/* * Vascular and perivascular nitric oxide release and transport: * biochemical pathways of neuronal nitric oxide synthase (NOS1) * and endothelial nitric oxide synthase (NOS3) * * Model Status * * This CellML model runs in OpenCell and COR and is known to be * mathematically consistent with the publication it was based * on. The units are consistent. An additional variable and equation * has been added to allow the CellML model to reproduce Figure * 2 of the publication. The three different graphs of this figure * can be produced by altering the variable 'Fe3' in the 'Fe3' * component (this variable represents the concentration of NOS-1 * in its Fe3+ bound state) to 0.3, 0.6 or 0.9 micromolar. In this * particular version of the model it has been set to 0.9. * * Model Structure * * ABSTRACT: Nitric oxide (NO) derived from nitric oxide synthase * (NOS) is an important paracrine effector that maintains vascular * tone. The release of NO mediated by NOS isozymes under various * O(2) conditions critically determines the NO bioavailability * in tissues. Because of experimental difficulties, there has * been no direct information on how enzymatic NO production and * distribution change around arterioles under various oxygen conditions. * In this study, we used computational models based on the analysis * of biochemical pathways of enzymatic NO synthesis and the availability * of NOS isozymes to quantify the NO production by neuronal NOS * (NOS1) and endothelial NOS (NOS3). We compared the catalytic * activities of NOS1 and NOS3 and their sensitivities to the concentration * of substrate O(2). Based on the NO release rates predicted from * kinetic models, the geometric distribution of NO sources, and * mass balance analysis, we predicted the NO concentration profiles * around an arteriole under various O(2) conditions. The results * indicated that NOS1-catalyzed NO production was significantly * more sensitive to ambient O(2) concentration than that catalyzed * by NOS3. Also, the high sensitivity of NOS1 catalytic activity * to O(2) was associated with significantly reduced NO production * and therefore NO concentrations, upon hypoxia. Moreover, the * major source determining the distribution of NO was NOS1, which * was abundantly expressed in the nerve fibers and mast cells * close to arterioles, rather than NOS3, which was expressed in * the endothelium. Finally, the perivascular NO concentration * predicted by the models under conditions of normoxia was paradoxically * at least an order of magnitude lower than a number of experimental * measurements, suggesting a higher abundance of NOS1 or NOS3 * and/or the existence of other enzymatic or nonenzymatic sources * of NO in the microvasculature. * * model diagram * * [[Image file: chen_2007.png]] * * Schematic diagram of the mathematical model. Pathway of NO release * and transport catalysed by neuronal nitric oxide synthase ((NOS1), * here represented by the heme iron (Fe)). The heme ion of NOS1 * binds L-arginine (Arg), hydroxyl-L-arginine (NOHA), and oxygen * (O2), and undergoes a series of oxygenation and reduction reactions. * * The original paper reference is cited below: * * Vascular and perivascular nitric oxide release and transport: * biochemical pathways of neuronal nitric oxide synthase (NOS1) * and endothelial nitric oxide synthase (NOS3), Kejing Chen and * Aleksander S. Popel, 2007,Free Radical Biology and Medicine, * 42, 811-822. PubMed ID: 17320763 */ import nsrunit; unit conversion on; // unit micromolar predefined unit first_order_rate_constant=1 second^(-1); unit second_order_rate_constant=1E3 meter^3*second^(-1)*mole^(-1); unit flux=1E-3 meter^(-3)*second^(-1)*mole^1; math main { realDomain time second; time.min=0; extern time.max; extern time.delta; real Fe3(time) micromolar; when(time=time.min) Fe3=0.9; real Arg micromolar; Arg=100.0; real Fe3_Arg(time) micromolar; when(time=time.min) Fe3_Arg=0.0; real Fe3_NO(time) micromolar; when(time=time.min) Fe3_NO=0.0; real Fe2_NO(time) micromolar; when(time=time.min) Fe2_NO=0.0; real O2 micromolar; O2=100.0; real k1 second_order_rate_constant; k1=6.6; real k_1 first_order_rate_constant; k_1=6.6; real k2 first_order_rate_constant; k2=20.8; real k13 first_order_rate_constant; k13=39.9; real k12 second_order_rate_constant; k12=0.01; real k3 first_order_rate_constant; k3=20.8; real Fe2(time) micromolar; when(time=time.min) Fe2=0.0; real Fe2_Arg(time) micromolar; when(time=time.min) Fe2_Arg=0.0; real k_4 first_order_rate_constant; k_4=6.6; real k4 second_order_rate_constant; k4=6.6; real Fe3_O2_Arg(time) micromolar; when(time=time.min) Fe3_O2_Arg=0.0; real k5 second_order_rate_constant; k5=8.5; real k_5 first_order_rate_constant; k_5=215.6; real k6 first_order_rate_constant; k6=175.6; real Fe3_NOHA(time) micromolar; when(time=time.min) Fe3_NOHA=0.0; real k7 first_order_rate_constant; k7=20.8; real Fe2_NOHA(time) micromolar; when(time=time.min) Fe2_NOHA=0.0; real NOHA(time) micromolar; when(time=time.min) NOHA=0.0; real Fe3_O2_NOHA(time) micromolar; when(time=time.min) Fe3_O2_NOHA=0.0; real k9 second_order_rate_constant; k9=8.6; real k_9 first_order_rate_constant; k_9=399.2; real k_8 first_order_rate_constant; k_8=13.2; real k8 second_order_rate_constant; k8=13.2; real k10 first_order_rate_constant; k10=39.1; real k11 first_order_rate_constant; k11=20.8; real NO(time) micromolar; when(time=time.min) NO=0.0; real dNOdt(time) flux; real citrulline(time) micromolar; when(time=time.min) citrulline=0.0; real NO3(time) micromolar; when(time=time.min) NO3=0.0; // // Fe3:time=(k_1*Fe3_Arg+k13*Fe3_NO+k12*Fe2_NO*O2-(k1*Arg*Fe3+k2*Fe3)); // Fe3_Arg:time=(k1*Fe3*Arg-(k_1*Fe3_Arg+k3*Fe3_Arg)); // Fe2:time=(k2*Fe3+k_4*Fe2_Arg-k4*Fe2*Arg); // Fe2_Arg:time=(k3*Fe3_Arg+k_5*Fe3_O2_Arg+k4*Fe2*Arg-(k5*Fe2_Arg*O2+k_4*Fe2_Arg)); // Fe3_O2_Arg:time=(k5*Fe2_Arg*O2-(k6*Fe3_O2_Arg+k_5*Fe3_O2_Arg)); // Fe3_NOHA:time=(k6*Fe3_O2_Arg-k7*Fe3_NOHA); // Fe2_NOHA:time=(k7*Fe3_NOHA+k_9*Fe3_O2_NOHA+k8*Fe2*NOHA-(k_8*Fe2_NOHA+k9*Fe2_NOHA*O2)); // Fe3_O2_NOHA:time=(k9*Fe2_NOHA*O2-(k10*Fe3_O2_NOHA+k_9*Fe3_O2_NOHA)); // Fe3_NO:time=(k10*Fe3_O2_NOHA-(k13*Fe3_NO+k11*Fe3_NO)); // Fe2_NO:time=(k11*Fe3_NO-k12*Fe2_NO*O2); // NO:time=(k13*Fe3_NO); NO:time=dNOdt; // citrulline:time=(k10*Fe3_O2_NOHA); // NO3:time=(k12*Fe2_NO*O2); // NOHA:time=(k_8*Fe2_NOHA-k8*Fe2*NOHA); // }