The Genom of Homo sapiens.pdf

INTEGRATIVE GENOMICS 441IMPLICATIONS FOR DRUG DISCOVERY:CHEMICAL GENETIC NETWORKSAn understanding of cellular networks provides an essentialfoundation for rational drug discovery. The fieldof chemical genetics rests on the premise that inactivationof a protein by a specific small-molecule ligand is equivalentto mutational inactivation of the corresponding gene(Mitchison 1994). The concept of synthetic lethality isreadily extended to small molecule–gene interactions,which may be used to selectively target genetic disorders,in particular, cancer (Hartwell et al. 1997). Indeed, proofof-conceptsynthetic lethal screens have identified compoundsthat selectively kill engineered cell lines with definedmutant genotypes (Simons et al. 2001; Torrance etal. 2001). Moreover, most successful therapeutics marketedto date have been discovered by screening for thedesired phenotypic effects rather than specific biochemicalactivities, such that off-target effects may often makecritical contributions to drug action through syntheticinteractions (Huang 2001). Mass-spectrometry-basedchemiproteomics approaches that directly identify proteintargets are beginning to reveal the scope of such effects(Graves et al. 2002). With the advent of genomeandproteome-wide data sets, it seems propitious to applycellular logic to the drug discovery process, using geneticand physical interaction networks as a guide (Sharom etal. 2004).CONCLUSION: PROSPECTS FOR HUMANFUNCTIONAL GENOMICSMany of the functional genomics first developed inyeast are readily extended to other organisms. The discoveryand application of RNA interference (RNAi) willenable synthetic genetic interactions to be systematicallyinvestigated in C. elegans, D. melanogaster, and mammaliantissue-culture cells (Grishok and Mello 2002; Kamathet al. 2003). Notably, if the density of digenic interactionsobserved for deletion alleles in yeast holds fornatural alleles in metazoan populations, including humans,the sheer number of genetic interactions underlyinga specific phenotype may compromise efforts to mapcomplex disease traits by SNP-based haplotype maps(Hartman et al. 2001; Tong et al. 2004). The use of physicaland biochemical pathway interaction information tofocus on relevant polymorphisms predicted to underliegenetic interactions may become an essential componentof efforts to map polygenic traits. A compelling case canbe made for systematic elucidation of genetic and proteininteraction networks in both model organisms and humancells.ACKNOWLEDGMENTSWe thank Don Gilbert and Rachel Drysdale for invaluableassistance in curating all genetic interactions fromFlyBase. B.A., C.B., and M.T are supported by grantsfrom the Canadian Institutes of Health Research, the NationalCancer Institute of Canada, and Genome Canada.REFERENCESAebersold R. and Mann M. 2003. Mass spectrometry-based proteomics.Nature 422: 198.Albert R., Jeong H., and Barabasi A.L. 2000. Error and attacktolerance of complex networks. Nature 406: 378.Bader G.D. and Hogue C.W. 2002. Analyzing yeast protein-proteininteraction data obtained from different sources. Nat.Biotechnol. 20: 991._______ . 2003. An automated method for finding molecular complexesin large protein interaction networks. BMC Bioinformatics4: 2.Bader G.D., Betel D., and Hogue C.W. 2003a. BIND: TheBiomolecular Interaction Network Database. 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