Presenter
Emanuele Penocchio
Emanuele Penocchio is a postdoc in the Department of Chemistry at Northwestern University. After studying chemistry, he obtained a Ph.D. in Physics in 2022, with a thesis on the non-equilibrium thermodynamics of chemical reaction networks. His research focuses on the physical chemistry underlying chemical systems that consume energy to perform functions. Emanuele received the 2022 Distinguished Student Award from the Foresight Institute and the 2023 Perkin Prize in Physical Organic Chemistry from the Royal Society of Chemistry as part of "The Molecular Ratcheteers" team
Summary:
For several decades, molecular motor directionality has been rationalized in terms of the free energy of molecular conformations visited before and after the motor takes a step, a so-called power-stroke mechanism with analogues in macroscopic engines. Despite theoretical and experimental demonstrations of its flaws, power-stroke language is quite ingrained, and some communities still value power-stroke intuition.
By building a catalysis-driven motor into simulated numerical experiments, I systematically show how directionality responds when the motor is modified according to power-stroke intuition. Simulations confirm that the power stroke mechanism does not generally predict the directionality. Still, the relative stability of molecular conformations can nevertheless be a useful design element that helps one alter the directional bias of a molecular motor. The ostensible effectiveness of power-stroke intuition is explained by the recognition that to target conformation stability, one must alter interactions between moieties of a molecular motor, and those altered interactions do not affect the power stroke in isolation. This can lead to apparent correlations between power stroke and directionality that one might leverage when engineering specific systems.
Challenges:
– To paraphrase Richard Feynman, what I cannot simulate, I do not understand. Developing general and predictive computational models to simulate out-of-equilibrium molecular machinery explicitly is a grand challenge for the statistical mechanics community.
– For the field in general, finding applications of out-of-equilibrium molecular machinery and scaling their functioning up to the macroscopic world is one of the next significant steps.
– I would also love to see more dialogue between the artificial molecular machine and the biophysical communities, addressing the challenge of finding a common language and vision.
