Prediction of second-order interactions is a classic link prediction problem. Standard regression metrics do not properly represent the model's performance, so we used ROC AUC (area under the receiver operating characteristic curve) and mean ROC AUC. The value of ROC AUC is equal to 0.9934, which is a good result for such complex tasks. Interestingly, the value for the mean ROC AUC of 0.9926 is a bit smaller, suggesting that there might be some outlier molecules. Finally, the properties of these interactions were also predicted. As can be seen from the data, the only drop in performance is observed for the values of Fock-matrix elements.