ISIS Neutron and Muon Source Data Journal

How hydrophobicity and polymer architecture imacts the ability of star polymers to anchor to mammalian cell membranes

Abstract: Engineering the cell surface with synthetic polymers offers a transformative strategy to control cell behaviour without altering genetic material, with broad applications in drug delivery, regenerative medicine, and diagnostics. Achieving stable yet reversible polymer attachment to the lipid membrane without compromising cellular function remains a key challenge. We focus on the development of star-shaped polymers that self-assemble into reversible, mesh-like networks at the cell surface via precisely tuned physicochemical interactions. Understanding polymer-lipid bilayer interactions is critical for optimising design and ensuring biocompatibility. While we have previously developed antimicrobial polymers that bind to and disrupt lipid bilayers, our current aim is to adsorb polymers onto mammalian membranes without compromising their integrity We have developed a series of linear and 4-arm star block copolymers which hydrophobic blocks to anchor into lipid bilayers. However, the roles of hydrophobic monomer incorporation and polymer architecture in governing the behaviour at the membrane remains poorly understood. We propose to use Neutron Reflectometry to systematically investigate how lipid anchor composition and polymer design influence membrane binding and penetration. These insights will inform the rational design of programmable, biocompatible polymers for reversible cell surface engineering, enabling precise therapeutic interventions at the cellular interface.

Principal Investigator: Dr Julia Rho
Experimenter: Miss Justine Sansom
Experimenter: Miss Yaqi Yang
Experimenter: Miss Hannah Howie
Local Contact: Dr Stephen Hall

DOI: 10.5286/ISIS.E.RB2520659

ISIS Experiment Number: RB2520659

Publisher: STFC ISIS Neutron and Muon Source

Data format: RAW/Nexus
Select the data format above to find out more about it.

Data Citation

The recommended format for citing this dataset in a research publication is as:
[author], [date], [title], [publisher], [doi]

For Example:
Dr Julia Rho et al; (2026): How hydrophobicity and polymer architecture imacts the ability of star polymers to anchor to mammalian cell membranes, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB2520659

Data is released under the CC-BY-4.0 license.