Abstract
Conformation-Dependent Chirality Code that includes information of 3D molecular structures and atomic properties, and can be used to distinguish enantiomers, even if chirality does not result from chiral centers, this is named as a general chiral description of molecules. In this article the conformation-dependent chirality code was implemented by the sum of pi and sigma residual electronegativity as atomic properties and applied to a dataset of 80 chiral secondary alcohols esterified with (R)MTPA and the corresponding 1H NMR chemical shifts. For the training sets composed of 60 chiral secondary alcohols, 96. 7% correct recognitions were obtained and the entire test set of 20 objects were correctly predicted, and 91. 3% objects were correctly predicted for cross-validation of the whole dataset.
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