Optimality in superselective surface binding by multivalent DNA nanostars

TL;DR

This study demonstrates that multivalent DNA nanostars can exhibit superselective surface binding, with an optimal valency of three, explained by extended theoretical models including ligand interactions, advancing understanding of selective targeting mechanisms.

Contribution

It introduces a multivalent DNA nanostar system to explore superselectivity with few ligands and extends existing theory to include ligand interactions, revealing optimal binding conditions.

Findings

DNA nanostars bind superselectively to surfaces.

Optimal binding occurs at a valency of three.

Extended theory explains the ligand interaction effects.

Abstract

Weak multivalent interactions govern a large variety of biological processes like cell-cell adhesion and virus-host interactions. These systems distinguish sharply between surfaces based on receptor density, known as superselectivity. Earlier experimental and theoretical work provided insights into the control of selectivity: Weak interactions and a high number of ligands facilitate superselectivity. Present experimental studies typically involve tens or hundreds of interactions, resulting in a high entropic contribution leading to high selectivities. However, if, and if so how, systems with few ligands, such as multi-domain proteins and virus binding to a membrane, show superselective behavior is an open question. Here, we address this question with a multivalent experimental model system based on star shaped branched DNA nanostructures (DNA nanostars) with each branch featuring a single stranded overhang that binds to complementary receptors on a target surface. Each DNA nanostar possesses a fluorophore, to directly visualize DNA nanostar surface adsorption by total internal reflection fluorescence microscopy (TIRFM). We observe that DNA nanostars can bind superselectively to surfaces and bind optimally at a valency of three. We quantitatively explain this optimum by extending the current theory with interactions between DNA nanostar binding sites (ligands). Our results add to the understanding of multivalent interactions, by identifying microscopic mechanisms that lead to optimal selectivity, and providing quantitative values for the relevant parameters. These findings inspire additional design rules which improve future work on selective targeting in directed drug delivery.