/* * Agonist-Dependent Phosphorylation Of The Inositol 1,4,5-Triphosphate * Receptor * * Model Structure * * The production of the intracellular signalling factor inositol * 1,4,5-triphosphate (IP3) and the subsequent release of Ca2+ * stored in intracellular organelles is a fundamental cellular * signalling function. The inositol triphosphate receptor (IPR) * is an IP3-activated Ca2+ channel in the ER. The properties of * IP3-dependent intracellular calcium oscillations in pancreatic * acinar cells depend on the agonist used to stimulate them. * * This agonist-dependency is captured in Andrew P. LeBeau et al's * 1999 mathematical model of agonist-specific intracellular calcium * oscillations in pancreatic acinar cells. They assume that the * complete IPR is composed of four functionally identical, independent * subunits, (see below). IP3 must be bound to all four subunits * for the receptor to be in the conducting state. * * The complete original paper reference is cited below: * * Agonist-dependent Phosphorylation of the Inositol 1,4,5-Triphosphate * Receptor. A Possible Mechanism for Agonist-specific Calcium * Oscillations in Pancreatic Acinar Cells, Andrew P. LeBeau, David * I. Yule, Guy E. Groblewski and James Sneyd, 1999, The Journal * Of General Physiology, 113, 851-871. PubMed ID: 10352035 * * The raw CellML description of the dynamic model of the type-2 * inositol triphosphate receptor can be downloaded in various * formats as described in . * * A simplified diagram of the IPR model * * [[Image file: lebeau_1999.png]] * * A diagram of the receptor states of the model of the IP3 receptor. * S denotes the fraction of the subunits in the shut state. Binding * of IP3 causes the receptor to be converted to the open state * O. O is a relatively unstable state and the subunits will progress * through to the more stable I1 (inactivated) state in which IP3 * is still bound but the channels do not conduct. I2 represents * a second inactivated state of the receptor in which IP3 is no * longer bound. */ import nsrunit; // Warning: unit conversion turned off due to unit errors in 7 equation(s) unit conversion off; // unit micromolar predefined unit flux=1E-3 meter^(-3)*second^(-1)*mole^1; unit first_order_rate_constant=1 second^(-1); unit second_order_rate_constant=1E3 meter^3*second^(-1)*mole^(-1); math main { //Warning: the following variables were set 'extern' or given // an initial value of '0' because the model would otherwise be // underdetermined: O, I1, I2, c realDomain time second; time.min=0; extern time.max; extern time.delta; real O(time) micromolar; //Warning: Assuming zero initial condition; nothing provided in original CellML model. when(time=time.min) O=0; real S(time) micromolar; real I1(time) micromolar; //Warning: Assuming zero initial condition; nothing provided in original CellML model. when(time=time.min) I1=0; real I2(time) dimensionless; //Warning: Assuming zero initial condition; nothing provided in original CellML model. when(time=time.min) I2=0; real p micromolar; p=3.0; real k1(time) first_order_rate_constant; real k1_ first_order_rate_constant; k1_=0.88; real k2 first_order_rate_constant; k2=0.5; real k3 first_order_rate_constant; k3=0.5; real k4 first_order_rate_constant; real k5 first_order_rate_constant; k5=0.02; real c(time) micromolar; //Warning: Assuming zero initial condition; nothing provided in original CellML model. when(time=time.min) c=0; real J_rel(time) flux; real J_pump(time) flux; real J_influx flux; J_influx=0.4; real V_p flux; V_p=2.6; real K_p micromolar; K_p=0.54; real k_flux flux; k_flux=28.0; real alpha_1 flux; alpha_1=40.0; real beta_1 micromolar; beta_1=0.8; real alpha_4 flux; alpha_4=0.06; real beta_4 micromolar; beta_4=0.01; // // O:time=(k1*p*S-(k1_*O+k2*O)); S=(4-(O+I1+I2)); // I1:time=(k2*O-(k3+k4)*I1); // I2:time=(k4*I1-k5*I2); // c:time=(J_rel-J_pump+J_influx); J_rel=(k_flux*O^4); J_pump=(V_p*c^2/(K_p^2+c^2)); // k1=(alpha_1*c^3/(beta_1^3+c^3)); k4=(alpha_4*p/(beta_4+p)); }