Here, the partition coefficients are calculated using the already trained models from Ref. and Ref. along with Equation . All GNN models use an ensemble approach, i.e., the prediction of multiple models trained on different data splits are averaged to obtain a final prediction. In addition, we consider the Multi-Linear Regression (MLR) and Random Forest Regression (RFR) from that were fitted on the HF-Exp set. The partition coefficient values are taken directly from the original publication . These two regression models use 11 input descriptors, including AlogP (octanol/water partition coefficient using Ghose-Crippen atomic contributions ), which shows a 58% correlation to the toluene-water partition coefficient, cf. . Lastly, we compare to two semi-empirical models: COSMO-RS and Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) . In the COSMO-RS approach , the geometry of each molecule is optimized at GFN2-xTB level and further in the COSMO state using COSMOconf (Dassault Systèmes, 2022a). Next, the solvation free energies of the molecules are calculated in water and toluene at infinite dilution using COSMOtherm (Dassault Systèmes, 2022b). In the MM/PBSA approach, each molecule is optimized using QM, followed by molecular dynamics geometry optimization, and solvation free energies in water and toluene are calculated. In this case, the partition coefficient values are obtained directly from the original publication .