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Discovering target and off-target effects of specific compounds is critical to drug discovery and development. We generated a compendium of "chemical-genetic interaction" profiles by testing the collection of viable yeast haploid deletion mutants for hypersensitivity to 82 compounds and natural product extracts. To cluster compounds with a similar mode-of-action and to reveal insights into the cellular pathways and proteins affected, we applied both a hierarchical clustering and a factorgram method, which allows a gene or compound to be associated with more than one group. In particular, tamoxifen, a breast cancer therapeutic, was found to disrupt calcium homeostasis and phosphatidylserine (PS) was recognized as a target for papuamide B, a cytotoxic lipopeptide with anti-HIV activity. Further, the profile of crude extracts resembled that of its constituent purified natural product, enabling detailed classification of extract activity prior to purification. This compendium should serve as a valuable key for interpreting cellular effects of novel compounds with similar activities.

Bioactive compounds can be valuable research tools and drug leads, but it is often difficult to identify their mechanism of action or cellular target. Here we investigate the potential for integration of chemical-genetic and genetic interaction data to reveal information about the pathways and targets of inhibitory compounds. Taking advantage of the existing complete set of yeast haploid deletion mutants, we generated drug-hypersensitivity (chemical-genetic) profiles for 12 compounds. In addition to a set of compound-specific interactions, the chemical-genetic profiles identified a large group of genes required for multidrug resistance. In particular, yeast mutants lacking a functional vacuolar H(+)-ATPase show multidrug sensitivity, a phenomenon that may be conserved in mammalian cells. By filtering chemical-genetic profiles for the multidrug-resistant genes and then clustering the compound-specific profiles with a compendium of large-scale genetic interaction profiles, we were able to identify target pathways or proteins. This method thus provides a powerful means for inferring mechanism of action.