n summary we observe that natural cut-and-join crossovers produce a large fraction of chemically meaningful candidates. Moreover, unrealistic candidates are easily removed using well-established filtering criteria. Even applying stringent filters for drug-likeness, a significant fraction of the crossover products are retained. It is important to note that in the benchmarking experiment reported here we only tested the suitability of the crossover procedure for chemical space exploration. It is perfectly acceptable in this setting that on average the offsprings are somewhat more difficult to synthesize and a moderate fraction does not conform to viable molecules at all. For successful applications of GAs to chemical structure search it is sufficient that in each step a significant fraction of good candidates are produced and that bad candidates can be rejected efficiently. Cut-and-join crossover for chemical graphs, i.e., structural formulae, clearly satisfies these criteria.