~13C NMR Chemical Shift Prediction of the sp~3 Carbon Atoms in the a Position Relative to the Double Bond in Acyclic Alkenes

摘要

The ~13C NMR chemical shift of sp~3 carbon atoms situated in the α position relative to the double bond in acyclic alkenes was estimated with multilayer feedforward artificial neural networks (ANNs) and multilinear regression (MLR), using as structural descriptors a topo-stereochemical code which characterizes the environment of the resonating carbon atom. The predictive ability of the two models was tested by the leave-20/100-out cross-validation method. The neural model provides better results than the MLR model both in calibration and in cross-validation, demonstrating that there exists a nonlinear relationship between the structural descriptors and the investigated ~13C NMR chemical shift and that the neural model is capable to capture such a relationship in a simple and effective way.