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Bromination of endo- 7-norbornene derivatives revisited: failure of a computational NMR method in elucidating the configuration of an organic structure.

Demet Demirci GültekinArif DastanYavuz TaşkesenligilCavit KazazYunus ZorluMetin Balci
Published in: Beilstein journal of organic chemistry (2023)
Previously we reported on the bromination of endo- 7-bromonorbornene at different temperatures yielding mixtures of addition products. The structural elucidations of the formed compounds were achieved by NMR spectroscopy. Particularly, the γ-gauche effect and long-range couplings were instrumental in assigning the stereochemistry of the adducts. However, in a recent paper, Novitskiy and Kutateladze claimed that based on an applied machine learning-augmented DFT method for computational NMR that the structure of the product, (1 R ,2 R ,3 S ,4 S ,7 s )-2,3,7-tribromobicyclo[2.2.1]heptane was wrong. With the aid of their computational method, they revised a number of published structures, including ours, and assigned our product the structure (1 R ,2 S ,3 R , 4S ,7 r )-2,3,7-tribromobicyclo[2.2.1]heptane. To fit their revised structure, they proposed an alternative mechanism featuring a skeletal rearrangement without the intermediacy of a carbocation. Herein, we are not only confirming the structure originally assigned by us through crucial NMR experiments, we also present the ultimate structural proof by means of X-ray crystallography. Moreover, we disprove the mechanism proposed by the aforementioned authors based on sound mechanistic reasoning and point to an oversight by the authors that led them to an erroneous mechanistic pathway.
Keyphrases
  • high resolution
  • machine learning
  • magnetic resonance
  • systematic review
  • randomized controlled trial
  • computed tomography
  • mass spectrometry