Proteome Mining as a Predicitve Tool of Drug Toxicity

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DESCRIPTION (provided by applicant): In this proposal we will utilize a unique blend of chemoproteomics, metabolomics and informatics to develop a highly predictive assay of drug toxicity at the earliest stages of the discovery process. In achieving this goal we will specifically reduce lead attrition rates that often occur in later more expensive stages of drug development. Traditional approaches to drug discovery begin with high throughput screens of small molecule libraries against single enzyme/receptor target or disease cell line. Importantly, neither assay can predict interactions with other off target proteins that invariable manifest themselves as toxicities and adverse reactions in later more expensive stages of the drug development process, in particular, in animal and human studies. Our technology called proteome mining, enables a targeted proteome containing many hundreds of potential drugs targets (includes therapeutic and toxicity targets) to be quantitatively captured in reversible affinity arrays and screened en masse against drug like molecules. Knowledge derived from this screen can be used to identify all off target liabilities and used to drive iterative chemistry to improve potency and selectivity simultaneously. As a proof of concept we will target the purine utilizing proteome. Purine utilizing enzymes are the most frequently expressed enzymes in the human genome and contain both classical drug targets (e.g. dihydrofolate reductase and HMG CoA reductase) as well as cutting edge targets (protein kinases and stress induced proteins). Importantly, inspection of the current OMIM database reveals that purine utilizing enzymes potentially also represent a significant proportion of the drug toxicity genome, with over 1500 distinct enzymes being identified with associations with inborn errors in metabolism. To validate our technology we will examine the selectivity profiles of several established drugs and their metabolites exhibiting well characterized side effects in animals and humans. Directed metabolomic profiling using state of the art techniques in mass spectrometry will be used to verify that potential toxicity targets identified in proteome mining are indeed inhibited in vivo.