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                    BIOINFORMATICS COLLOQUIUM
               School of Computational Sciences
                    George Mason University
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       Multi-Scale Modeling of Calcium Signaling in the Cardiac Dyad

                        Dr. Raimond Winslow
        Professor, Department of Biomedical Engineering 
        The Johns Hopkins University School of Medicine


                 Tuesday, January 24, 2006
                             4:30 pm
           Verizon Auditorium, Prince William Campus
ABSTRACT 
In cardiac ventricular myocytes, events crucial to excitation-
contraction coupling take place in spatially restricted microdomains 
known as dyads. The movement and dynamics of calcium (Ca2+) ions in the 
dyad have often been described by assigning continuously valued Ca2+ 
concentrations to one or more dyadic compartments. However, even at its 
peak, the estimated number of free Ca2+ ions present in a single dyad 
is small (~ 10 ions). This in turn suggests that modeling dyadic 
calcium dynamics using laws of mass action may be inappropriate. To 
address this issue, we have developed a model of stochastic, local 
molecular signaling between L-type Ca2+ channels (LCCs) and ryanodine 
receptors (RyRs) that describes: a) known features of dyad geometry, 
including the space-filling properties of dyadic proteins; and b) 
movement of individual Ca2+ ions. We will show that this molecularly 
detailed model is able to reconstruct a broad range of experimental 
data on properties of excitation-contraction (EC) coupling including 
graded release and voltage-dependent EC coupling gain. We will also 
demonstrate that LCC-RyR signaling is influenced by the stochastic 
dynamics of Ca2+ ions in the dyad. Finally, we will present a new model 
of EC coupling consisting of a low dimensional system of ordinary 
differential equations in which all parameters may be derived 
analytically from those of the stochastic local control model and which 
captures fundamental EC coupling properties such as voltage-dependent 
graded Ca2+ release. The simplified model may be solved several orders 
of magnitude faster than can the stochastic model, thus enabling its 
incorporation into tissue level simulations.



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