The RBFE prediction of the model varies widely across the different test sets when no finetuning is performed. However, with increasing amounts of finetuning we see that the correlation with experimental affinity increases and the error decreases (Figure , S3, S4,5, S5, S6, S7, S8). Some congeneric series, especially those in the Schindler et al. show almost no improvement when adding more finetuning information. CDK2 shows nearly perfect correlation and zero error with no finetuning performed, likely due to the high ligand similarity to the BindingDB dataset (Table ). A number of congeneric series (TYK2, PFKB3, SYK, and TNKS2) do not show monotonically increasing RBFE performance as more data is added to the finetuning dataset. Finetuning does not provide the same amount of RBFE prediction boost as demonstrated in Jiménez-Luna et al. on both the Mobley et al. and Wang et al. datasets (Figure ).