Computational method for the identification of third generation activity cliffs

摘要

In medicinal chemistry and chemoinformatics, activity cliffs (ACs) are defined as pairs of structurally similar compounds that are active against the same target but have a large difference in potency. Accordingly, ACs are rich in structure-activity relationship (SAR) information, which rationalizes their relevance for medicinal chemistry. For identifying ACs, a compound similarity criterion and a potency difference criterion must be specified. So far a constant potency difference between AC partner compounds has mostly been set, e.g. 100-fold, irrespective of the specific activity (targets) of cliff-forming compounds. Herein, we introduce a computational methodology for AC identification and analysis that includes three novel components: