Light-Driven Micromotors to Dissociate Protein Aggregates That Cause Neurodegenerative Diseases

Paula Mayorga-Burrezo, Carmen C. Mayorga-Martinez, Martin Pumera

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

Nowadays, microrobots are considered appealing mobile carriers for clinical therapies. In this sense, high expectations against unmet medical challenges have been created around microswimmers that combine autonomous navigation with enhanced abilities to perform specific tasks. Neurodegenerative disorders are incurable diseases that have a huge impact on the quality of life for millions of people. To date, protein disaggregation (i.e., dissociation of mature protein fibrils on the origin of the given illness) has been discussed as targeted therapy by means of nonautonomous nanoparticles. Here, self-propelled light-driven single-component micromotors based on concave BiVO4 microspheres are used to disaggregate protein fibrils. Efficient disaggregation is proved to be promoted by the micromotors’ intrinsic on-the-fly generation of reactive oxygen species (ROS). Moreover, the helical trajectories observed for these single-component micromotors are thought to be probably behind the uniform distribution of ROS, leading to enhanced protein dissociation. This conceptually promising application of light-driven micromotors with efficient photocatalytic ROS production and distribution can be extended to alternative ROS-based photodynamic therapies against lung or skin cancer, among others.

Original languageEnglish
Article number2106699
JournalAdvanced Functional Materials
Volume32
Issue number1
DOIs
Publication statusPublished - 2022 Jan 3

Bibliographical note

Funding Information:
M.P. was supported by the Ministry of Education, Youth and Sports (Czech Republic) grant LL2002 under ERC CZ program. P.M.‐B. thanks the CEITEC Nano Research Infrastructure supported by MEYS CR (LM2018110) for providing spectroscopic and microscopic characterization facilities, and Dr. Jayraj V. Vaghasiya for BET surface area measurements. C.C.M.M. was supported by the project Advanced Functional Nanorobots (reg. No. CZ.02.1.01/0.0/0.0/15_003/0000444 financed by the EFRR).

Publisher Copyright:
© 2021 Wiley-VCH GmbH

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Materials Science(all)
  • Condensed Matter Physics

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