**Model Status**

This CellML model has been built from a mathematical model of feedback control of T-cell receptor by Cliburn Chan, Jaroslav Stark and Andrew J. T. George (2004). This model was integrated and simulated using OpenCOR. Figure 3(a) of the reference publication is produced. 

**Model structure**

The specificity of T-cell recognition is vital to the immune response. Ligand engagement with the T-cell receptor (TCR) results in the activation of a complex sequence of signalling events. Assuming that the recruited Lck is increasing with the duration of TCR ligand engagement, this model simulates a ligand that engages the TCR at time t=10s and dissociates at time t=24s.     

.. image:: chan_2004.png

A schematic diagram of feedback control model. TCR binding to the peptide-MHC results in the recruitment of kinases as shown in reaction (1). This reaction balances the kinase-phosphatase cycle. The positive feedback of active kinase is on enhancing further kinase activation and negative feedback arises when active kinase activates phosphatase, which then deactivate active kinase in a classical loop.

.. image:: chan_output.png

The diagram shows feedback control results in high specificity. This model simulates a ligand that engages the TCR at time t=10s and dissociates at time t=24s. At time t=23s, the level of Lck* rises and the TCR is activated.

The original paper reference is cited below: 

Chan, C., Stark, J., & George, A. J. (2004). Feedback control of T-cell receptor activation. Proceedings of the Royal Society B: Biological Sciences, 271(1542), 931.