Hyperparameters of the model were optimized before using it for predictions. Dimension of the GNN hidden vector (dim), number of hidden layers of the GNN, and sub-graph radius were optimized by considering the five-fold cross validated F1 score. Three values were used for the dimension of the GNN hidden molecular vector output (i.e. dim = 5, 10 and 15). Numbers 1, 2, and 3 were used to check for the optimum number of hidden layers in the GNN. Finally, the optimum sub-graph radius for the model was selected out of radius = 1, 2 and 3.