# Computer modeling of myosin binding protein C and its effects on cardiac contraction

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2020 · $551,216

## Abstract

PROJECT ABSTRACT
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 ...

## Key facts

- **NIH application ID:** 9903433
- **Project number:** 5R01HL146676-02
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** STUART G CAMPBELL
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $551,216
- **Award type:** 5
- **Project period:** 2019-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9903433

## Citation

> US National Institutes of Health, RePORTER application 9903433, Computer modeling of myosin binding protein C and its effects on cardiac contraction (5R01HL146676-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9903433. Licensed CC0.

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