Each protein target in the subset was modelled independently using the Papyrus Python scripts. Targets for which less than 30 activity values or associated with activity values spanning less than 2 log units were disregarded for modelling. Then for each target, a temporal split between training and test sets was performed: datapoints associated with year 2013 and above constituted the test set. If no activity data was available after year 2013, then the target was disregarded. The 777 Mold2 molecular descriptors were calculated for each molecule and were centered and scaled to unit variance. Extreme Gradient Boosting (XGBoost version 1.4.2) regressors and classifiers were trained on the training set using random seed 1234 and default parameters.