- Author:
- Shelley Fong <s.fong@auckland.ac.nz>
- Date:
- 2022-04-22 13:34:53+12:00
- Desc:
- Trying to improve GHK fit
- Permanent Source URI:
- https://models.physiomeproject.org/workspace/831/rawfile/d640a286065c882f10aa045e3ada5ecfa0db3dd8/parameter_finder/kinetic_parameters_TCC.py
# fast Na module
# Return kinetic parameters, constraints, and vector of volumes in each
# compartment (pL) (1 if gating variable, or in element corresponding to
# kappa)
# Translated from Pan 2018 cardiac AP
import numpy as np
def kinetic_parameters(M, include_type2_reactions, dims, V):
# Set the kinetic rate constants
num_cols = dims['num_cols']
num_rows = dims['num_rows']
# constants are stored in V
F = V['F']
R = V['R']
T = V['T']
N_A = V['N_A']
G_GHK = 1.905857500832444e-07 #1.289597464589430e-06 # Unit mA/mM
P_TCC = G_GHK/F * 1e12 # Unit pL/s . G_GHK [=] Amp/(mol/s)
x_TCC = 228000/N_A*1e15 # unit fmol. From Droogmans 1989
x_TCC = V['numChannels']/N_A*1e15 # unit fmol
# load gate transition parameters
params_d = [2.66722621712886, 0.876568910405296, 0.483332201416662, -0.872117216889333]
params_f = [0.00284309660183583, -0.576510778245838, 0.830414906761407, 1.73582739545622]
z_df = params_d[1]
z_dr = params_d[3]
z_ff = params_f[1]
z_fr = params_f[3]
zf = [z_df, z_ff]
zr = [z_dr, z_fr]
# unit s ^ -1
alpha_d = params_d[0]*1e3 # unit s ^ -1
beta_d = params_d[2]*1e3 # unit s ^ -1
alpha_f = params_f[0]*1e3 # unit s ^ -1
beta_f = params_f[2]*1e3 # unit s ^ -1
kf_Ca = [P_TCC / x_TCC, # R_GHK
alpha_d, # Rb_10
alpha_d, # Rb_11
alpha_f, # Rg_00
alpha_f] # Rg_20
kr_Ca = [P_TCC / x_TCC, # R_GHK
beta_d, # Rb_00
beta_d, # Rb_01
beta_f, # Rg_00
beta_f] # Rg_20
k_kinetic = kf_Ca + kr_Ca
# CONSTRAINTS
N_cT = []
K_C = []
# volume vector
# W = list(np.append([1] * num_cols, [V['V_myo']] * num_rows))
W = [1] * num_cols + [V['V_myo'], V['V_o']] + [1] * (num_rows-2)
return (k_kinetic, N_cT, K_C, W)
