The use of the SA score modifier has a much bigger effect on the number of molecules with better scores than the known binders and their average docking score. The effect is most pronounced for CM where the number of good binders drops more than an order of magnitude to only 181 molecules, while the decrease is about 70% for both β 2 AR and DDR1 and 23% for BCD. The most likely explanation is that ligands that bind well in the CM binding pocket tend to have high (bad) SA scores compared to the other targets. This is supported by the fact that the SA scores for the known binders TSA, carazolol, ponatinib, and 2,6-ANS (Table ) are 5.4, 2.6, 2.9, and 1.8, respectively. The corresponding Molecule.one scores are 10.0, 2.9, 2.3, and 2.2, which indicates that the heuristic scores correlate well with the more sophisticated ML approach used by Molecule.one. With fewer molecules in the final population with high scores the average score necessarily increases (becomes less negative). The good news is that the fraction of molecules in the final population that Molecule.one deems synthetically accessible increases significantly to between 0.24 to 0.64. These fraction can be further increased to between 0.76 and 0.91, with only negligible effect on the number of good binders in the final population, by using the score modifier together with the filters. The increase in good binders (to 511) in the case of CM is most likely due to the stochastic nature of the GA searches.