University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Modeling 1-adrenergic receptor blockers and polymorphisms in cardiac myocytes

Modeling 1-adrenergic receptor blockers and polymorphisms in cardiac myocytes

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Mustapha Amrani.

The Cardiac Physiome Project

Modeling β1-adrenergic receptor blockers and polymorphisms in cardiac myocytes

Robert Amanfu, Ryan Connolly, Sean Meredith, and Jeff Saucerman

β-blockers are the one of the most effective medications for heart failure. But their success appears counterintuitive because they block the β1-adrenergic signaling pathway in cardiac myocytes, which enhances cardiac contractility. To evaluate mechanisms of β-blocker efficacy, we extended our cardiac myocyte β1-adrenergic signaling model using an extended ternary complex receptor model. This receptor model includes spontaneous switching between the active and inactive receptor conformations crucial for accurate representation of β-blockers and receptor polymorphisms. We determined parameters from the literature to model 11 agonists and 10 β-blockers and validated against a range of published experimental data. This new model predicts that at intermediate concentrations, β-blockers may protect the adrenergic pathway from chronic stress while paradoxically sensitizing the pathway to acute stress (like exercise). The Arg389 receptor polymorphism (prevalence ~50%) was predicted to constitutively stimulate calcium transients by 68%, which was restored to the activity of the wild type receptor by administration of 1 M β-blocker (propranolol). Model predictions are being validated experimentally. These simulations are a first step towards evaluating personalized β-blocker therapies with computational models.

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2021 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity