Dynamic Fluctuations Can Counteract Catalytic Inhibition and Enhance Catalytic Performance

Abstract

It is widely accepted that inhibition always suppresses catalysis by blocking active sites or trapping reaction intermediates, negatively affecting multiple chemical, biological and industrial processes. However, this has been established only for static systems in which the properties of catalytic active sites do not change with time. Dynamic catalysis, a phenomenon where active sites fluctuate over time, has recently emerged as a strategy to overcome some fundamental limitations of conventional static catalysis. In this work, we theoretically investigate the coupling between catalytic inhibition and dynamic catalysis using a quantitative stochastic approach that can explicitly evaluate the dynamics of catalyzed reactions. It is found that, in contrast to static catalysis, dynamic catalysis might neutralize the negative effects of inhibition and, in some cases, even increase the catalytic efficiency. It is argued that this is the result of dynamic fluctuations creating reaction pathways that can help the system escape trapped inhibited states, yielding better catalytic performance. Our theoretical analysis shows that there is additional energy dissipation associated with inhibition that drives the system further away from equilibrium, reshaping the overall reaction network, and making dynamic catalysis more efficient. However, greater energy dissipation does not imply higher catalytic efficiency, emphasizing the need to optimize rather than maximize the energetic cost of dynamic catalysis. The proposed theoretical framework provides a quantitative description of the coupling between inhibition and dynamic catalysis, revealing principles for understanding and exploring catalytic phenomena in chemical, biological and industrial processes.