Signal Transduction and Transformation by the Platelet Activation Cascade: Systems Biology Insights

Abstract Binding of platelet activators to their receptors initiates a signal transduction network, where intracellular signal is filtered, amplified, and transformed. Computational systems biology methods could be a powerful tool to address and analyze dynamics and regulation of the crucial steps in this cascade. Here we review these approaches and show the logic of their use for a relatively simple case of SFLLRN-induced procoagulant activity. Use of a typical model is employed to track signaling events along the main axis, from the binding of the peptide to PAR1 receptor down to the mPTP opening. Temporal dynamics, concentration dependence, formation of calcium oscillations and their deciphering, and role of stochasticity are quantified for all essential signaling molecules and their complexes. The initial step-wise activation stimulus is transformed to a peak at the early stages, then to oscillation calcium spikes, and then back to a peak shape. The model can show how both amplitude and width of the peak encode the information about the activation level, and show the principle of decoding calcium oscillations via integration of the calcium signal by the mitochondria. Use of stochastic algorithms can reveal that the complexes of Gq, in particular the complex of phospholipase C with Gq, which are the limiting steps in the cascade with their numbers not exceeding several molecules per platelet at any given time; it is them that cause stochastic appearance of the signals downstream. Application of reduction techniques to simplify the system is demonstrated.