Model Performance on LIT-PCBA our initial results demonstrated the same problems seen in PDBbind -namely, that the model overfit to targets in the training set, and has similar performance with and without receptor information. It seems that simply adding more data doesn't automatically yield better generalization. We hypothesized that the source of this issue was biased protein-ligand co-occurrence in the dataset. Since ChEMBL activities are curated from publications, many molecules were specifically designed to bind to the target they were tested on. Thus it may be possible to guess the relevant target information simply by analyzing the ligand (as our models appeared to be doing). This process, however, does not generalize well to new targets, which is why the models overfit.