Model Organisms in Drug Discovery

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WEB-ACCESSIBLE DATABASES: BRINGING IT ALL BACK HOME 31 purification, although one report on the 40s ribosomal subunit directly analyzed complexes physically separated by other means (Link et al., 1999). Honey et al. reported the use of TAP and mass spectrometry to characterize components of the active yeast CDK complex tagged on its cyclin subunit (Honey et al., 2001). More recently two commercial entities reported far larger scale projects: Cellzome’s work included 1143 yeast orthologs of relevance to human biology (Gavin et al., 2002), whereas MDS Proteomics tagged 725 proteins, including a large number implicated in DNA damage responses (Ho et al., 2002). These commercial projects represent pilots for mammalian work, as well as providing a large body of data for many yeast proteins that have mammalian homologs. Biochemical analysis A surprising pursuit, in this day and age, is to click around the links in various metabolic pathway websites and to discover how many of the described biochemical activities do not have a yeast gene linked to them. To eliminate the onerous task of purifying such activities to identify the responsible protein, Martzen et al. (1999) created expression constructs for all yeast ORFs in which the yeast protein was fused to glutathione-s-transferase (GST). These GST-fusion proteins can be purified and screened for enhancement of a particular activity; they are also a useful resource for hypothesis testing with cross-linkable ligands. As a further refinement, Zhu et al. report attachment of such tagged yeast proteins to microarrays and their screening for kinase activity (Zhu et al., 2000) and for affinity to calmodulin and phospholipids (Zhu et al., 2001). It is easy to conceive of future use of such arrays to identify molecular targets for labeled compounds. Localization data In addition to the most complete protein interaction data resources, yeast has a large volume of information on subcellular protein localization. Greatly extending data provided by individual studies and by an earlier large-scale project (Ross- Macdonald et al., 1999), Kumar et al. conducted a genome-wide epitope-tagging and immunocytochemistry project resulting in annotation of nearly half the proteins in yeast to one of six subcellular localization sites (Kumar et al., 2002a,b). 2.13 Web-accessible databases: bringing it all back home . Saccharomyces Genome Database: http://genome-www.stanford.edu/ Saccharomyces/
32 GROWING YEAST FOR FUN AND PROFIT . Comprehensive Yeast Genome Database: http://mips.gsf.de/proj/yeast/ CYGD/db/index.html The community of yeast researchers numbers in the tens of thousands and, coupled with the tools described above, the capacity to generate ‘omic’ scale information is almost overwhelming (Zhu and Snyder, 2002). In addition, the ability to measure and modulate so many parameters in yeast means that it is a natural test bed for systems biology (Ideker et al., 2001). Gene-centric information for yeast is compiled into several databases that have made commendable efforts to cross-reference each other. Principal among these are the Saccharomyces Genome Database (SGD) based at Stanford, USA (Dwight et al., 2002), the Comprehensive Yeast Genome Database (CYGD) at MIPS-GSF (Germany) (Mewes et al., 2000) and Incyte’s YPD (Costanzo et al., 2001). The latter is a commercial subscription database historically provided free to academic researchers and has served as a template for Incyte’s Human-PSD and GPCR-PSD databases. Many other databases exist to collate specialized information in greater detail; these are indexed off the sources listed above. 2.14 Conclusion Analysis of the genomic sequences of both humans and yeast has led to a renewed appreciation of the shared biology of these long-separated eukaryotes. Although the understanding of this relationship is broader in the academic community, this review illustrates the wide range of uses that yeast has served in the pharmaceutical industry. As the technologies available become more powerful every year, it is to be hoped that we do not lose our appreciation of the insight that this small organism can continue to provide. 2.15 References Arkinstall, S., Payton, M. and Maundrell, K. (1995). Activation of phospholipase C gamma in Schizosaccharomyces pombe by coexpression of receptor or nonreceptor tyrosine kinases. Mol. Cell. Biol. 15, 1431–1438. Arkinstall, S., Gillieron, C., Vial-Knecht, E. and Maundrell, K. (1998). A negative regulatory function for the protein tyrosine phosphatase PTP2C revealed by reconstruction of platelet-derived growth factor receptor signalling in Schizosaccharomyces pombe. FEBS Lett. 422, 321–327. Barth, H. and Thumm, M. (2001). A genomic screen identifies AUT8 as a novel gene essential for autophagy in the yeast Saccharomyces cerevisiae. Gene 274, 151–156. Bassett, D. E., Jr., Boguski, M. S. and Hieter, P. (1996). Yeast genes and human disease. Nature 379, 589–590.
Page 1 and 2: Model Organisms in Drug Discovery M
Page 3 and 4: Copyright u 2003 John Wiley & Sons
Page 5 and 6: Contents List of contributors .....
Page 7 and 8: CONTENTS ix 7 Genetics and Genomics
Page 9 and 10: List of Contributors Hector Beltran
Page 11 and 12: LIST OF CONTRIBUTORS xiii Stefan Sc
Page 13 and 14: 1 Introduction to Model Systems in
Page 15 and 16: Organism INTEGRATING MODEL ORGANISM
Page 17 and 18: INTEGRATING MODEL ORGANISM RESEARCH
Page 19 and 20: INTEGRATING MODEL ORGANISM RESEARCH
Page 21 and 22: 10 GROWING YEAST FOR FUN AND PROFIT
Page 41: 30 GROWING YEAST FOR FUN AND PROFIT
Page 51 and 52: 3 Caenorhabditis elegans Functional
Page 53 and 54: THE DRUG DISCOVERY PROCESS 43 thoug
Page 55 and 56: multivulva phenotype of Ras gain-of
Page 57 and 58: disease. These molecular targets ar
Page 59 and 60: FROM DISEASE TO TARGET 49 Figure 3.
Page 61 and 62: FROM DISEASE TO TARGET 51 Figure 3.
Page 63 and 64: signaling pathway. The third catego
Page 65 and 66: FROM DISEASE TO TARGET 55 resistant
Page 67 and 68: phenomenon was first observed in C.
Page 69 and 70: profiles. The C. elegans gene expre
Page 71 and 72: emerging technologies. Forward gene
Page 73 and 74: The compound library LEAD DISCOVERY
Page 75 and 76: LEAD DISCOVERY 65 previous section,
Page 77 and 78: LEAD DISCOVERY 67 Figure 3.5 Distri
Page 79 and 80: Compound learning set for assay val
Page 81 and 82: 10 000-15 000 human drug targets ar
Page 83 and 84: transporter itself. The SSRIs that
Page 85 and 86: REFERENCES 75 de Montigny, C., Blie
Page 87 and 88: REFERENCES 77 Lewis, J. A., Wu, C.
Page 89 and 90: REFERENCES 79 Tissenbaum, H. A. and
Page 91 and 92: 82 DROSOPHILA AS A TOOL FOR DRUG DI
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84 DROSOPHILA AS A TOOL FOR DRUG DI
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100 DROSOPHILA AS A TOOL FOR DRUG D
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5 Drosophila - a Model System for T
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EVOLUTIONARY CONSERVATION OF DISEAS
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TARGET IDENTIFICATION/TARGET VALIDA
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CHEMICAL GENETICS 143 acid identity
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3. A hit identifies a biologically
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about their function in a multicell
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REFERENCES 149 Han, Z. S., Enslen,
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REFERENCES 151 Rintelen, F., Stocke
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6 Mechanism of Action in Model Orga
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INTRODUCTION TO COMPOUND DEVELOPMEN
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MODEL ORGANISMS ARRIVE ON THE SCENE
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ELUCIDATING THE MECHANISM OF COMPOU
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ELUCIDATING THE MECHANISM OF COMPOU
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A CASE STUDY FOR ALZHEIMER’S DISE
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NEW CHEMICAL GENETIC STRATEGIES 171
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A CASE STUDY FOR INNATE IMMUNITY 17
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GLOBAL GENE EXPRESSION STUDIES IN M
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As described above, the extensive i
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REFERENCES 179 Austin, J. and Kimbl
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REFERENCES 181 Hughes, T. R., Marto
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REFERENCES 183 Sin, N., Meng, L., W
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186 GENETICS AND GENOMICS IN THE ZE
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8 Lipid Metabolism and Signaling in
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FISH AS A MODEL ORGANISM 205 genes
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LIPID METABOLISM SCREEN 207 transpo
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LIPID METABOLISM SCREEN 209 Figure
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the embryo media containing radioac
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ZEBRAFISH AS A MODEL SYSTEM 213 Fig
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ZEBRAFISH AS A MODEL SYSTEM 215 Reg
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aspirin, which has potent inhibitor
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REFERENCES 219 Chau, I. and Cunning
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REFERENCES 221 Patrono, C., Patrign
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224 CHEMICAL MUTAGENESIS IN THE MOU
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252 SATURATION SCREENING OF DRUGGAB
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280 INDEX bupropion 92 busulfan 143
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282 INDEX Dscam 171 dual-energy X-r
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284 INDEX L-685,818 16 lead discove
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286 INDEX protein function 19-22 pr
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288 INDEX yeast (continued) functio
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