About this model
====================

This is a bond-graph model of a ligand binding a receptor on the cell surface and forming an activated complex. The corresponding G protein is also involved.

    **INPUTS:** 
        - Ligand (L) stimulus e.g. isoproterenol 
        
    **OUTPUTS:** 
        - Amount of activated G protein (G)
        
    **REACTIONS:** 
        - R\ :sub:`C`, R\ :sub:`L`, R\ :sub:`R`
        

Model status
=============

The current CellML implementation runs in OpenCOR.


Model overview
===================
This model is made by from an existing kinetic model, where the mathematics are translated into the bond-graph formalism. This describes the model in energetic terms and forces adherence to the laws of thermodynamics.


.. figure:: exposure/BG_diagram.png
   :width: 100%
   :align: center
   :alt: BG_diagram

|

For the above bond-graphs, a '0' node refers to a junction where all chemical potentials are the same. A '1' node refers to all fluxes being the same going in and out of the junction.

Parameter finding
~~~~~~~~~~~~~~~~~
A description of the process to find bond-graph parameters is shown in the folder    `parameter_finder <parameter_finder>`_, which relies on the:

1. stoichiometry of system

2. kinetic constants for forward/reverse reactions

  - If not already, all reactions are made reversible by assigning a small value to the reverse  direction.
  
3. `linear algebra script <https://models.physiomeproject.org/workspace/6ba/file/c32be022513dc4b620d74803a6ace6ca2d817e11/parameter_finder/find_BG_parameters.py>`_. 

Here, this solve process is performed in Python.


Original kinetic model
======================
Saucerman et al: `Modeling beta-adrenergic control of cardiac myocyte contractility in silico. <https://models.physiomeproject.org/exposure/9766d9bd0325c31e47a31b291e26ccad>`_