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

• Demet Demirci Gültekin,
• Arif Daştan,
• Yavuz Taşkesenligil,
• Cavit Kazaz,
• Yunus Zorlu and
• Metin Balci

Beilstein J. Org. Chem. 2023, 19, 764–770, doi:10.3762/bjoc.19.56

• Kutateladze claimed that based on an applied machine learning-augmented DFT method for computational NMR that the structure of the product, (1R,2R,3S,4S,7s)-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

• erroneous mechanistic pathway. Keywords: bromination; computational NMR; γ-gauche effect; NMR; NOE-Diff experiments; Introduction Nuclear magnetic resonance (NMR) spectroscopy is one of the most important analytical tools used to determine the structure of organic compounds. NMR not only confirms the

• have developed a machine learning-augmented DFT method for computational NMR, DU8ML, for fast and ‘accurate’ computational approaches [2]. They applied this computational method to a number of previously published organic compounds and claimed to have revised some structures and proposed new mechanisms