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Table 4 Compounds generated using reinforcement learning

From: Memory-assisted reinforcement learning for diverse molecular de novo design

Target Memory type Generated active compounds Unique BM scaffolds Unique carbon skeletons
HTR1A No memory 9323 7312 5446
Compound similarity 16,779 13,304 9887
IdenticalBMScaffold 17,390 13,863 9941
IdenticalCarbonSkeleton 17,597 15,531 12,408
ScaffoldSimilarity 17,383 15,296 12,082
DRD2 No memory 5143 2635 1949
Compound similarity 21,486 17,844 12,749
IdenticalBMScaffold 22,312 14,850 8220
IdenticalCarbonSkeleton 22,115 19,096 12,562
ScaffoldSimilarity 22,784 20,712 16,434
  1. The generative models were directed towards predicting active compounds using RL for 300 iterations. During each iteration, a model generated 100 compounds resulting in a total of 30.000 compounds. Only compounds with a prediction score of at least 0.7 were considered active