Motor or Switch? Theory Shows the Way to Obtain Elusive, Granu-lar Information about Kinetic Asymmetry Driven Systems

Kinetic asymmetry is crucial in chemical systems where the selective synthesis of one product over another, or the accelera-tion of specific reaction(s) is necessary. However, obtaining precise information with current experimental methods about the behavior of such systems as a function of time, substrate concentration and other relevant parameters is not possible. Computational chemistry provides a powerful means to address this problem. The current study unveils a two-pronged computational approach: (i) full quantum chemical studies with density functional theory (DFT), followed by (ii) stochastic simulations with a validated Gillespie algorithm (GA) (using representative model systems where necessary), to study the behavior of a unidirectional molecular motor (1-phenylpyrrole2,2′-dicarboxylic acid) (Nature 2022, 604 (7904), 80–85). Our approach allows us to understand what is really taking place in the system, showing that its behavior is dependent on the concentration of one of the substrates (“fuel”): when the fuel concentration is high, the rotating molecule behaves more like a switch (undesirable), but when low, it behaves primarily as a motor (desired outcome). These insights allow us to propose recipes to significantly improve the ability of the molecule to behave as a motor. They further serve to explain the efficient rotation of the very recently reported gel-embedded molecular motor (Nature 2025, 637 (8046), 594–600), and thus to also possibly provide insight into the functioning of bio-molecular motors. The current work therefore provides a template for carefully and properly studying a wide variety of important, kinetic asymmetry driven systems in the future.