Abstract:
Understanding cellular signaling is central for gaining insight into the molecular mechanisms behind diseases as well as adaptation of living cells to changes in the environment. Signaling pathways are often branched in an interconnected fashion and are therefore integrated into signaling networks that are quite complex with many levels of interconnectivity of different molecular components. Recently, it became apparent that each MAPK pathway is a part of a network in which there is extensive sharing of signaling elements among the MAPK signaling pathways. Understanding the design principles that bridge the topology to the function of the network is a major challenge in systems biology since almost all known diseases exhibit dysfunctional aspects in these signaling networks. In the present study, using a probabilistic graph model (Bayesian Network) the feasibility of alternative signaling mechanisms was tested in the MAPK network in Saccharomyces cerevisiae. As a result of the large cross-talks between MAPK pathways, several signal transmission mechanisms that are biologically inactive were observed to be feasible. On the other hand, adaptation of a game theoretical formulation, in which the optimum strategy of a player was determined by considering the possible strategies of other players, resulted in a Nash Equilibrium (i.e., the set of optimum strategies) which eliminated the false-positives due to the crosstalk and represented the biology successfully. This mathematical framework has shown that logical reasoning is in accordance with real biology and thus provides an opportunity to model complex systems. The proposed methodology with further improvements in biological data is expected to provide more insight about the underlying principle in evolutionary construction of network topology.
