Two ways of splitting the target data were used: random split and target split at a ratio of 4:1 (80% training collection, 20% test collection). In the random split, complexes were randomly allocated to the training and test sets. In target split, UniprotIDs split the complexes therefore there are no identical training and testing examples. The target split can therefore be used to approximate the generalization potential. Ligands were split using DeepChem . Scaffold Splitter divides molecules into groups based on their Bemis-Murcko scaffolds; the smallest scaffold groups form the test set.