# Scalable Multiparametric Characterization of Aptamer–Target Interactions

## TL;DR

This paper introduces a scalable platform to study how aptamers change shape when binding targets, enabling better design of biosensors for detecting small molecules.

## Contribution

A scalable microfluidic platform integrating FRET and imaging for high-resolution profiling of aptamer–target interactions.

## Key findings

- The platform enables detailed analysis of aptamer–target interactions in picoliter volumes across millisecond-to-hour timescales.
- Structure–function relationships of serotonin aptamers were systematically explored to select optimal candidates for biosensing.
- The system bridges low-throughput structural analysis with rapid, multiparametric readouts for translational biosensor development.

## Abstract

Structure-switching aptamers transduce target-induced
conformational
changes into detectable signals, enabling the specific detection of
small molecules with limited surface area and charge. Understanding
these structural transitions is critical for the rational design of
aptamers in downstream biosensing. However, current methods lack the
scalability and high spatiotemporal resolution to characterize and
resolve these structural dynamics within a single unified platform.
Here, we report a scalable droplet microfluidic platform that fills
this technological gap by integrating Förster resonance energy
transfer with automated imaging for the multiparametric profiling
of aptamer–target interactions. This integrated system enables
the detailed analysis of aptamer–target interactions in picoliter
volumes under physiologically relevant conditions across the millisecond-to-hour
time scales. Investigating serotonin aptamers with varying stem lengths,
we systematically explore structure–function relationships
and translate molecular-level insights into the application-driven
selection of optimal candidates. By bridging low-throughput structural
characterization with a rapid, low-volume, and multiparametric readout,
our platform overcomes a key barrier in translational biosensor development
and lays the foundation for data-driven engineering of structure-switching
aptamers tailored for diagnostics and beyond.