Real-time prediction of ¹H and ¹³C chemical shifts with DFT accuracy using a 3D graph neural network.

ABSTRACT: Nuclear magnetic resonance (NMR) is one of the primary techniques used to elucidate the chemical structure, bonding, stereochemistry, and conformation of organic compounds. The distinct chemical shifts in an NMR spectrum depend upon each atom's local chemical environment and are influenced by both through-bond and through-space interactions with other atoms and functional groups. The in silico prediction of NMR chemical shifts using quantum mechanical (QM) calculations is now commonplace in aiding organic structural assignment since spectra can be computed for several candidate structures and then compared with experimental values to find the best possible match. However, the computational demands of calculating multiple structural- and stereo-isomers, each of which may typically ex

SUBMITTER: Guan Y 

PROVIDER: S-EPMC8457395 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature