Modular dynamic biomolecular modelling with bond graphs: the unification of stoichiometry, thermodynamics, kinetics and data

Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here, we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermodynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of Escherichia coli and published experimental data.

Automated summary

Renewed interest in dynamic simulation models of biomolecular systems has led to the development of genome-scale models of cellular metabolism that go beyond steady state to capture transient and dynamic regulatory properties. The energy-based bond graph methodology proposed in this study integrates stoichiometric models with thermodynamic principles and kinetic modeling, enforcing thermodynamic constraints and providing a modular approach for model estimation. Illustration of the approach using an established stoichiometric model of Escherichia coli and published experimental data demonstrates its effectiveness in dynamic modeling of biomolecular systems.