Table in the Supporting Information summarizes the MCC values from each validation phase for the top three best-performing architectures selected for each target. To determine the optimal model, we prioritized the MCC values obtained during the retraining phase (refer to Methods Section 2.4 for further details). As shown in Table , MCC values improved in general after the retraining phase, with the AdaBoost model for IBV Neuraminidase standing out as a particularly strong performer. These results showed the capability of the models to accurately identify promising compounds, underscoring their potential utility in antiviral drug discovery.