in addition to the magnetic shielding constant calculations greatly increases the accuracy of NMR chemical shift predictions and can correctly reproduce the ordering of the 13C shifts and yield predictions that are, on average, within 1.50 ppm for 13C and 0.12 ppm for 1H shifts for apio–borate compounds.
Highlights
Computational prediction of the spectroscopic chemical shifts of nuclear magnetic resonance (NMR) can significantly improve its capability as an essential technique for the identification and characterization of complex biomolecular structures in solution (Duus et al, 2000; Wüthrich, 2003; Bifulco et al, 2007; Lodewyk et al, 2012; Tantillo, 2013; Iron, 2017; Krivdin, 2019)
We evaluated 23 functional–basis set (FBS) combinations based on the levels of theory recommended in the literature for NMR chemical shift predictions and applied them using implicit solvation models and a reference correction to study apio–borate compounds
We demonstrate that considering implicit solvation during both the geometry optimization and the shielding constant calculation results in lower mean absolute errors (MAEs) for computational predictions with respect to the experimental data for apio–borate compounds
Summary
Computational prediction of the spectroscopic chemical shifts of nuclear magnetic resonance (NMR) can significantly improve its capability as an essential technique for the identification and characterization of complex biomolecular structures in solution (Duus et al, 2000; Wüthrich, 2003; Bifulco et al, 2007; Lodewyk et al, 2012; Tantillo, 2013; Iron, 2017; Krivdin, 2019). Apiose is one of the 12 monosaccharide units in RG-II and has special significance as it is involved in dimerizing RG-II via a borate–ester cross-link (O’Neill et al, 1996; Bharadwaj et al, 2020). The formation of this borate–ester cross-link is required for normal plant growth, and most RG-II found in the plant cell wall remains cross-linked (O’Neill et al, 2004). The three-dimensional (3D) structure of RG-II in solution in its monomeric and dimerized states still remains to be elucidated
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