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Catalysis‐driven Active Transport Across a Liquid Membrane.

  • Published In: Angewandte Chemie, 2025, v. 137, n. 15. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Liang, Kaiyuan; Nicoli, Federico; Shehimy, Shaymaa Al; Penocchio, Emanuele; Di Noja, Simone; Li, Yuhan; Bonfio, Claudia; Borsley, Stefan; Ragazzon, Giulio 3 of 3

Abstract

Biology has mastered energy transduction, converting energy between various forms, and employing it to drive its vital processes. Central to this is the ability to use chemical energy for the active transport of substances, pumping ions and molecules across hydrophobic lipid membranes between aqueous (sub)cellular compartments. Biology employs information ratchet mechanisms, where kinetic asymmetry in the fuel‐to‐waste (i. e., substrate‐to‐product) conversion results in catalysis‐driven active transport. Here, we report an artificial system for catalysis‐driven active transport across a hydrophobic phase, pumping a maleic acid cargo between aqueous compartments. We employ two strategies to differentiate the conditions in either compartment, showing that active transport can be driven either by adding fuel to a single compartment, or by differentiating the rates of activation and/or hydrolysis when fuel is present in both compartments. We characterize the nonequilibrium system through complete kinetic analysis. Finally, we quantify the energy transduction achieved by the catalysis‐driven active transport and establish the emergence of positive and negative feedback mechanisms within the system. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Angewandte Chemie. 2025/04, Vol. 137, Issue 15, p1
  • Document Type:Article
  • Subject Area:Biology
  • Publication Date:2025
  • ISSN:0044-8249
  • DOI:10.1002/ange.202421234
  • Accession Number:184320869
  • Copyright Statement:Copyright of Angewandte Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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