A comparison of the feature importance of the GP and ET models reveals different features as the most influential in transport activity. The GP model found the number of Sulfur atoms to be important (Figure ). Interestingly, the presence of one Sulfur atom (nS_1) contributes to a higher predicted probability for class 1 (active transporter), while the presence of zero (nS_0) or two Sulfur atoms (nS_2) contributes to a higher predicted probability for class 0 (inactive transporter). For the ET model, while the relative ranking of features differs, there is considerable overlap between the top important features ranked by SHAP, permutation, and Gini feature importances (Figure and). SHAP suggests that a higher count of aromatic rings (n5ARing_0) might correlate with better transport activity, and the number of non-hydrogen atoms bonded to methylene groups (NdsCH_2) could have a similar impact. The feature with the highest Gini importance is P EOE_V SA6, which is the sum of van der Waals surface area atomic contribution (VSA)for atoms that present Gasteiger charges (PEOE) between 0.15 and 0.20. It intends to capture the direct electrostatic interactions. P EOE_V SA6 is also highlighted as a top feature by SHAP, which found a higher value corresponds to a higher predicted probability for class 0 (inactive transporter).