Identification of Bioactive Scaffolds Based on QSAR Models

In medicinal chemistry, the molecular scaffolds commonly found in compounds with preferable biological activities are called bioactive scaffolds. They are important because if present in a structure, it is more likely that the compound will be bioactive. Traditionally, medicinal chemists use their knowledge to identify bioactive scaffolds from a given data set after systematic extraction of all candidate scaffolds. However, manually sorting all the scaffolds is not practical as the number of compounds in a data set is often very large. Herein, we propose a method to systematically identify bioactive scaffolds based on a structure generator and a QSAR model. Two proof-of-concept studies showed that known bioactive scaffolds as well as scaffolds containing important substructures were extracted. The proposed method does not depend on scaffold frequencies in a data set, which is different from currently used methods for bioactive scaffold identification.