1. Alignment of NMR spectra – Part I: The problem
2. Alignment of NMR spectra – Part II: Binning / Bucketing
3. Alignment of NMR spectra – Part III: Global Alignment
4. Alignment of NMR spectra – Part IV: Advanced Alignment
Following the progression of chemical reactions by NMR is becoming more and more popular. Quoting Michael A. Bernstein et al. (Magn. Reson. Chem. 2007; 45: 564–571)
(…)The technique is rich in structural information, and can uniquely provide subtle information on speciation, protonation sites, and intermediate compound production. NMR measurements can be made under quantitative conditions, and one can be confident that all organic species will be observed. These factors combine to make NMR a very attractive tool for these analyses, and address many of the shortcomings in traditional spectroscopic measurements (…)
Typically, as a reaction proceeds, it’s very common to observe very significant chemical shift fluctuations of a given resonance due to, for example, changes in pH or protonation of the starting material, just to mention a few. These changes in chemical shift can be so large that extracting relevant information from those spectra (e.g. intensities/integrals across the data set) can be difficult, so aligning those spectra can be helpful. Let me illustrate this with an example exhibiting clear nonlinear misalignments: peaks at about ca 11.6 ppm do not move whilst the peaks at higher field move very significantly:
Instead of displaying the data set as a stacked plot as above, it might be more convenient to display it as an intensity or bitmap plot because this plotting mode highlights more clearly the alignment /misalignment profiles:
It’s evident that correcting the data using a single reference peak (or a global shift) is not sufficient. In order to align this data set, we can follow two different strategies:
Strategy 1:
Starting with raw spectrum (1), it is possible to perform a full-spectrum correction (global alignment) before the single intervals are aligned:
It can be appreciated that after applying the global alignment, most of the peaks in (2) are now properly aligned, except the peaks at the left which were previously aligned but after this operation get misaligned. This problem will be covered in the next step.
After the spectra have been aligned ‘globally’, the user just needs to select the interval which comprises the peaks left to be aligned as depicted in (1). (2) shows the final result once both the global and local alignment have been applied:
Strategy 2:
A different, although analogous strategy, would consist in aligning two different spectral intervals separately without resorting to a global alignment as shown in (1) below. Note that the peaks in the interval in the left are already well aligned (so selecting this region is optional; if there were some minor misalignment, the algorithm would optimize such residual misalignment).
(2) shows the final result after the two intervals have been aligned. It’s completely equivalent to the result obtained with Strategy 1
Conclusion
In this post I showed how the automatic alignment algorithm can be used to align RM data sets prior to any further analysis. However, there is a better way to extract NMR descriptors from Reaction Monitoring experiments that does not require any prior pre-processing alignment. In fact, I believe that this method, which I will present in my next post, has several advantages (in the context of reaction monitoring), especially in those cases where the chemical shift ordering of some peaks changes during the reaction, situations in which automatic alignment algorithms usually have great trouble dealing with. An example of a reaction monitoring data set showing peaks crossing over is shown below, in bitmap mode (it’s a simulated data set)
Therefore in my next post, I will show how to analyze RM data sets with important peak fluctuations and crossing over
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