However, this is not practically useful as the number of classes is very large. Conversely, despite leading to a larger number of singletons than Ward's clustering (90 and 0, respectively), the application of SCINS also resulted in a higher SP. This is in agreement with the findings presented in the original SCINS paper , where methods such as OptiSim on FCPF_4 fingerprints also performed better than SCINS in terms of lower class spread and number of clusters. One possible explanation for this result is that sets of bioactive compounds for a target tend to contain series of analogues with the same or similar substructures which can be identified Furthermore, we selected Ward's cluster 45 from Figure for visual analysis and illustrated its members in Figure , highlighting their maximum common substructure in red. It can be seen that the molecules contain a large common substructural motif but are also considerably different in size (molecular weight, number of heavy atoms, etc.) and even functionality. This may be desirable when the goal is chemical series identification (as Kruger et al suggested ), but does not ensure that molecules are similar outside of the repeated structural motif. While Morgan fingerprints depend on the connectivity table (unlike SCINS), molecules with different functional groups are within the same cluster because the distance cutoff is relatively high for the set number of clusters that was used here. In order to ensure higher similarity of the compound clusters, one can decrease the distance threshold. However, this would increase the number of clusters substantially. Thus, we can conclude that fingerprint-based clustering tends to identify common substructures but does not ensure topological similarities beyond that substructure. This conclusion is also in agreement with the statement by Vogt that substructure-based fingerprints work best on small molecules comparable in size but do not adequately reflect the overall size or shape of a molecule well. This further highlights the connectivity information loss which results from the abstractions made in SCINS. In Figure this is the relative position of ring connectivity patterns between rings in fused ring assemblies, but it could also be the connectivity between rings and chains.