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Table 1 Comparison of model performance and properties for non-sulphur containing structures generated by the two models

From: Molecular de-novo design through deep reinforcement learning

Model Prior Agent Action basis REINFORCE REINFORCE + Prior
Fraction of valid SMILES 0.94 ± 0.01 0.95 ± 0.01 0.95 ± 0.01 0.98 ± 0.00 0.98 ± 0.00
Fraction without sulphur 0.66 ± 0.01 0.98 ± 0.00 0.92 ± 0.02 0.98 ± 0.00 0.92 ± 0.01
Average molecular weight 371 ± 1.70 367 ± 3.30 372 ± 0.94 585 ± 27.4 232 ± 5.25
Average cLogP 3.36 ± 0.04 3.37 ± 0.09 3.39 ± 0.02 11.3 ± 0.85 3.05 ± 0.02
Average NumRotBonds 5.39 ± 0.04 5.41 ± 0.07 6.08 ± 0.04 30.0 ± 2.17 2.8 ± 0.11
Average NumAromRings 2.26 ± 0.02 2.26 ± 0.02 2.09 ± 0.02 0.57 ± 0.04 2.11 ± 0.02
  1. Properties reported as Mean ± SD