DYNAMO: Molecular Dynamics of Membrane-associated Protein Complexes

Signal transducing protein networks are topologically tightly organized macromolecular protein complexes that act like specialized molecular machines. These machines are composed of constitutive building blocks including specific nodes in combination with multifunctional scaffolds and highly dynamic interactions, moving in and out of a complex. Specificity within these complexes is conferred using combinatory principles combined with specific signaling in- and outputs. The main aim of the DYNAMO consortium is a systems biology approach to analyze dynamics of membrane associated protein complexes. For this purpose the consortium develops novel measurement techniques to determine the state of protein complexes in vivo and novel mathematical modeling techniques to describe these networks in silico.

Two different model systems covering different dynamic aspects are studied: (1) the light signalling by rhodopsin and (2) protein translocation through the mitochondrial protein import.

The conventional modeling methods run into severe problems due to the combinatorial explosion of the number of different protein complexes. The description of such networks is hardly possible without the use of reaction rules, i.e. patterns describing sets of reactions. Furthermore, it is difficult to guarantee the thermodynamic consistency of such networks since each cycle in the network has to fulfill the Wegscheider conditions. Thermodynamic Kinetic Modeling (TKM, Ederer et al., Biophys J, 2007) is a formalism which is equivalent to the conventional modelling approach and implicitly guarantees the thermodynamic consistency of the reaction network. Furthermore, reduction of fast reactions is easily possible by a formalised procedure.

We have extended the concept of TKM for the use with reaction rules. This creates a powerful method for thermodynamically consistent modelling with reaction rules. Introducing the concept of interaction factors, the formalism allows a much more flexible parameterisation than conventional rule-based models, while keeping the number of parameters low. Formalised model reduction is still possible - in many cases, the reduction can even be performed at the level of the reaction rules, so that the computational effort is drastically reduced. The approach was implemented in Mathematica. Currently, we are developing models of phosducin phosphorylation in light signalling and of TOM complex assembly. The approach will then be applied to these models.

 

The project was funded by the BMBF.

 

Julia Rex