Eileen Dover and Günther Schlonk
*Note: this article was originally published in early 2022
Abstract: It’s only a bit of ethyl acetate, what does it matter, right?
Specific: Have you ever attempted to reproduce a literature procedure, compared your shitty bar-code style spectra to their exhibition grade masterpiece and exclaimed “how the fuck did they do that?” Then perhaps you too have encountered BS-NMR.
Acquiring NMR data for publications can be gruelling, time consuming and infuriating. Supporting-information (SI) files are now the third largest category on the internet, after porn and cat videos. The average SI is thicker than MTG, with hundreds of spectra attached. Each one is a monument to a molecule that was synthesised, purified, dried, analysed, processed, and assigned, representing months of tedious and repetitive work. So it’s hardly surprising that some in the chemical community have sought to “streamline” this process with some “unconventional post-spectral processing” techniques. Funding at the University of West Failure has grown pretty tight, so our group needed a citation smash-hit sharpish to keep us off the streets. Lacking any inspiration of our own, we thought we could rip off that Goldberg paper1 by listing these techniques, collectively known as PS-NMR (photoshop-NMR), BS-NMR (self-explanatory) or 1H-TRIKSY. This work will be of use to both cheating authors and reviewers trying to catch them. As long as they both cite us, we don’t care which is which.
For a first pass at BS-NMR, it’s important to establish if the reviewers at your chosen journal are even going to read your SI. This is particularly important for the higher-tier journals. As a rule, their reviewers have less available time, more fulfilment in life, partners who love them and children they can tolerate. This attitude is often reflected in their rushed approach to your work. In this case, try attaching your NMR spectra as raw, unprocessed FID, and pray that your reviewers only read as far as the corresponding author’s surname (Figure 1).
Reviewers at discipline-specific journals, however, will gladly take a week off work to go through your manuscript like an air crash investigator, looking the faintest hint of a grease-peak.2 In this case, you’re screwed. But if your reviewers inhabit the middle ground, BS-NMR can improve a manuscript with minimal time lost. As the old adage goes, “an hour in the library can save a day in the lab, but an hour in photoshop can save six months.” The next simplest application of BS-NMR is “selective cropping”. This technique is particularly useful when desirable peaks are grouped at one end of the spectrum, and impurities at the other. In this case, one can simply chop off the unwanted end of the spectrum (Figure 2).
This sample could be full of solvent residue, grease, water and assorted other shit, but no one will ever know. Let us turn now to a sample that actually is full of solvent residue, grease, water and shit. Figure 3 shows a sample of the popular study-drug, potassium procrastinate (3).
When obtained from street dealers, this narcotic is frequently cut with organic solvents, amorphous silica and vacuum grease. The sample displayed above clearly exhibits several of these undesirable additives. A popular method of supressing multiple impurities like this is to zoom the whole spectrum out to an almost sarcastic extent (Figure 4).
The more astute reviewer will request an enlargement of this figure, at which point they may notice the additional peaks. The optimisation of this spectrum will therefor require more rigorous methods.
The DCM peak at ~5.5 is large but narrow, making it susceptible to the “white text-box treatment” (Figure 5A). This is only noticeable upon magnification. The acetone, water and shit peaks are too broad to be effectively resolved by this method (figure 5B), representing a clear case for “localised baseline correction”. When performing this correction, it is imperative that the new baseline is appropriately phased (figure 5C) and tuned to the correct nucleus (figure 5D). Finally, the ether triplet at 0.9 ppm is amenable to “selective amplitude subtraction” (figure 5 E).
With this array of operations, it is possible to turn most shitty NMRs into something vaguely publishable. Yet there are some researchers out there who choose, for whatever reason, to entirely fabricate their spectral data. This is typically done by using NMR prediction software, and passing off the result as real data. We used the Faustian software package to generate an NMR spectrum of the antipsychotic drug Profanidol (4, Figure 6).
The processing methods described above may become redundant, with the recent announcement from the CCDC that it is permissible to state that “solvent peaks have been omitted for clarity”.3
Conclusion
There may be more ways of doctoring NMR spectra, but no-one has been caught using them yet. When this happens, we’ll be there to report it.
NMR spectra were collected in deuterated olive oil on a 420MHz Varibrük Advance III spectrometer. Other experimental data, spectra and reaction conditions are available from behind the bar at The Kings Head, 42 Phlogiston St, Little Whining, West Failure. Just knock three times and ask for Mickey.
Acknowledgements
The authors wish to thank the chemistry community at large for providing the inspiration for this work.
Author Contributions
Eileen Dover sourced the drug samples for figures 2–6. Günther Schlonk processed the data, prepared the manuscript, and bribed reviewer 2 with a bottle of scotch.
About the Authors
Günther Schlonk lost his membrum virile in a lab accident in 2007. He now refers to his testicles as his “lone pair”.
Conflicts of Interest
Günther Schlonk has never used these techniques personally, but has published some pretty dubious spectra in ACS Peripheral Science.
The authors regret that nothing they can write is as funny as Proton Enhanced Nuclear Induction Spectroscopy.
Notes and references
1 K. I. Goldberg et al. 2010, Organometallics. 29, 2176–2179.
2 Not to mention any names (JOC).
3 Everyone on Twitter for about two weeks in January.