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  • 1
    Publication Date: 1999-07-27
    Description: Genetic selections were used to find peptides that inhibit biological pathways in budding yeast. The peptides were presented inside cells as peptamers, surface loops on a highly expressed and biologically inert carrier protein, a catalytically inactive derivative of staphylococcal nuclease. Peptamers that inhibited the pheromone signaling pathway, transcriptional silencing, and the spindle checkpoint were isolated. Putative targets for the inhibitors were identified by a combination of two-hybrid analysis and genetic dissection of the target pathways. This analysis identified Ydr517w as a component of the spindle checkpoint and reinforced earlier indications that Ste50 has both positive and negative roles in pheromone signaling. Analysis of transcript arrays showed that the peptamers were highly specific in their effects, which suggests that they may be useful reagents in organisms that lack sophisticated genetics as well as for identifying components of existing biological pathways that are potential targets for drug discovery.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Norman, T C -- Smith, D L -- Sorger, P K -- Drees, B L -- O'Rourke, S M -- Hughes, T R -- Roberts, C J -- Friend, S H -- Fields, S -- Murray, A W -- P41-RR11823/RR/NCRR NIH HHS/ -- New York, N.Y. -- Science. 1999 Jul 23;285(5427):591-5.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Physiology, University of California, San Francisco, CA 94143-0444, USA. tnorman@microbia.com〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/10417390" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Sequence ; Calcium-Calmodulin-Dependent Protein Kinases/metabolism ; Fungal Proteins/metabolism ; G1 Phase ; Galactose/metabolism ; Lipoproteins/metabolism ; Micrococcal Nuclease ; Mitosis ; Molecular Sequence Data ; Peptide Library ; Peptides/genetics/metabolism/*pharmacology ; Pheromones/*metabolism ; Protein Binding ; Protein-Serine-Threonine Kinases ; Protein-Tyrosine Kinases ; Saccharomyces cerevisiae/cytology/genetics/*metabolism ; *Saccharomyces cerevisiae Proteins ; *Selection, Genetic ; *Signal Transduction ; Spindle Apparatus/drug effects/*metabolism ; Transcription, Genetic
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 1997-11-14
    Description: The discovery of anticancer drugs is now driven by the numerous molecular alterations identified in tumor cells over the past decade. To exploit these alterations, it is necessary to understand how they define a molecular context that allows increased sensitivity to particular compounds. Traditional genetic approaches together with the new wealth of genomic information for both human and model organisms open up strategies by which drugs can be profiled for their ability to selectively kill cells in a molecular context that matches those found in tumors. Similarly, it may be possible to identify and validate new targets for drugs that would selectively kill tumor cells with a particular molecular context. This article outlines some of the ways that yeast genetics can be used to streamline anticancer drug discovery.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Hartwell, L H -- Szankasi, P -- Roberts, C J -- Murray, A W -- Friend, S H -- N01-BC65017/BC/NCI NIH HHS/ -- New York, N.Y. -- Science. 1997 Nov 7;278(5340):1064-8.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Seattle Project, Molecular Pharmacology Department, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/9353181" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; *Antineoplastic Agents/pharmacology/therapeutic use ; *Drug Design ; *Drug Screening Assays, Antitumor ; Humans ; Mutation ; Neoplasms/*drug therapy/genetics ; Signal Transduction ; Yeasts/genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 1997-01-17
    Description: Since 1990, the National Cancer Institute (NCI) has screened more than 60,000 compounds against a panel of 60 human cancer cell lines. The 50-percent growth-inhibitory concentration (GI50) for any single cell line is simply an index of cytotoxicity or cytostasis, but the patterns of 60 such GI50 values encode unexpectedly rich, detailed information on mechanisms of drug action and drug resistance. Each compound's pattern is like a fingerprint, essentially unique among the many billions of distinguishable possibilities. These activity patterns are being used in conjunction with molecular structural features of the tested agents to explore the NCI's database of more than 460,000 compounds, and they are providing insight into potential target molecules and modulators of activity in the 60 cell lines. For example, the information is being used to search for candidate anticancer drugs that are not dependent on intact p53 suppressor gene function for their activity. It remains to be seen how effective this information-intensive strategy will be at generating new clinically active agents.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Weinstein, J N -- Myers, T G -- O'Connor, P M -- Friend, S H -- Fornace, A J Jr -- Kohn, K W -- Fojo, T -- Bates, S E -- Rubinstein, L V -- Anderson, N L -- Buolamwini, J K -- van Osdol, W W -- Monks, A P -- Scudiero, D A -- Sausville, E A -- Zaharevitz, D W -- Bunow, B -- Viswanadhan, V N -- Johnson, G S -- Wittes, R E -- Paull, K D -- New York, N.Y. -- Science. 1997 Jan 17;275(5298):343-9.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Laboratory of Molecular Pharmacology (LMP), Division of Basic Science, National Cancer Institute (NCI), National Institutes of Health, Bethesda, MD 20892, USA. weinstein@dtpax2.ncifcrf.gov〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/8994024" target="_blank"〉PubMed〈/a〉
    Keywords: Algorithms ; Antineoplastic Agents/chemistry/*pharmacology ; Cluster Analysis ; *Computational Biology ; Computer Communication Networks ; *Databases, Factual ; *Drug Screening Assays, Antitumor ; Genes, p53 ; Humans ; Molecular Structure ; Mutation ; Software ; Tumor Cells, Cultured ; Tumor Suppressor Protein p53/physiology
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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