ORIGINAL ARTICLESIdentification of drug targets by chemogenomic and metabolomic profiling in yeastWu, Manhonga; Zheng, Minga; Zhang, Weiruob; Suresh, Sundaric; Schlecht, Ulrichc; Fitch, William L.a; Aronova, Sofiad; Baumann, Stephand; Davis, Ronaldc; St.Onge, Robertc; Dill, David L.b; Peltz, GaryaAuthor Information aDepartment of Anesthesia, Stanford University School of Medicine bDepartment of Computer Science, Stanford University School of Engineering cDepartment of Biochemistry and Stanford Genome Technology Center, Stanford University, Stanford dAgilent Technologies Inc., Santa Clara, California, USA Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (www.pharmacogeneticsandgenomics.com). Correspondence to Gary Peltz, MD, PhD, Department of Anesthesia, Stanford University School of Medicine, Stanford University, 300 Pasteur Drive L232, Stanford, CA 94305, USA Tel: +1 650 721 2487; fax: +1 650 721 2420; e-mail: [email protected] Received May 15, 2012 Accepted September 22, 2012 Pharmacogenetics and Genomics: December 2012 - Volume 22 - Issue 12 - p 877-886 doi: 10.1097/FPC.0b013e32835aa888 Buy SDC Metrics Abstract Objective To advance our understanding of disease biology, the characterization of the molecular target for clinically proven or new drugs is very important. Because of its simplicity and the availability of strains with individual deletions in all of its genes, chemogenomic profiling in yeast has been used to identify drug targets. As measurement of drug-induced changes in cellular metabolites can yield considerable information about the effects of a drug, we investigated whether combining chemogenomic and metabolomic profiling in yeast could improve the characterization of drug targets. Basic methods We used chemogenomic and metabolomic profiling in yeast to characterize the target for five drugs acting on two biologically important pathways. A novel computational method that uses a curated metabolic network was also developed, and it was used to identify the genes that are likely to be responsible for the metabolomic differences found. Results and conclusion The combination of metabolomic and chemogenomic profiling, along with data analyses carried out using a novel computational method, could robustly identify the enzymes targeted by five drugs. Moreover, this novel computational method has the potential to identify genes that are causative of metabolomic differences or drug targets. © 2012 Lippincott Williams & Wilkins, Inc.