The central hypothesis underlying this research project is that molecular mechanisms exist for killing tumor cells selectively and that these mechanisms can be elucidated through the use of chemical genetic screens. In this chemical genetic approach, a high-throughput screen is used to select drugs that exert a desired phenotypic effect in a cellular assay. Subsequently, the molecular mechanisms by which these drugs exert their effects are determined. The primary technological barrier to widespread use of the chemical genetic approach is the difficulty of identifying the molecular basis of action of new drugs of unknown function. New strategies that allow for rapid identification of the molecular mechanism by which drugs exert their effects are of great value. This research project will result in the development of such a method and will result in the identification of molecular mechanisms that enable selective killing of engineered tumor cells. This project will result in the assembly and annotation of a chemical library of 5,000 drugs of known function using manual and automated Literature searching. These drugs will be tested for their ability to kill genetically defined tumor cells but not primary cell precursors to these tumor cells. Some of these tumor-selective killing agents will act by known molecular mechanisms and others will act by new, previously uncharacterized mechanisms. Using a variety of computational methods (neural networks, multiple linear regression, decision trees, self organizing maps, and genetic algorithms), we will demonstrate that functional annotation of chemical libraries makes it possible to identify specific molecular mechanisms that underlie cellular phenotypes, such as selective, apoptotic death in engineered tumor cells. The recent discovery of Gleevec (STI-571), a BCR-ABL kinase inhibitor that selectively kills BCR-ABL transformed cells, illustrates the clinical value of tumor-selective cytotoxic agents. New compounds that selectively kill tumor cells may be candidates for development as anticancer drugs or they may serve to illuminate novel drug targets for anticancer drug development.
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