We then retrain all models and test them on the EnzymeMap test set, after removing overlap in the training and validation sets with the new test set. For RHEA and MetAMDB, this provides an even harder task trying to predict retrosynthesis steps of reactions for which no close analogue might be available in the training set, so that the low performances in Table were somewhat expected. The performance loss is less for MetAMDB vs. the much smaller RHEA, indicating that MetAMDB covers a wider range of reaction functionalities.