(Figure ). The variance across protein families is quite large, with some protein families having near perfect predictions and other protein families having extremely poor predictive performance. Adding information to the training set about the left out protein family tends to increase the average correlation and decrease the average error across protein families, (Figure and S9). However, only adding one pair of ligands from the left out protein family does not seem to help the performance of the model. We need at least 4 ligands from the protein family that we are evaluating on to see an increase in our RBFE prediction performance. Adding ligands from the left out protein family to our training data seems to have a greater impact on the correlation of the RBFE predictions rather than the error.