Virtual drug screen reveals context-dependent inhibition of cardiomyocyte hypertrophy

建议文摘

Proposal Abstract Heart failure is a leading cause of death worldwide. Cardiomyocyte hypertrophy is a leading predictor of heart failure as it contributes to maladaptive remodeling of the heart. Hypertrophy is therefore a good therapeutic target for preventing the onset of heart failure. Hypertrophy is mediated by complex intracellular signaling, which limits our ability to effectively model drug activity in cardiomyocytes. Currently there are no therapeutics that specifically target the intracellular signaling of cardiomyocyte hypertrophy. Previous work by the Saucerman lab has utilized computational models of signaling networks to simulate cardiomyocyte behavior in the context of hypertrophy. These simulations allow us to explore how drugs may inhibit cardiomyocyte hypertrophy using a systems biology approach. Identifying drugs that target cardiomyocyte hypertrophy would allow for translational application. The central focus of this grant is to identify drugs that inhibit cardiomyocyte hypertrophy and the mechanisms by which they act. Aim 1 will use a computational model of cardiomyocyte hypertrophy signaling to screen FDA approved drugs that inhibit hypertrophy and validate these predictions experimentally. Aim 2 will use protein interaction data to identify the mechanisms of putative antihypertrophic drugs from a separate in vitro drug screen. These aims together will result in the selection and testing of drugs repurposed for the inhibition of cardiomyocyte hypertrophy, and will lay the platform for designing virtual drug screens for heart disease.