[No authors listed]
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.
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DCC1, HCM1, TUB2, UBP6, BRE2, CSF1, ARV1, YPT6, FKS1, VAC14, VMA6, DRS2, PMT2, CLB3, BRE1, RPN4, RGP1, SUM1, MCM21, SLA1, GRS1, VMA2, BEM1, SSH1, GET1, VMA7, CAX4, VMA21, CHO2, SMI1, MNN11, MAD2, MAD3, OPI3, CNB1, SAC1, VPH2, VMA5, ELM1, VPS24, VPS1, DYN1, GYP1, RIM20, VMA4, CIN1, GIM5, VAN1, UBX2, UBC7, CIN4, CIK1, CUE1, SCS7, JNM1, DYN3, GAS1, KRE1, KEX2, PDR16, CIN2, VMA11, DAP1, BTS1, YPR089W, ERG11, VPS29, VMA16, SLT2, VMA10, YHR045W, VMA22, NPR2, SPF1, VMA3, GIM4, PAC2, BUD25, YPT31, GET2, BEM2
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