After pre-training, the model was fine-tuned with the SMILES strings of 41 LXRα agonists (EC50 < 0.5 µM, Supporting Table ). This fine-tuning step allowed us to focus the model on features that are shared by a chosen set of compounds; therefore, it was used to bias the generation of new SMILES strings toward the chemical space of known LXRα agonists. Both the number of fine-tuning epochs for molecule design and the sampling temperature for SMILES string generation were automatically determined to optimize three parameters simultaneously (Supporting Figure ), namely: the (i) predicted LXR activity, (ii) scaffold diversity, 37 and (iii) pharmacophore similarity to the fine-tuning compounds. From the fine-tuned model (epochs 15 to 20), 3000 SMILES strings were sampled per epoch. Only those generated molecules were retained that were not included in the pre-training and the fine-tuning sets, namely, a total of 3626 de novo designs.