Regarding the conventional MPNN model, the ROC-AUC was 0.695 which was lower than the MM-GB/SA regression model, and the accuracy was 0.684 which was identical to it. Respective values from 5-fold CV were 0.710 and 0.641, which indicates no significant overfitting. The precision and specificity were lowest in this study (at 0.637 and 0.655, respectively). However, the sensitivity was higher (0.716) than those of other models (0.614 to 0.640). Consequently, we can see that this MPNN model has lower predictivity in overall metrics; however, its high sensitivity is beneficial not to miss any inhibitors, which is a very important aspect in practical project work.