Application of a New Scaffold Concept for Computational Target Deconvolution of Chemical Cancer Cell Line Screens

Abstract

Target deconvolution of phenotypic assays is a hot topic in chemical biology and drug discovery. The ultimate goal is the identification of targets for compounds that produce interesting phenotypic readouts. A variety of experimental and computational strategies have been devised to aid this process. A widely applied computational approach infers putative targets of new active molecules on the basis of their chemical similarity to compounds with activity against known targets. Herein, we introduce a molecular scaffold-based variant for similarity-based target deconvolution from chemical cancer cell line screens that were used as a model system for phenotypic assays. A new scaffold type was used for substructure-based similarity assessment, termed analog series-based (ASB) scaffold. Compared with conventional scaffolds and compound-based similarity calculations, target assignment centered on ASB scaffolds resulting from screening hits and bioactive reference compounds restricted the number of target hypotheses in a meaningful way and lead to a significant enrichment of known cancer targets among candidates.