Comparing these results to models trained on interactions containing only tryptophan or only tyrosine and phenylalanine, the models trained on all data perform as well as or better than models trained on specific data subsets (Supporting Information Tables and and Figures and). In evaluating the feature importance for each model (see Computational Methods), we identified the features most critical for predicting the energetic strength of a given CH-p stacking orientation. Despite differences in the most important features for each model, four features, dC2-Ctr, dC3-Ctr, dC5-Ctr, and dC6-Ctr, consistently rank among the most important (Supporting Information Table ). These features involve carbon atoms that are distributed across the carbohydrate.