Regarding RF, the Python (ver. 3.7.10) scikit-learn (version 0.24.2) library RandomForest Regressor function was used, and the parameters were set as defaults . Regarding MPNN, the Python (ver. 3.7.10) Chemprop (version 1.3.1) library chemprop function was used, and the parameters were set as defaults . 2.7. Model Validation 5-fold CV was performed using the KFold function in scikit-learn (versions 0.24.2) with parameters: n_splits = 5 and shuffle = True. Furthermore, hold-out test was performed with a separate test dataset. To avoid the biased dataset composition, we repeated these process 6 times (Figure ).