Rationalizing the Formation of Activity Cliffs in Different Compound Data Sets

Activity cliffs are formed by structurally analogous compounds with large potency variations and are highly relevant for the exploration of discontinuous structure-activity relationships and compound optimization. So far, activity cliffs have mostly been studied on a case-by-case basis or assessed by global statistical analysis. Different from previous investigations, we report a large-scale analysis of activity cliff formation with a strong focus on individual compound activity classes (target sets). Compound potency distributions were systematically analyzed and categorized, and structural relationships were dissected and visualized on a per-set basis. Our study uncovered target set-dependent interplay of potency distributions and structural relationships and revealed the presence of activity cliffs and origins of cliff formation in different structure-activity relationship environments.