Figures
Using mathematical models to design better anti-arrhythmic drugs.
Many cardiac drugs fail because they exhibit reverse rate dependence, prolonging ventricular action potentials at slow heart rates, where this is pro-arrhythmic, while failing to prolong action potentials at fast heart rates. The colored squares in the image show predictions that were obtained by testing the effects of multiple ion channel perturbations in multiple mathematical models. Through this analysis we identified perturbations that act with forward rate dependence, prolonging the cardiac action potential at fast heart rates (top traces) but not at slow rates (bottom traces). See Cummins et al.
Image Credit: Megan Cummins, Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai
Citation: (2014) PLoS Computational Biology Issue Image | Vol. 10(3) March 2014. PLoS Comput Biol 10(3): ev10.i03. https://doi.org/10.1371/image.pcbi.v10.i03
Published: March 27, 2014
Copyright: © 2014 Cummins et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Many cardiac drugs fail because they exhibit reverse rate dependence, prolonging ventricular action potentials at slow heart rates, where this is pro-arrhythmic, while failing to prolong action potentials at fast heart rates. The colored squares in the image show predictions that were obtained by testing the effects of multiple ion channel perturbations in multiple mathematical models. Through this analysis we identified perturbations that act with forward rate dependence, prolonging the cardiac action potential at fast heart rates (top traces) but not at slow rates (bottom traces). See Cummins et al.
Image Credit: Megan Cummins, Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai