Although not without its caveats, this type of ligand split is more challenging than random splits as it tests more thoroughly the generalizability to new or less abundant areas of chemical space. Three different ML models were trained using the MDD dataset; Random Forest and SVM with and XGBoost with . Model parameters were selected using 5-fold cross-validation (CV). The models were fitted to the training sets and evaluated on the test sets. Throughout this work boxplots represent results obtained on the test set, with mean (triangle) and median (horizontal line inside the boxplot) values. More details on the Random Forest models and on the Descriptor model (XGB) are present in the Supplementary material section