- Author:
- Shelley Fong <s.fong@auckland.ac.nz>
- Date:
- 2021-11-26 14:26:15+13:00
- Desc:
- Updating Knames
- Permanent Source URI:
- https://models.physiomeproject.org/workspace/6f7/rawfile/cc2514c39be9403d498e6a6d62927e4d52b3c541/parameter_finder/kinetic_parameters_LRGbinding_B1AR.py
# LRGbinding module - for saucerman B1AR as GPCR
# 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']
# concentration of BARK = 0.6uM (crude approx from litsearch, for GRK)
bigNum = 1e6
fastKineticConstant = bigNum
KRc = 33 # uM Kc
KRL = 0.285 # uM Kl
KRr = 0.062 # uM Kr
kRcp = fastKineticConstant
kRcm = kRcp*KRc
# ksig2p = fastKineticConstant
# ksig2m = ksig2p*Ksig2
kRrp = fastKineticConstant
kRrm = kRrp*KRr
kRLp = fastKineticConstant
# find kRLm using detailed balance if a closed loop exists
# kRLm = kRcm*ksig2m*kRrp*kRLp/(kRcp*ksig2p*kRrm)
kRLm = kRLp*KRL
k_kinetic = [
kRcp, kRrp, kRLp,
kRcm, kRrm, kRLm
]
# CONSTRAINTS
N_cT = []
K_C = []
# volume vector
W = list(np.append([1] * num_cols, [V['V_myo']] * num_rows))
return (k_kinetic, [N_cT], K_C, W)
