Structure−Activity Relationship Anatomy by Network-like Similarity Graphs and Local Structure−Activity Relationship Indices

Abstract

The study of structure-activity relationships (SARs) of small molecules is of fundamental importance in medicinal chemistry and drug design. Here, we introduce an approach that combines the analysis of similarity-based molecular networks and SAR index distributions to identify multiple SAR components present within sets of active compounds. Different compound classes produce molecular networks of distinct topology. Subsets of compounds related by different local SARs are often organized in small communities in networks annotated with potency information. Many local SAR communities are not isolated but connected by chemical bridges, i.e., similar molecules occurring in different local SAR contexts. The analysis makes it possible to relate local and global SAR features to each other and identify key compounds that are major determinants of SAR characteristics. In many instances, such compounds represent start and end points of chemical optimization pathways and aid in the selection of other candidates from their communities.