IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-019-11402-7.html
   My bibliography  Save this article

Kinetic asymmetry allows macromolecular catalysts to drive an information ratchet

Author

Listed:
  • R. Dean Astumian

    (University of Maine)

Abstract

Molecular machines carry out their function by equilibrium mechanical motions in environments that are far from thermodynamic equilibrium. The mechanically equilibrated character of the trajectories of the macromolecule has allowed development of a powerful theoretical description, reminiscent of Onsager’s trajectory thermodynamics, that is based on the principle of microscopic reversibility. Unlike the situation at thermodynamic equilibrium, kinetic parameters play a dominant role in determining steady-state concentrations away from thermodynamic equilibrium, and kinetic asymmetry provides a mechanism by which chemical free-energy released by catalysis can drive directed motion, molecular adaptation, and self-assembly. Several examples drawn from the recent literature, including a catenane-based chemically driven molecular rotor and a synthetic molecular assembler or pump, are discussed.

Suggested Citation

  • R. Dean Astumian, 2019. "Kinetic asymmetry allows macromolecular catalysts to drive an information ratchet," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11402-7
    DOI: 10.1038/s41467-019-11402-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-11402-7
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-019-11402-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andrea Braeutigam & Ahmet Nihat Simsek & Gerhard Gompper & Benedikt Sabass, 2022. "Generic self-stabilization mechanism for biomolecular adhesions under load," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Daniela Sorrentino & Simona Ranallo & Francesco Ricci & Elisa Franco, 2024. "Developmental assembly of multi-component polymer systems through interconnected synthetic gene networks in vitro," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11402-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.