Real-time prediction of <sup>1</sup> H and <sup>13</sup> C chemical shifts with DFT accuracy using a 3D graph neural network
Yanfei Guan, S. V. Shree Sowndarya, Liliana C. Gallegos, Peter C. St. John, Robert S. Paton
Abstract
C chemical shifts with comparable accuracy to the best-performing DFT functionals (1.5 ppm) in around 1/6000 of the CPU time. An automated prediction webserver and graphical interface are accessible online at http://nova.chem.colostate.edu/cascade/. We further demonstrate the model in three applications: first, we use the model to decide the correct organic structure from candidates through experimental spectra, including complex stereoisomers; second, we automatically detect and revise incorrect chemical shift assignments in a popular NMR database, the NMRShiftDB; and third, we use NMR chemical shifts as descriptors for determination of the sites of electrophilic aromatic substitution.