Investigating conditions of perfect adaptation in equilibrium signaling networks

There exists a substantial body of work utilizing thermodynamic limits to analyze computations made by biological signaling systems yielding fruitful insights about the topology and energetics of pathways capable of carrying out various functions of interest. Prior work in the field has identified a tradeoff between energy, speed, and accuracy, suggesting that cells will spend energy to make computations faster and more accurate with respect to a particular function, like adaptation or proofreading. This tradeoff has been treated as a fundamental physical limit on biological computation. However, minimal counter examples have been identified, demonstrating that this tradeoff is not universal and may not explain why we generally observe non-equilibrium networks in biology. To explore this question further, we designed a biologically motivated signaling circuit capable of achieving perfect adaptation at equilibrium. We then utilize this circuit to explore the ESA relationship in these networks, finding that they perform well in all aspects of this tradeoff. We then explore other axes of selection acting in biological and biochemical contexts to try to characterize the limitations of equilibrium systems and the advantages conferred by non-equilibrium networks.