Filtering out compounds outside of this molecular weight range in ChEMBL, as well as the additional Ro5 and Verber criteria with which the compounds in Enamine REAL Diverse comply (as detailed in Methods), results in the loss of around 600,000 compounds (or about 30% of the dataset, leading to 1.3 M compounds) and the loss of 6,000 SCINS classes (or about 80% of the total number of SCINS classes in ChEMBL). Hence, it can be seen that larger molecules contribute disproportionately to SCINS diversity in case of ChEMBL. This is to be expected as heavier compounds containing more heavy atoms can have a larger variety of rings and chains. The distribution of populations in SCINS classes of the resulting ChEMBL set is shown in the box plot in Supplementary Figure and it is noticeably less skewed. Hence, the majority of SCINS classes in ChEMBL arise from a minority of members with properties outside of the ranges in Lipinski's Ro5 and Verber's criteria. However, the number of SCINS classes in ChEMBL after the application of the filters is around 1,500, still significantly higher than that in Enamine REAL Diverse, highlighting the constraints implied in combining building blocks to obtain Enamine REAL space.