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Modular Input-Output Biosensor Design Using De Novo Protein Switches
James Wang1, Julie Yi-Hsuan Chen1, Chenggang Xi1
1Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, United States.
ACS Sensors
|June 3, 2026
Summary
Researchers developed a versatile biosensor platform called LOCKR. This plug-and-play system efficiently links molecular binding events to detectable signals, enabling sensitive detection of various peptides.
Area of Science:
- Biotechnology
- Molecular Biology
- Sensor Technology
Background:
- Protein-based biosensors offer real-time detection with minimal sample preparation, surpassing conventional methods.
- A significant challenge in biosensor development is effectively translating molecular recognition into a reliable signal output.
Purpose of the Study:
- To introduce the LOCKR (Ligand-Oriented Combinatorial Kinase-Regulated) platform, a novel plug-and-play strategy for biosensor development.
- To demonstrate the modularity of the LOCKR platform by enabling interchangeable recognition domains and reporter modules for diverse analyte detection and signal output formats.
Main Methods:
- The LOCKR platform was designed for modular reconfiguration, allowing for the swapping of recognition domains and reporter modules.
- The study expanded LOCKR-compatible readouts to include Förster-type resonance energy transfer (FRET) and β-lactamase-based colorimetry, in addition to split luciferase.
- Computationally designed high-affinity binders were integrated as recognition elements for specific analyte detection.
Main Results:
- The LOCKR platform successfully enabled direct signal transduction from molecular binding events.
- Sensitive detection of glucagon, neuropeptide Y, and peptide YY was achieved, with limits of detection in the picomolar range.
- The platform demonstrated versatility by supporting multiple readout formats, including FRET and colorimetry.
Conclusions:
- The LOCKR platform provides a flexible and efficient solution for bridging molecular recognition and signal generation in biosensors.
- This modular approach facilitates the development of tailored biosensors for various user-defined applications.
- The integration of computationally designed binders enhances the sensitivity and specificity of the developed biosensors.
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