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Table 3 Results of constrained optimization for 800 validation molecules

From: MERMAID: an open source automated hit-to-lead method based on deep reinforcement learning

\(\delta\) GCPN Mol-CycleGAN MERMAID
Improvement Similarity Success (%) Improvement Similarity Success (%) Improvement Similarity Success (%)
0.2 4.12 ± 1.19 0.34 ± 0.11 100 5.79 ± 2.35 0.30 ± 0.11 93.8 9.94 ± 2.74 0.23 ± 0.04 100.0
0.4 2.49 ± 1.30 0.47 ± 0.08 100 2.89 ± 2.08 0.52 ± 0.10 58.8 6.04 ± 2.29 0.42 ± 0.02 100.0
0.6 0.79 ± 0.63 0.68 ± 0.08 100 1.22 ± 1.48 0.69 ± 0.07 19.3 1.99 ± 1.74 0.62 ± 0.02 85.3
  1. The results of GCPN and Mol-CycleGAN are cited from Maziarka et al. [36]. The mean and standard deviation of improvement, similarity, and success rate of generated molecules are shown