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Default Alignment of NMR spectra – The problem: Part I

Alignment of NMR spectra – The problem: Part I

The chemical shift is of great importance for NMR spectroscopy because it reflects the chemical environment of the nuclides under observation providing detailed information about the structure of a molecule.
Although the chemical shift of a nucleus in a molecule is generally assumed to be fairly stable, there are a number of experimental factors (pH, ionic strength, solvent, field inhomogeneity –bad shimming, temperature, etc) which might produce slight or even quite significant variations in chemical shifts.
This is particularly important in metabonomics/metabolomics where shifts of NMR peaks due to differences in pH and other physico-chemical interactions are quite common in NMR spectra of biological samples. For example, some important metabolites, such as citrate or taurine, have peaks whose chemical shifts fluctuate in an uncontrolled way from sample to sample. These variations can cause spurious grouping of samples in chemometric models.

Example of peak position variation in the citrate region (simulated data)

Whilst it is critical to setup the experimental conditions in the best way to minimize these chemical shift fluctuations (for example by using an appropriate buffer; BTW, there exists a standard protocol for biofluid [urine, serum/plasma] and tissue sample collection and preparation as described by Beckonert et al. [1]), spectral misalignments may still occur and special post-processing methods have to be employed.
Another example in which variation in the chemical shift is important occurs in the context of kinetics or reaction monitoring experiments by NMR. For example, consider the following reaction monitoring example [2]:

Reaction monitoring data set for the solution of phenylethylamine and 2-methoxyphenyl acetate in D2O, with every 35th spectrum from the first (bottom) to the last (top) shown (see [2])

It can be appreciated that during the course of the reaction, the chemical shifts of several signals change as a result of the change in pH (in this case, as a hydrolysis proceeds)
Although characterizing these chemical shifts fluctuations can be sometimes important (pH or drug binding-induced chemical shifts, for example) in general they obscure the process of pattern recognition (metabonomics) and impede the performance of data analysis (e.g. selection of the peaks whose intensities/heights need to be monitored becomes more difficult).

In my next posts, I will cover different ways to deal with the peak misalignment problem, first in the field of metabonomics and then in reaction monitoring.

References:
[1] O. Beckonert, H.C. Keun, T.M. Ebbels, J. Bundy, E. Holmes, J.C. Lindon, J.K. Nicholson, Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts, Nat. Protoc. 2 (2007) 2692–2703

[2] M. Khajeh, M. A. Bernsteinb, G. A. Morrisa, Magn. Reson. Chem. 2010, 48, 516–522








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