The results of 40 SMILES-based GA searches for each of the three molecules are shown in Figure . 45%, 0%, and 7% of the searches succeed for celecoxib, troglitazone, and tiotixene, respectively, which all are significantly lower than the 100% success rate for the Shakespeare example. Why do so many of the searches fail? The SMILES strings range in length from 56 to 61 characters and the search uses 25 different characters so the search spaces are larger than in the Shakespeare example. However, the GA used in that example has no problem finding longer sentences (Figure ). The other main difference between the SMILES-based rediscovery and the Shakespeare example is the score. In order to compute the Tanimoto score the SMILES string is first converted to a molecular graph, and this conversion fails for a larger portion of the SMILES strings generated using the mating and mutation operations. The failure is primarily due to incorrect SMILES syntax, such as unmatched parentheses or integers denoting ring-closures. Thus, the rediscovery search can only follow paths through sequence space leading to the target molecules that are composed of valid SMILES strings, which is a small subset of all possible paths (Figure ). This makes the rediscovery task intrinsically harder than the Shakespeare example, where the score can be evaluated for nonsensical strings.