Fluctuation-Response Design Rules for Nonequilibrium Flows

Area of Science:

• Biophysics
• Biochemistry
• Systems Biology

Background:

• Biological machines, including molecular motors and enzymes, function through dynamic cycles modeled as stochastic flows on networks.
• Current stochastic dynamics models are limited to fixed network structures.
• Understanding and controlling these biological systems requires methods that can adapt network dynamics.

Purpose of the Study:

• To develop a scalable approach for designing biological networks with tunable dynamics.
• To enable systematic variation of local transition rates to achieve specific global dynamical objectives.
• To provide new insights into the behavior of biological machines by analyzing their network dynamics.

Main Methods:

• Utilizing the fluctuation-response duality from Caliber Force Theory, a path-entropy variational formalism for non-equilibrium systems.
• Developing a method for systematic variation of local transition rates within a network.
• Applying the approach to analyze a kinesin motor model.

Main Results:

• A scalable method for network design applicable to complex biological systems.
• Demonstration of how local rate variations can achieve global dynamical control.
• Identification of a transition from timing-dominated to branching-dominated fluctuations in a kinesin motor model.

Conclusions:

• The developed network design approach offers a powerful tool for engineering biological machines.
• Caliber Force Theory provides a robust framework for understanding non-equilibrium dynamics in biological networks.
• This work advances the understanding of molecular motor fluctuations and control mechanisms.