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 analyze the gear system of an artificial molecular motor, identifying numerous counterproductive gears and providing insights into its transduction capabilities and optimization.