In this project, we will develop a new computational modeling framework capable of designing targeted molecular therapies for heart failure. Impairment of cardiac muscle function constitutes a major clinical problem and comes in many forms. For example, sarcomere-level contraction is depressed in many of the 3 million Americans who have Heart Failure with reduced Ejection Fraction (HFrEF). The opposite issue, excessive activity of muscle proteins, can contribute to Heart Failure with preserved Ejection Fraction (HFpEF) by slowing relaxation and stiffening the ventricle. Genetic mutations to sarcomeric proteins afflict another 700,000 Americans. Gain of function mutations typically produce cardiac hypertrophy while loss of molecular function results in dilated cardiomyopathy. Patients and physicians urgently need better therapies for these conditions but the clinical trials used to test potential new strategies cost ~$1 billion and are plagued by high failure rates. This project tests the hypothesis that computer modeling can help to overcome these challenges by efficiently predicting the therapeutic potential of novel drug targets in the context of each different form of heart failure. The ultimate goal would be to screen a wide range of molecular strategies in silico and then select the most promising options for animal experiments and/or clinical trials. In the long term, it might even be possible to implement patient-specific computer modeling to help optimize treatment plans. The more immediate impacts would include reducing costs and focusing trials on the most effective molecular targets. The first step is to establish the feasibility of a modeling-driven pipeline using murine models of heart failure (HF) and a single molecular target. Recent studies show that sarcomere-focused treatments for HF have significant promise and that myosin-binding protein-C (MyBPC) could be a particularly effective target. This is because MyBPC can both enhance and inhibit contractility with the net regulatory effect depending on the phosphorylation status of three known residues. Phospho-variants of MyBPC could therefore be engineered to increase or decrease cardiac contractility as desired. In our view, the main roadblock hindering MyBPC's development as a potential new therapy is incomplete understanding of the molecule's mechanistic action. Specifically, it is not yet known precisely how the phosphorylation status of each residue modulates MyBPC's ability to enhance function (by activating the thin filament) and depress function (by restricting the mobility of detached myosin heads). The goals of this project are therefore to (1) develop a modeling framework that establishes how site-specific MyBPC phosphorylation impacts contractile function, (2) validate the model using sarcomere to animal-level experiments, and (3) test the pipeline's ability to predict effective therapeutic strategies by combining in silico screening and viral delivery of computer-selected mutant MyBPC.
Heart failure is major public health burden with no effective therapies. Poor contractile function is a major factor in the development and progression of this disease. This project will develop new computational models in order to test new therapies for heart failure. Expertise in computer modeling and cardiac muscle biology will be used to gain a better understanding of how cardiac muscle function can be manipulated to improve pump function in heart failure. Our computer models will be tested in animal models of human cardiac disease as a first step towards development of treatments for human heart failure patients.
