Study on Phosphorus Compound/Catechol-Catalyzed Dehydrative Amidation and Its Database Development for Machine Learning.

Herein, we report that the catalytic activity of phosphorus compounds with a P─H bond in dehydrative amidation reactions is substantially enhanced when using catechol derivatives as additives. A systematic investigation into the catalytic activity of four phosphorus compounds and 17 catechol derivatives allowed identifying several effective combinations, for example, dimethyl phosphite and 2,3-dihydroxynaphthalene, for the catalytic amidation of carboxylic acids with amines. The developed catalytic system enables the synthesis of pharmaceuticals and facilitates the amidation of anilines, which are typically considered poor substrates with low reactivity. In addition, machine-learning (ML) models were constructed to validate the effectiveness of the database generated from the above-mentioned investigation. Multilayer perceptron (MLP) models incorporating descriptors derived from both quantum chemical calculations and RDKit provided accurate predictions while maintaining chemical interpretability, which was underscored by a visual analysis using SHAP.