Gears in Chemical Reaction Networks: Optimizing Energy Transduction Efficiency

TL;DR

This paper introduces a gear analogy for chemical reaction networks (CRNs), showing how their pathways can be optimized for energy efficiency through topology and kinetics, with applications in biological and artificial systems.

Contribution

It conceptualizes chemical reaction pathways as gears, deriving a method to optimize CRN efficiency based on topology and conditions, and demonstrates biological and artificial system applications.

Findings

CRNs can be tuned for optimal energy efficiency using gear analogy.

Biological enzymes act as adaptive gear shifters in CRNs.

Artificial molecular motors are less efficiently regulated.

Abstract

Similarly to gear systems in vehicles, most chemical reaction networks (CRNs) involved in energy transduction have at their disposal multiple transduction pathways, each characterized by distinct efficiencies. We conceptualize these pathways as `chemical gears' and demonstrate their role in refining the second law of thermodynamics. This allows us to determine the optimal efficiency of a CRN, and the gear enabling it, solely based on its topology and operating conditions, defined by the chemical potentials of its input and output species. By suitably tuning reaction kinetics, a CRN can be engineered to self-regulate its gear settings, maintaining optimal efficiency under varying external conditions. We demonstrate this principle in a biological context with a CRN where enzymes function as gear shifters, autonomously adapting the system to achieve near-optimal efficiency across changing environments. Additionally, we examine artificial molecular motors and reveal that their gearing mechanisms are far from optimally regulated.