With SMIRKY, we were at least partially successful with all molecule sets as evidenced by our ability to find high total scores and 100% partial scores for the majority of fragment types in smirnoff99Frosst. Initially, we performed simulations of comparable length with SMIRKY as with SMARTY; however, increased complexity made longer simulations necessary. Specifically, we began by performing 10 simulations with 10,000 iterations for each fragment type at all eight temperatures (0, 10 -6 , 10 -5 , 0.0001, 0.001, 0.01, 0.1, 1). However, because SMIRKY goes beyond atom types to fragment types, it necessarily must sample more complex chemical perception trees. For example, torsion fragment types require at least four atoms and potentially substituents as well; decorators may also be required for all these atoms. This results in SMIRKS patterns which involve four or more atoms (three or more bonds) all with decorators-a challenging problem. In SMARTY, the combinatorial problem of discovering sufficiently complex SMARTS patterns was tackled by creating the elemental sampler in order to limit the chemical space being searched. But with SMIRKY, we cannot currently sub-divide the chemical space for these more complex fragments (Section 2.3), so we instead increased the number of iterations. For the most complex molecule set, MiniDrugBank, we increased the number of iterations to 50,000 and then 100,000. In each case, we performed three simulations at each temperature for each fragment type. To summarize our results, we report total scores for in the initial fragment types used in each simulation and the maximum total score received across all simulations (Table ). We also report the fraction of reference fragment types to receive a 100% partial score during any simulation (Table ).