Fragment Library Dataset. A large set of fragment-like molecules were selected from ChEMBL32 applying the following criteria to desalted, neutral molecules: i. MW 100-300 g/mol, ii. LogP ≤ 3, iii. HBD ≤ 3, iv. HBA ≤ 6, v. Rotatable Bond Count ≤ 5 and vi. Heavy Atom Count 10-20. KNIME was used to perform the filtering and data processing. Bemis-Murcko scaffolds were calculated for the resulting 202,704 molecules and used to class the molecules within respective (Bemis-Murcko) scaffold families. Ten exemplar scaffold families were subsequently selected -containing either 10 to 15 fragment molecules or fewer than 5 fragment moleculesfor use in the fragment library progressibility assessment presented in this work. Our final dataset consists of 110 molecules in total; the 10 Bemis-Murcko scaffolds are used as model screening fragment molecules. We performed the EVP analysis on this virtual library to assess the progressibility of the 10 model screening fragments. A random, larger subset of 2000 scaffolds was used for the analysis presented in Figure .