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arXiv · 2605.27040

Designing Multivalent Copolymers for Selective Targeting of Multicomponent Surfaces

Vid Ravnik·Urban Bren·Tine Curk
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Abstract

Selective targeting of membranes with a specific receptor profile is an ongoing challenge in targeted drug delivery. We investigate the adsorption of copolymers on a multicomponent receptor-covered surface using grand-canonical Monte Carlo simulations and demonstrate that polymers can be designed to target a particular receptor density profile. To achieve this, the ligand profile on the polymers should match the targeted receptor profile, and the ligand--receptor affinity should be inversely proportional to the ligand profile. While the same can be obtained using multivalent nanoparticles, the entropic effects due to polymer conformations significantly enhance the binding selectivity of multivalent polymers compared to nanoparticles. Surprisingly, the ligand distribution on the polymer plays a crucial role, whereas the persistence length does not. The optimal selectivity to the overall receptor concentration is obtained by the Poisson distribution of ligands (random copolymer), whereas the maximal selectivity to a specific receptor profile is obtained by a defined sequence of grouped alternating ligands (regular copolymer). Interestingly, the regular copolymer can become anti-selective when ligands of the same type are in homogenous blocks, showing that specific ligand distribution qualitatively affects the targeting ability. These findings suggest that sequence control is necessary to selectively target a specific density profile of membrane receptors using linear copolymers.

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Vid Ravnik, Urban Bren, Tine Curk. 2026-05-26. Designing Multivalent Copolymers for Selective Targeting of Multicomponent Surfaces. https://doi.org/10.1021/acs.macromol.4c00541

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