Model-aided analysis of signal transduction pathway
There have been questions on how ligand-stimulated receptor tyrosine kinases induce ligand-specific cell fate by utilizing overlapping intracellular proteins and genetic resources. This specificity may be caused by differences in kinetic determinants of protein-protein interaction complex in the signal transduction pathways, or distinct gene networks with different components and architectures. We have been working on the signal transduction network using model-aided molecular and network models.
-Our current focus are;
ErbB receptor, ERK and Akt signaling in cancer
B cell receptor (BCR)-mediated NF kappaB signaling
EGF receptor families or ErbB receptor tyrosine kinases play essential roles in cell growth, proliferation, differentiation or apoptosis, and their deregulated expression or mutation highly correlates with the incidence of human cancer. Based on the experimental observation, we develop mathematical models for the ligand-induced ErbB signaling pathway to understand the regulatory dynamics of the kinases and phosphatases in cell fate decision process. The spatio-temporal changes of the biochemical reactants are simulated and the effects of the parameters such as the kinetic parameters, diffusion coefficients, and the spatial structures on the dynamics are analyzed with the model.
Building of the network model is sometimes difficult because of the lack of kinetic information such as association/dissociation constants for protein-protein interaction, or Vmax and Km for enzyme reactions. Precise network modeling based on the structural information should be very useful for predicting the binding affinity between proteins. For this purpose, we perform molecular dynamics (MD) simulation as well as network simulation in close collaboration with High Performance Molecular Simulation Team in RIKEN Kobe and CBRC Odaiba.