A pictorial summary of our workflow is shown in Figure . Using the Chemical Reaction functionality of RDKit, we used the SMARTS language 47 to exchange the heteroaromatic unit of each molecule in a given subset for each of the other types of heteroaromatics listed in Figure . We refer to these heteroaromatic-exchanging transformations as "virtual skeletal edits", since reactions to achieve these transformations may or may not exist (for example, the conversion of pyrimidines into pyrazines is not yet reported) and the transformations are performed in silico. After generating datasets of the products of these virtual transformations, we compared the newly generated molecules against the same heterocycle type in the starting library of molecules to determine which of the computationally generated products are synthetically feasible (or commercially available in the cases of the Mcule and ChEMBL libraries). , respectively. We chose to analyze these datasets separately, since the molecules in each database represent different levels of commercial availability. For example, the Enamine REAL database contains "synthetically feasible" or "make on-demand" molecules, whereas the Mcule and ChEMBL databases contain existing, commercial compounds, with the latter being a manually curated database of bioactive compounds. The numerical values represent the percentage of computationally generated products that are uncharacterized in relation to the starting dataset. This metric identifies which transformations, if developed, would generate the greatest number of previously unknown compounds.