Previously, we used REINVENT to optimize the docking score against other GPCR targets (DRD2, OPRM1, AGTR1 and OX1R) over the course of 3,000 RL updates, the first 500 updates of which are shown in Figure . DRD2 (same data as previously published ) contains a deep hydrophobic sub-pocket and requires a salt bridge interaction with D114 3x32 for ligand activity. OPRM1 similarly forms a salt bridge interaction via D147 3x32 (a structurally conserved position in aminergic receptors ) but with a more open pocket than DRD2. AGTR1 requires important salt bridge and hydrogen bond interactions to R167 4x65 (e.g., via acidic tetrazole of co-crystallised ligand ZD7155) as well as hydrogen bonds to Y35 1x39 on the opposite side of the pocket. Meanwhile OX1R contains four well defined hydrophobic sub-pockets and sometimes a hydrogen bond to N318 6x55 and water mediated hydrogen bond to H344 7x38 , ligands are found to adopt a horseshoe conformation via π-stacking to satisfy these sub-pockets as in the co-crystallised ligand suvorexant. The first two targets' respective docking scores were able to be minimized similarly (Figure and 4b), while the latter two targets' respective docking scores were more challenging and showed little minimization (Figure and) (especially with respect to the distribution of docking scores for known actives). This suggests that the docking score optimization ability of REINVENT was system dependent or that the MOSES n dataset used for RNN pretraining did not contain chemistry amenable to minimizing the docking score for these systems.