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. Author manuscript; available in PMC: 2022 Oct 2.
Published in final edited form as: Proc Mach Learn Res. 2022 Jul;162:5777–5792.

Table 5.

Comparison of generated ligands for ESR1 and ACAA1 following multi-objective optimization and refinement.

Ligand Optimized prop. Non-optimized prop.
KD (AD) (↓) QED (↑) SA (↓) KD (ABFE) (↓) Lipinski PAINS (↓) Fsp3 (↑) MCE-18 (↑)

ESR1

LIMO mol. #1 4.6 0.43 4.8 6 · 10−5 0 0.16 90
LIMO mol. #2 2.8 0.64 4.9 1000 0 0.52 76

GCPN mol. #1 810 0.43 4.2 - 0 0.29 22
GCPN mol. #2 2.7 · 104 0.80 3.7 - 0 0.56 47

Tamoxifen 87 0.45 2.0 1.5* 0 0.23 16
Raloxifene 7.9 · 106 0.32 2.4 0.030* 0 0.25 59

ACAA1

LIMO mol. #1 28 0.57 5.5 4 · 104 0 0.52 52
LIMO mol. #2 31 0.44 4.9 No binding 0 0.81 45

GCPN mol. #1 8500 0.69 4.2 - 0 0.52 61
GCPN mol. #2 8500 0.54 4.3 - 0 0.52 30

Arrows indicate whether a high score (↑) or low score (↓) is desired. High QED, Fsp3, and satisfying Lipinski’s Rule of 5 suggest drug-likeness. A low number of PAINS alerts indicates a low likelihood of false positive results in binding assays. MCE-18 is a measure of molecular novelty based on complexity, and SA is a measure of synthesizability. KD values in nM are computed binding affinities from AutoDock-GPU (AD) and from more rigorous absolute binding free energy calculations (ABFE). See Appendix A.2 for a full description of each metric.

*

indicates an experimentally determined value obtained from BindingDB (Liu et al., 2007).