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Motility of an autonomous protein-based artificial motor that operates via a burnt-bridge principle

Author

Listed:
  • Chapin S. Korosec

    (Simon Fraser University
    York University)

  • Ivan N. Unksov

    (Lund University)

  • Pradheebha Surendiran

    (Lund University)

  • Roman Lyttleton

    (Lund University)

  • Paul M. G. Curmi

    (University of New South Wales)

  • Christopher N. Angstmann

    (University of New South Wales)

  • Ralf Eichhorn

    (Nordita, Royal Institute of Technology and Stockholm University)

  • Heiner Linke

    (Lund University)

  • Nancy R. Forde

    (Simon Fraser University)

Abstract

Inspired by biology, great progress has been made in creating artificial molecular motors. However, the dream of harnessing proteins – the building blocks selected by nature – to design autonomous motors has so far remained elusive. Here we report the synthesis and characterization of the Lawnmower, an autonomous, protein-based artificial molecular motor comprised of a spherical hub decorated with proteases. Its “burnt-bridge” motion is directed by cleavage of a peptide lawn, promoting motion towards unvisited substrate. We find that Lawnmowers exhibit directional motion with average speeds of up to 80 nm/s, comparable to biological motors. By selectively patterning the peptide lawn on microfabricated tracks, we furthermore show that the Lawnmower is capable of track-guided motion. Our work opens an avenue towards nanotechnology applications of artificial protein motors.

Suggested Citation

  • Chapin S. Korosec & Ivan N. Unksov & Pradheebha Surendiran & Roman Lyttleton & Paul M. G. Curmi & Christopher N. Angstmann & Ralf Eichhorn & Heiner Linke & Nancy R. Forde, 2024. "Motility of an autonomous protein-based artificial motor that operates via a burnt-bridge principle," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45570-y
    DOI: 10.1038/s41467-024-45570-y
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    1. Anna-Katharina Pumm & Wouter Engelen & Enzo Kopperger & Jonas Isensee & Matthias Vogt & Viktorija Kozina & Massimo Kube & Maximilian N. Honemann & Eva Bertosin & Martin Langecker & Ramin Golestanian &, 2022. "A DNA origami rotary ratchet motor," Nature, Nature, vol. 607(7919), pages 492-498, July.
    2. Eldad Kepten & Aleksander Weron & Grzegorz Sikora & Krzysztof Burnecki & Yuval Garini, 2015. "Guidelines for the Fitting of Anomalous Diffusion Mean Square Displacement Graphs from Single Particle Tracking Experiments," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-10, February.
    3. Akihiko Nakamura & Kei-ichi Okazaki & Tadaomi Furuta & Minoru Sakurai & Ryota Iino, 2018. "Processive chitinase is Brownian monorail operated by fast catalysis after peeling rail from crystalline chitin," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    4. Kyle Lund & Anthony J. Manzo & Nadine Dabby & Nicole Michelotti & Alexander Johnson-Buck & Jeanette Nangreave & Steven Taylor & Renjun Pei & Milan N. Stojanovic & Nils G. Walter & Erik Winfree & Hao Y, 2010. "Molecular robots guided by prescriptive landscapes," Nature, Nature, vol. 465(7295), pages 206-210, May.
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