Here, we chose TFD and TanimotoCombo, rather than the more common RMSD, as key metrics for this analysis. The primary trouble with RMSD is that it is highly dependent on molecular size. For example, a value of 1.0 Åmight correspond to a very large geometric difference for an extremely small molecule (e.g. butane) but a trivial geometric difference for a large, drug-like molecule (e.g. lipitor). Both TFD and TanimotoCombo are dimensionless numbers covering a well defined scale (TFD from 0 to 1; TanimotoCombo from 0 to 2) allowing us to define similarity and difference flags which are independent of molecular size. As described above, these metrics also track well with the qualitative structural differences we hope to identify in molecule pairs. While RMSD also captured some of these differences, its size dependence makes it impractical for surveying a wide variety of molecules.