Scaffold Diversity Analysis of Compound Data Sets Using an Entropy‐Based Measure

Abstract Scaffold diversity analysis of compound databases has multiple applications in medicinal chemistry and drug discovery including library design, compounds acquisition, virtual screening and assessment of structure‐activity‐relationships. The scaffold diversity is commonly measured based on frequency counts. Further information can be obtained by considering the specific distribution of the molecules in those scaffolds. To this end, we introduce in this work the use of an entropy‐based information metric to assess the scaffold diversity of compound data sets. As a test case we analyzed the scaffold diversity of 16 data sets of active compounds comparable in size targeting five protein classes of interest in drug design. The diversity was also assessed in terms of frequency counts and scaffold retrieval curves. The entropy‐based information metric takes into account the frequency distribution of the different scaffolds and is a complementary measure of scaffold diversity enabling a more comprehensive analysis.