- Author:
- Shelley Fong <s.fong@auckland.ac.nz>
- Date:
- 2021-10-27 09:36:20+13:00
- Desc:
- Removing legacy excel file
- Permanent Source URI:
- https://models.cellml.org/workspace/6f9/rawfile/94432e1fcbbda2c3e5e4a28e53785a563ee03c3d/parameter_finder/kinetic_parameters.py
# Gi protein module following Saucerman and Iancu: act1 and act2 with LR
# and LRG as substrates (G is already bound, so there is only one substrate
# to each act reaction)
# Gi is associated with muscarinic 2 (M2) receptors in cardiac myocytes
# 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_type2_reactions, dims, V):
# Set the kinetic rate constants.
# original model had reactions that omitted enzymes as substrates e.g. BARK
# convert unit from 1/s to 1/uM.s by dividing by conc of enzyme
# all reactions were irreversible, made reversible by letting kr ~= 0
num_cols = dims['num_cols']
num_rows = dims['num_rows']
bigNum = 1e3
fastKineticConstant = bigNum
smallReverse = fastKineticConstant/(pow(bigNum,2))
kAct1p = 2.5 # 1/s
kAct1m = smallReverse # 1/s
kAct2p = 0.05 # 1/s
kAct2m = smallReverse # 1/s
kHydp = 0.8 # 1/s
kHydm = smallReverse # 1/s
kReassocp = 1.21e3 # 1/uM.s
kReassocm = kReassocp/bigNum # 1/s
# ensure that the closed loop formed by Act1 & Act2 obey detailed
# balance
kAct2m = kAct1m * kAct2p / kAct1p
# CLOSED LOOP involving G - aGTP - aGDP - G
# use detailed balance to find kReasocm with either Act (as they have
# same equilibrium constant
if True:
kReassocm = kAct1p*kHydp*kReassocp/(kAct1m*kHydm)
k_kinetic = [
kAct1p, kAct2p, kHydp, kReassocp,
kAct1m, kAct2m, kHydm, kReassocm
]
# CONSTRAINTS
N_cT = np.zeros(len(M[0]))
# LR.G = aGTP.betaGamma
if False:
N_cT[1][num_cols + 2] = 1
N_cT[1][num_cols + 3] = 1
N_cT[1][num_cols + 4] = -1
N_cT[1][num_cols + 5] = -1
# [a-GTP] + [a-GDP] = [beta.gamma] **SMALL_ERROR**
if True:
N_cT[num_cols + 6] = 1 # beta_gamma
N_cT[num_cols + 5] = -1 # a_GTP
N_cT[num_cols + 7] = -1 # a_GDP
K_C = [1]
# volume vector
W = list(np.append([1] * num_cols, [V['V_myo']] * num_rows))
return (k_kinetic, [N_cT], K_C, W)
