$\mathrm{LR}=\frac{LR}{\mathrm{Kl}}\mathrm{LRG}=\frac{\mathrm{LR}\mathrm{Gs}}{\mathrm{Kr}}\mathrm{RG}=\frac{R\mathrm{Gs}}{\mathrm{Kc}}\mathrm{BARK_DESENS}=\mathrm{k_bar_kp}(\mathrm{LR}+\mathrm{LRG})\mathrm{BARK_RESENS}=\mathrm{k_bar_km}\mathrm{b1_AR_d}\mathrm{PKA_DESENS}=\mathrm{k_p_kap}\mathrm{PKAC_I}\mathrm{b1_AR_tot}\mathrm{PKA_RESENS}=\mathrm{k_p_kam}\mathrm{b1_AR_p}\mathrm{G_ACT}=\mathrm{k_g_act}(\mathrm{RG}+\mathrm{LRG})\mathrm{HYD}=\mathrm{k_hyd}\mathrm{Gs_agtp_tot}\mathrm{REASSOC}=\mathrm{k_reassoc}\mathrm{Gs_agdp}\mathrm{Gs_bg}L=\mathrm{L_totmax}-\mathrm{LR}-\mathrm{LRG}R=\mathrm{b1_AR_tot}-\mathrm{LR}-\mathrm{LRG}-\mathrm{RG}\mathrm{Gs}=\mathrm{Gs_tot}-\mathrm{LRG}-\mathrm{RG}\frac{d \mathrm{b1_AR_tot}}{d \mathrm{time}}}=\mathrm{BARK_RESENS}-\mathrm{BARK_DESENS}+\mathrm{PKA_RESENS}-\mathrm{PKA_DESENS}\frac{d \mathrm{b1_AR_d}}{d \mathrm{time}}}=\mathrm{BARK_DESENS}-\mathrm{BARK_RESENS}\frac{d \mathrm{b1_AR_p}}{d \mathrm{time}}}=\mathrm{PKA_DESENS}-\mathrm{PKA_RESENS}\frac{d \mathrm{Gs_agtp_tot}}{d \mathrm{time}}}=\mathrm{G_ACT}-\mathrm{HYD}\frac{d \mathrm{Gs_agdp}}{d \mathrm{time}}}=\mathrm{HYD}-\mathrm{REASSOC}\frac{d \mathrm{Gs_bg}}{d \mathrm{time}}}=\mathrm{G_ACT}-\mathrm{REASSOC}$ $\mathrm{Gsa_GTP_AC}=\frac{\mathrm{Gsa_GTP}\mathrm{AC}}{\mathrm{K_gsa}}\mathrm{Fsk_AC}=\frac{\mathrm{Fsk}\mathrm{AC}}{\mathrm{K_fsk}}\mathrm{AC_ACT_BASAL}=\frac{\mathrm{k_ac_basal}\mathrm{AC}\mathrm{ATP}}{\mathrm{Km_basal}+\mathrm{ATP}}\mathrm{AC_ACT_GSA}=\frac{\mathrm{k_ac_gsa}\mathrm{Gsa_GTP_AC}\mathrm{ATP}}{\mathrm{Km_gsa}+\mathrm{ATP}}\mathrm{AC_ACT_FSK}=\frac{\mathrm{k_ac_fsk}\mathrm{Fsk_AC}\mathrm{ATP}}{\mathrm{Km_fsk}+\mathrm{ATP}}\mathrm{PDE_ACT}=\frac{\mathrm{k_pde}\mathrm{PDE}\mathrm{cAMP}}{\mathrm{Km_pde}+\mathrm{cAMP}}\mathrm{PDE_IBMX}=\frac{\mathrm{PDE}\mathrm{IBMX}}{\mathrm{Ki_ibmx}}\mathrm{Gsa_GTP}=\mathrm{Gs_agtp_tot}-\mathrm{Gsa_GTP_AC}\mathrm{Fsk}=\mathrm{Fsk_tot}-\mathrm{Fsk_AC}\mathrm{AC}=\mathrm{AC_tot}-\mathrm{Gsa_GTP_AC}\mathrm{PDE}=\mathrm{PDE_tot}-\mathrm{PDE_IBMX}\mathrm{IBMX}=\mathrm{IBMX_tot}-\mathrm{PDE_IBMX}\frac{d \mathrm{cAMP_tot}}{d \mathrm{time}}}=\mathrm{AC_ACT_BASAL}+\mathrm{AC_ACT_GSA}+\mathrm{AC_ACT_FSK}-\mathrm{PDE_ACT}$ $\mathrm{I_PCa}=\frac{\mathrm{I_bar_PCa}\mathrm{Ca_i}}{\mathrm{Km_PCa}+\mathrm{Ca_i}}$ $\mathrm{I_CaB}=\mathrm{G_CaB}(\mathrm{V_m}-\mathrm{E_Ca})$ $\mathrm{I_NaB}=\mathrm{G_NaB}(\mathrm{V_m}-\mathrm{E_Na})$
Modelling Beta-adrenergic Control of Cardiac Myocyte Contractility in Silico Catherine Lloyd Auckland Bioengineering Institute, The University of Auckland
Model Status This CellML version of the Saucerman and McCulloch 2003 model is a translation of Jeff Saucerman's original MATLAB code, where all figures of the original paper are reproduced. In this CellML version, units are consistent.
Model Structure ABSTRACT: The beta-adrenergic signaling pathway regulates cardiac myocyte contractility through a combination of feedforward and feedback mechanisms. We used systems analysis to investigate how the components and topology of this signaling network permit neurohormonal control of excitation-contraction coupling in the rat ventricular myocyte. A kinetic model integrating beta-adrenergic signaling with excitation-contraction coupling was formulated, and each subsystem was validated with independent biochemical and physiological measurements. Model analysis was used to investigate quantitatively the effects of specific molecular perturbations. 3-Fold overexpression of adenylyl cyclase in the model allowed an 85% higher rate of cyclic AMP synthesis than an equivalent overexpression of beta 1-adrenergic receptor, and manipulating the affinity of Gs alpha for adenylyl cyclase was a more potent regulator of cyclic AMP production. The model predicted that less than 40% of adenylyl cyclase molecules may be stimulated under maximal receptor activation, and an experimental protocol is suggested for validating this prediction. The model also predicted that the endogenous heat-stable protein kinase inhibitor may enhance basal cyclic AMP buffering by 68% and increasing the apparent Hill coefficient of protein kinase A activation from 1.0 to 2.0. Finally, phosphorylation of the L-type calcium channel and phospholamban were found sufficient to predict the dominant changes in myocyte contractility, including a 2.6x increase in systolic calcium (inotropy) and a 28% decrease in calcium half-relaxation time (lusitropy). By performing systems analysis, the consequences of molecular perturbations in the beta-adrenergic signaling network may be understood within the context of integrative cellular physiology. The original paper reference is cited below: Modeling beta-adrenergic control of cardiac myocyte contractility in silico , Jeffrey J. Saucerman, Laurence L. Brunton, Anushka P. Michailova, and Andrew D. McCulloch, 2003, Journal of Biological Chemistry, 48, 47997-48003. PubMed ID: 12972422 cell diagram Schematic diagram of the integrated model components, including the beta-adrenergic network, calcium handling, and the electrophysiology of the rat ventricular myocyte.
0.9880 0 0.000055258 0 3.8182 0 0.0224 0 0 0 0.0471 0 0.0389 0 0 0 0.2270 0 0.0588 0 0.0083 0 0.000062734 0 0.8375 0 0.0001915621321237139 0 0.011797127788434 0 6.393472881317164e-006 0 1.318755891261303e-005 0 2.550303598764206e-006 0 0.188856340181038 0 0.002637049031266 0 0 0 0.007804801155677 0 0.021086469205792 0 0 0 0.028913120628562 0 5.347178381946943e-004 0 0.002902132276476 0 0.215969749518694 0 5.833957806072837e-005 0 0.030620759947184 0 0.116855995664640 0 0.002349076069413 0 3.912192345658711 0 2.632174973738626 0 2.631352403516753 0 0.052537266144485 0 0.699596361354732 0 0.004224662072671 0 0.004069381726891 0 Nunns Geoffrey Rogan gnunns1@jhu.edu The University of Auckland Auckland Bioengineering Institute 2009-12-02 keyword signal transduction metabolism cardiac myocyte electrophysiology cardiac 12972422 Saucerman J J Brunton L L Michailova A P McCulloch A D Modeling beta-adrenergic control of cardiac myocyte contractility in silico 2003-11-28 The Journal of Biological Chemistry 278 47997 48003