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

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.