The drug-likeness of the compounds was evaluated by calculating the Quantitative Estimator of Drug-likeliness (QED) score using RDKit. The QED score considers several molecular descriptors namely, molecular weight, octanol-water partitioning coefficient, number of hydrogen bond acceptors, number of hydrogen bond donors, molecular polar surface area, number of rotatable bonds, number of aromatic rings, and number of structural alerts (presence of unwanted chemical functionalities). Based on the molecular descriptors an estimate of the drug-likeliness of a compound can be estimated where a value close to 1 indicates that a compound is drug-like and 0 indicates that it is not. The distribution of the QED score for the predicted compounds is compared to the distribution of the product compounds in USPTO and is showed in Figure . We can see that the distributions for the predicted compounds are slightly shifted toward lower QED scores. Although the distributions for the predictions are shifted towards lower scores, there is a large overlap between the distributions. A significant proportion of the compounds have high QED scores with 30-32% > 0.6 and 7-8% > 0.8, compared to 46% and 12% for USPTO. Finally, we also note that the distributions of the compound's properties are slightly different compared to what is observed in the USPTO products. Moreover, we observe that the predicted compounds in general are slightly more complex in terms of molecular weight, number of aromatic rings and rotatable bonds etc., see Figure . Specifically, the predicted compounds are slightly larger with more aromatic rings and rotatable bonds. This is likely an effect of the initial sampling of the starting reactants as if these are more complex, the resulting predicted products will also be so.