# PLB module # all rxn directions align with kinetic Saucerman model (Km unchanged, # aside from dimensional scaling) # 5 AUG PLB separated into PLB and Inhib1 submodules # (parameter error was large with both submodules together) # 25 Aug # return (k_kinetic, N_cT, K_C, W) kinetic parameters, constraints, and vector of volumes in each # compartment (pL) (1 if gating variable, or in element corresponding to # kappa) import numpy as np def kinetic_parameters(M, include_all_reactions, dims, V): # Set the kinetic rate constants. # all reactions are reversible. no closed loops. num_cols = dims['num_cols'] num_rows = dims['num_rows'] bigNum = 1e3 fastKineticConstant = bigNum smallReverse = fastKineticConstant/(pow(bigNum,2)) cPP2A = 0.224 # uM (Bhalla Iyengar a on PMR) but not sure what cell type this is # reaction IDs # PKAi1 (reverse), PKAi2 (reverse) # PP2ai1, PP2ai2 k_pka_i1 = 60 #: per_sec 60 Km_pka_i1 = 1 #: uM 1 Vmax_pp2a_i1 = 14 #: uM_per_sec 14 Km_pp2a_i1 = 1 #: uM 1 vKm = [Km_pka_i1, Km_pp2a_i1] vkcat = [ k_pka_i1, Vmax_pp2a_i1/cPP2A ] N = len(vKm) k1m = [] #np.zeros(N) k1p = [] #np.zeros(N) k2m = [] #np.zeros(N) k2p = [] #np.zeros(N) for i in range(N): # forward rxns k2p.append(vkcat[i]) k1m.append(fastKineticConstant) # 1/s k1p.append((k1m[i] + k2p[i]) / (vKm[i])) k2m.append(k1p[i]*k2p[i]/k1m[i]) # detailed balance if include_all_reactions: k_kinetic = k1p + k2p + k1m + k2m else: irr = range(3) k_kinetic = [ k1p[irr], k2p[irr], k1m[irr], k2m[irr] ] # CONSTRAINTS N_cT = [] # N_cT = [] # # # Reaction i: [PKA:PKI] = [C][PKI] at SS big error. Not isolated reaction # # repeat for type 1 and 2 # if False: # N_cT[0][num_cols + 1] = 1 # N_cT[0][num_cols + 5] = 1 # N_cT[0][num_cols + 8) = -1 # # # Gibbs free energy of L + R binding **MED_ERROR** # if False: # N_cT[2][num_cols + 3] = 1 # ARC # N_cT[2][num_cols) = -1 # cAMP # N_cT[2][num_cols + 2] = -1 # RC # G_0_bind = -45.1872 # kJ/mol # R = 8.314 # T = 310 # K_bind = np.exp(G_0_bind/(R*T))*10^6 # K_C = [] # volume vector W = list(np.append([1] * num_cols, [V['V_myo']] * num_rows)) return (k_kinetic, [N_cT], K_C, W)