Computational analysis of mTOR signaling pathway: bifurcation, carcinogenesis, and drug discovery.

Molecularly targeted therapeutics provides potentially more reliable performance while significantly reducing toxicity in comparison with chemotherapy. For cancer signaling networks which are usually complex, multiple molecules should be simultaneously targeted in order to stay in tune with the control mechanisms of the network and to achieve the maximum synergistic effects. Mathematical modeling and computer simulation are important in reproducing the dynamics of the network, some of which may correspond to healthy or cancer phenotypes. More importantly, the effects of multiple molecules can be simulated by perturbing many parameters in the model. In this paper, through the example of the mTOR signaling pathway, we demonstrate that computational analysis can provide great insights into cancer pathogenesis and the possible therapeutic interventions. In particular, we discovered a composite parameter which summarizes the synergistic effects of four different parameters. The geometry of the parameter space could be helpful in the development of a low dosage, minimal toxicity drug to cure cancer.