From: Molecular de-novo design through deep reinforcement learning
Model | Prior | Agent | Prior^{a} | Agent^{a} |
---|---|---|---|---|
Fraction valid SMILES | 0.94 | 0.99 | 0.94 | 0.99 |
Fraction predicted actives | 0.03 | 0.97 | 0.02 | 0.96 |
Fraction similar to train active | 0.02 | 0.79 | 0.02 | 0.75 |
Fraction similar to test active | 0.01 | 0.46 | 0.01 | 0.38 |
Fraction of test actives recovered (\(\times 10^{-3}\)) | 13.5 | 126 | 2.85 | 72.6 |
Probability of generating a test set active (\(\times 10^{-3}\)) | 0.17 | 40.2 | 0.05 | 15.0 |