To confirm the highlighted regions as important for the binding, we created a set of decoy kinase inhibitors to be used as adversarial examples for the explanations from the true positive predictions in the previous sections. In the decoys the nitrogen H-acceptors or donors were replaced with carbon atoms. Of the investigated set of adversarial kinase inhibitors, the model predicted 81% (80 molecules) as inactive on kinases. The adversarial examples do not show the same highlighted regions their active counterparts, confirming that the explanations highlight regions important for binding. Figure shows how the model no longer highlights a clearly important region. However, the false positive predictions of the adversarial molecules show that the model, despite understanding about the importance of H-donors and acceptors, overestimates the role the scaffold plays. In false positive predictions for the adversarial examples, the explanations were almost identical to the explanations on the original molecules. With some chemical understanding (H-donors and acceptors are important for the binding) the Myerson values then highlight this flaw in the model. But this experiment also shows that in order to rely on the Myerson explanations to identify key functional groups, a high-accuracy model is important.