Figure shows the three most representative chemical structures per library as calculated with RDKit fingerprints. The twenty more representatives (medoids) per library (including the three in Figure ) are listed in Table in the Supporting Information. The medoids are calculated using the algorithm described recently. In short, we calculate the complementary similarity of every molecule in a library, that is, the similarity of all but the selected molecule (which we can do in O(N) for the whole set). Then, we can rank all the molecules from more (e.g., medoid-like) to less (e.g., outlier-like) representative by simply ordering them according to the increasing value of their complementary similarity. The reasoning behind this is very simple: by removing a molecule that is closely related to all of the rest we leave behind a more 'disorganized' set, which will have a lower complementary similarity. In this context, the medoids could be interpreted as chemical structural markers or "signatures" of the compounds libraries and contribute to profile the chemical contents of each data set. <Figure 7 here >