Energy-based modelling of single actin filament polymerization using bond graphs.

Area of Science:

• Systems biology
• Biophysics
• Computational biology

Background:

• Bond graphs offer a hierarchical, energy-based modeling approach for complex systems.
• Current methods allow modeling of biological systems with chemical and electrical subsystems.
• Chemomechanical transduction is crucial in biological processes like muscle contraction and cell motility.

Purpose of the Study:

• To extend the bond graph methodology to include chemomechanical transduction.
• To model actin filament polymerization and force generation using bond graphs.
• To provide a simpler, energy-based alternative to the Brownian ratchet model.

Main Methods:

• Utilized the bond graph approach, incorporating the transformer (TF) component.
• Modeled actin filament polymerization and force generation as a chemomechanical system.
• Extended the model to include flexibility, non-normal incidence, and compliance.

Main Results:

• Demonstrated that the TF bond graph component effectively models chemomechanical transduction.
• Showed the bond graph approach yields equivalent equations to the Brownian ratchet model in simple cases.
• Illustrated how additional bond graph components can model system complexities like flexibility and non-normal incidence.
• Revealed that compliance leads to non-convexity in the force-velocity curve.

Conclusions:

• The bond graph approach provides a versatile and conceptually simple framework for modeling chemomechanical transduction in biological systems.
• This energy-based methodology facilitates the investigation of power transmission and efficiency in systems like actin filaments.
• The bond graph model can be fitted to experimental data by adjusting physical parameters, enabling quantitative analysis.