C13Shift: a computer program for the prediction of carbon-13 NMR spectra based on an open set of additivity rules

Pretsch, Ernö; Fürst, Andràs; Badertscher, Martin; Buergin, R.; Munk, Morton E.

doi:10.1021/ci00008a005

Cited by 65 publications

(54 citation statements)

References 8 publications

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“…Detailed assignments are not available for this crowded spectral region. First, we assigned these peaks by calculating the chemical shifts using the additivity rules proposed for isotropic liquids (61)(62)(63)(64)(65). With such assignments, the measured jS CH j order parameters for DMPC lipids agreed well with solid-state 2 H-NMR-determined jS CD j values (43,112).…”

Section: Dipolar Order Parameters Reflect Structural and Dynamic Featmentioning

confidence: 63%

See 1 more Smart Citation

Area per Lipid and Cholesterol Interactions in Membranes from Separated Local-Field 13 C NMR Spectroscopy

Leftin

Molugu

Job

et al. 2014

Biophysical Journal

108

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Investigations of lipid membranes using NMR spectroscopy generally require isotopic labeling, often precluding structural studies of complex lipid systems. Solid-state (13)C magic-angle spinning NMR spectroscopy at natural isotopic abundance gives site-specific structural information that can aid in the characterization of complex biomembranes. Using the separated local-field experiment DROSS, we resolved (13)C-(1)H residual dipolar couplings that were interpreted with a statistical mean-torque model. Liquid-disordered and liquid-ordered phases were characterized according to membrane thickness and average cross-sectional area per lipid. Knowledge of such structural parameters is vital for molecular dynamics simulations, and provides information about the balance of forces in membrane lipid bilayers. Experiments were conducted with both phosphatidylcholine (dimyristoylphosphatidylcholine (DMPC) and palmitoyloleoylphosphatidylcholine (POPC)) and egg-yolk sphingomyelin (EYSM) lipids, and allowed us to extract segmental order parameters from the (13)C-(1)H residual dipolar couplings. Order parameters were used to calculate membrane structural quantities, including the area per lipid and bilayer thickness. Relative to POPC, EYSM is more ordered in the ld phase and experiences less structural perturbation upon adding 50% cholesterol to form the lo phase. The loss of configurational entropy is smaller for EYSM than for POPC, thus favoring its interaction with cholesterol in raftlike lipid systems. Our studies show that solid-state (13)C NMR spectroscopy is applicable to investigations of complex lipids and makes it possible to obtain structural parameters for biomembrane systems where isotope labeling may be prohibitive.

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Section: Dipolar Order Parameters Reflect Structural and Dynamic Featmentioning

confidence: 63%

“…To see this figure in color, go online. for isotropic liquids(61,62,64,65). Even so, in the spectral region between 29.5 ppm and 31.5 ppm there is considerable overlap of the resonances from lipid hydrocarbon chain segments.…”

mentioning

confidence: 99%

Area per Lipid and Cholesterol Interactions in Membranes from Separated Local-Field 13 C NMR Spectroscopy

Leftin

Molugu

Job

et al. 2014

Biophysical Journal

108

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“…The results obtained in a previous paper show that such a kind of specific models can provide much better predictions than the general additive models in use for the prediction of the 13 C NMR chemical shift. Table 5 presents the number of poorly predicted values by the model developed by Pretsch [38][39][40][41] and implemented in the ChemWindows program. 42 The prediction results of this additive model are comparable with the results of the MLR model and much poorer than the results provided by the neural model.…”

Section: Resultsmentioning

confidence: 99%

¹³C NMR Chemical Shift Prediction of the sp³ Carbon Atoms in the α Position Relative to the Double Bond in Acyclic Alkenes

Ivanciuc

Rabine

Cabrol‐Bass

et al. 1997

J. Chem. Inf. Comput. Sci.

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The 13 C NMR chemical shift of sp 3 carbon atoms situated in the R position relative to the double bond in acyclic alkenes was estimated with multilayer feedforward artificial neural networks (ANNs) and multilinear regression (MLR), using as structural descriptors a topo-stereochemical code which characterizes the environment of the resonating carbon atom. The predictive ability of the two models was tested by the leave-20%-out cross-validation method. The neural model provides better results than the MLR model both in calibration and in cross-validation, demonstrating that there exists a nonlinear relationship between the structural descriptors and the investigated 13 C NMR chemical shift and that the neural model is capable to capture such a relationship in a simple and effective way. A comparison between a general model for the estimation of the 13 C NMR chemical shift and the ANN model indicates that general models are outperformed by more specific models, and in order to improve the predictions a possible way is to develop environment-specific models. The approach proposed in this paper can be used in automated spectra interpretation or computer-assisted structure elucidation to constrain the number of possible candidates generated from the experimental spectra.

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“…Recently, for instance, Sarotti and Pellegrinet [39] suggested using for GIAO-based 13 C chemical shift calculation a multi-standard method (MSTD). When the MSTD approach is employed, two reference compounds should be used: (i) methanol -for the prediction of chemical shifts of sp 3 -hybridized carbon atoms and (ii) benzene -for sp and sp 2 -hybridized ones. The authors concluded that the mPW1PW91/6-31G(d) protocol constituted a level of theory that provides maximal reliability and MAE values around 1.5 ppm at minimal computational cost when applying the MSTD approach.…”

Section: Introductionmentioning

confidence: 99%

Empirical and DFT GIAO quantum‐mechanical methods of ¹³C chemical shifts prediction: competitors or collaborators?

Elyashberg¹,

Blinov²,

Smurnyy³

et al. 2010

Magnetic Reson in Chemistry

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The accuracy of (13)C chemical shift prediction by both DFT GIAO quantum-mechanical (QM) and empirical methods was compared using 205 structures for which experimental and QM-calculated chemical shifts were published in the literature. For these structures, (13)C chemical shifts were calculated using HOSE code and neural network (NN) algorithms developed within our laboratory. In total, 2531 chemical shifts were analyzed and statistically processed. It has been shown that, in general, QM methods are capable of providing similar but inferior accuracy to the empirical approaches, but quite frequently they give larger mean average error values. For the structural set examined in this work, the following mean absolute errors (MAEs) were found: MAE(HOSE) = 1.58 ppm, MAE(NN) = 1.91 ppm and MAE(QM) = 3.29 ppm. A strategy of combined application of both the empirical and DFT GIAO approaches is suggested. The strategy could provide a synergistic effect if the advantages intrinsic to each method are exploited.

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C13Shift: a computer program for the prediction of carbon-13 NMR spectra based on an open set of additivity rules

Cited by 65 publications

References 8 publications

Area per Lipid and Cholesterol Interactions in Membranes from Separated Local-Field 13 C NMR Spectroscopy

Area per Lipid and Cholesterol Interactions in Membranes from Separated Local-Field 13 C NMR Spectroscopy

¹³C NMR Chemical Shift Prediction of the sp³ Carbon Atoms in the α Position Relative to the Double Bond in Acyclic Alkenes

Empirical and DFT GIAO quantum‐mechanical methods of ¹³C chemical shifts prediction: competitors or collaborators?

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C13Shift: a computer program for the prediction of carbon-13 NMR spectra based on an open set of additivity rules

Cited by 65 publications

References 8 publications

Area per Lipid and Cholesterol Interactions in Membranes from Separated Local-Field 13 C NMR Spectroscopy

Area per Lipid and Cholesterol Interactions in Membranes from Separated Local-Field 13 C NMR Spectroscopy

13C NMR Chemical Shift Prediction of the sp3 Carbon Atoms in the α Position Relative to the Double Bond in Acyclic Alkenes

Empirical and DFT GIAO quantum‐mechanical methods of 13C chemical shifts prediction: competitors or collaborators?

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Product

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About

¹³C NMR Chemical Shift Prediction of the sp³ Carbon Atoms in the α Position Relative to the Double Bond in Acyclic Alkenes

Empirical and DFT GIAO quantum‐mechanical methods of ¹³C chemical shifts prediction: competitors or collaborators?