In this experiment, we follow the experimental setup proposed by You et al. (2018). We optimize the penalized logP score of 800 low-scoring molecules from the ZINC data set. Our genetic algorithm is initiated with a molecule from the data set, and we run each experiment for 20 generations and a population size of 500 without the discriminator. For each run, we report the molecule m that increases the penalized logP the greatest, while possessing a similarity sim(m,m′) δ with the respective reference molecules m′. We calculate molecular similarity based on Morgan Fingerprints of radius 2. To ensure generation of molecules possessing a certain similarity, for molecule m we modify the fitness to: Here, SimilarityPenalty(m) is 0 if sim(m,m′) δ and 106 otherwise.