Highly Sensitive Protein Analysis Using Chiral Plasmonic Hotspots

— A New Hydrogel-Assisted Raman Platform for Trace Protein Analysis —

A research group led by Associate Professor Hideyuki Mitomo at the Research Institute for Electronic Science (RIES), Hokkaido University, has developed a new plasmonic sensing platform that enables highly sensitive analysis of protein chirality from trace amounts of sample. The platform combines peptide-modified chiral plasmonic nanostructures with a hydrogel that concentrates proteins into plasmonic hotspots, enabling highly sensitive chirality-dependent Raman measurements.

Protein chirality reflects the three-dimensional arrangement of biomolecules and is closely related to their biological functions. Conventional Raman optical activity (ROA) can provide such structural information, but the technique generally requires relatively large sample amounts and long acquisition times because of its inherently weak signals. Developing a practical alternative capable of probing molecular chirality from minute quantities of protein has therefore remained an important challenge.

In this study, the researchers developed chiral-AuTAG, a hydrogel-integrated plasmonic platform based on peptide-modified chiral gold nanoparticle assemblies. As proteins are transported into plasmonic hotspots during hydrogel shrinkage, Raman signals are strongly enhanced. By comparing measurements obtained on left- and right-handed chiral substrates, the platform extracts chirality-dependent Raman responses that reflect structural differences in proteins.

The researchers successfully demonstrated sensitive chirality-dependent Raman measurements of several proteins. The platform enables chirality-dependent Raman measurements with significantly reduced sample requirements and measurement times compared with conventional ROA, while providing structural information related to molecular chirality.

This work provides a practical platform for obtaining protein information that includes structural features. By incorporating structural information into highly sensitive protein detection, the technology may advance protein analysis and create new opportunities for biomarker research, the study of disease-associated proteins, including glycated proteins such as HbA1c, and future diagnostic technologies.

This research was published in ACS Sensors on August 16, 2026.

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