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  • Open Access

Nonequilibrium theory for molecular machine design

Ying-Jen Yang*

Ken A. Dill

  • *Contact author: ying-jen.yang@stonybrook.edu
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Phys. Rev. Research 8, 043104 – Published 29 October, 2026

DOI: https://doi.org/10.1103/c8kc-rklj

Abstract

Modeling biomolecular machines with the probability flows on Markov networks often entails computing node probabilities and edge fluxes with master equations and correlating machine performance with entropy production. However, this alone is not sufficient for design, optimization, and evolution because it does not treat cost-benefit trade-offs, topological misflows (backsteps, futile cycles, ineffective actions), or differential properties for flow design. Here, we develop CFT Design, based on the recently developed caliber force theory (CFT). We apply it to designing faster molecular motors through “traffic control”; optimizing speed, energy, and accuracy in kinetic proofreaders simultaneously to break their trade-offs; and designing better enzyme inhibitors based on their network topologies. CFT Design provides a general framework for optimizing nonequilibrium flows.

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Phys. Rev. Research 8, 043104– Published 29 October, 2026
  • Received 12 May 2026
  • Accepted 2 October 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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