To further investigate the characteristics of the designs, we computed the natural-product likeness , which captures how similar a molecule is to the chemical space covered by natural products in terms of its substructures (the higher the NP-likeness, the more similar). The novel designs of S4 have significantly higher (Mann-Whitney U test, p < 0.01) values of NP-likeness than the benchmarks, closer to the values of the training and test sets on average (Table ). Moreover, the NP-likeness values better match the distribution of the COCONUT molecules in terms of Kolmogorov-Smirnov (KS) distance , which quantifies how much the cumulative distributions of two observations differ (between 0% and 100%; the lower, the closer the distributions).