A Novel Approach for Signal Transduction Networks Simulation at a Mesoscopic Level

Signal transduction (ST) networks simulation is important to medical research. However, owing to the complexity of the networks, most methods presented for the simulation are not desirable. Here, based on multi-agent system (MAS), we proposed a novel approach characterized by a multi-level discrete space and mesoscopic molecule-agents for describing ST networks at a mesoscopic level. The space is developed for the representation of the cellular space; it provides a relatively sufficient spatial representation with less computational cost. The mesoscopic molecule-agents model the active components within the networks, which will offer new potentials to overcome the combinatorial complexity as well as make computation feasible. To validate this method, the simulations of a composition/decomposition system and the Mitogen-Activated Protein Kinase (MAPK) signal transduction pathway are implemented. Finally, an in-silico experiment with perturbation in the MAPK pathway is made. The results obtained from the simulations demonstrate the validity of the approach.