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Science Advances
Article . 2025 . Peer-reviewed
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Science Advances
Article . 2025
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Decoding aptamer-protein binding kinetics for continuous biosensing using single-molecule techniques

Authors: Mike Filius; Lena Fasching; Raman van Wee; Alina Y. Rwei; Chirlmin Joo;

Decoding aptamer-protein binding kinetics for continuous biosensing using single-molecule techniques

Abstract

Continuous biosensing provides real-time information about biochemical processes and holds great potential for health monitoring. Aptamers have emerged as promising alternatives over traditional biorecognition elements. However, the underlying aptamer-target binding interactions are often poorly understood. Here, we present a technique that can decode aptamer-protein binding interactions at the single-molecule level. We demonstrate that our single-molecule assay is able to decode the underlying binding kinetics of aptamers despite their similar binding affinity. Guided by computational simulations and validated with quartz crystal microbalance experiments, we show that the quantitative insights generated by this single-molecule technique enabled the rational understanding of biosensor performance (i.e., the sensitivity and limit of detection). This capability was demonstrated with thrombin as the analyte and the structurally similar aptamers HD1, RE31, and NU172 as the biorecognition elements. This work decodes aptamer-protein interactions with high temporal resolution, paving the way for the rational design of aptamer-based biosensors.

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Keywords

Kinetics, Thrombin, Quartz Crystal Microbalance Techniques, Humans, Physical and Materials Sciences, Biosensing Techniques, Aptamers, Nucleotide, Single Molecule Imaging, Protein Binding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%
Green
gold
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