Recognition of peptide antigens by the T-cell receptor (TCR) initiates intracellular signaling events that can culminate in T-cell activation, an essential component of the adaptive immune response. Early events following TCR stimulation are relayed in large part through phosphorylation of tyrosine residues in signaling proteins. These site-specific phosphorylation events have been identified and monitored quantitatively using time-resolved mass spectrometric techniques. The resulting phosphoproteomic data reflect the kinetics of molecular interactions in this signaling system. Thus, modeling of chemical kinetics can be a means of data analysis. To this end, we have developed a computational model of early events in TCR signaling that encompasses twenty proteins and aims to reproduce time courses of phosphorylation measured experimentally. To enable development and simulation of this large-scale model, we have applied rule-based representations of molecular interactions and algorithms for agent-based simulation consistent with physicochemical principles. The model can be used to provide a mechanistic interpretation of temporal phosphoproteomic data, to explore the roles of feedbacks in the system, and to visualize and annotate available knowledge about TCR signaling.
