Neighborhood behavior. Fuzzy molecular descriptors and their influence on the relationship between structural similarity and property similarity

The similarity principle, stating that molecules of similar structure behave similarly, is an important concept in medicinal chemistry. A properly characterized and well understood neighborhood behavior of the structural space versus the activity space is fundamental for the application of the similarity principle in computational chemistry. In this work we focus on the utilization of a fuzzy pharmacophore description of molecular similarity and specifically on the influence of fuzzy pharmacophore pattern matching on the neighborhood behavior (NB) of the similarity scoring scheme. NB is defined as a structure activity relationship between the intermolecular distances/ dissimilarities in the pharmacophore fingerprint structure space and the corresponding activity differences, formally seen as intermolecular distances in the activity spaces. The latter are defined on hand of a wide variety of datasets on pharmacological and physico-chemical properties and property profiles. We also investigate the clustering behavior (CB), where the structure-activity relationship is described in terms of distance-derived associations of compounds into clusters via classical hierarchical clustering procedures. The neighborhood behavior and the cluster behavior provide alternative and complementary criteria for evaluating the pertinence of a molecular similarity metric.