Overview of Molecularly Imprinted Polymer-Based Optical Biosensors for Protein Detection

Protein biomarkers play an indispensable role in the early diagnosis, prognosis assessment, therapeutic monitoring, and treatment evaluation of diseases. Optical biosensors have emerged as promising alternatives for protein detection due to their label-free, real-time, and highly sensitive characteristics. Molecularly imprinted polymers (MIPs), known as “plastic antibodies,” can provide chemically stable, low-cost, and tailorable recognition elements through the formation of target-complementary cavities in polymer matrices, making them highly attractive for integration with optical sensing platforms. In this work, we systematically summarize the advances in MIP-based optical biosensors for protein detection. The fundamental principles of biosensors and recognition elements are introduced, followed by a brief overview of the key components of imprinting technology, such as imprinting materials, functional monomers, cross-linking agents, polymerization mechanisms, template fixation strategies, and template removal conditions. Then, we comprehensively evaluate the integration of MIPs with various optical transduction techniques, including fluorescence, chemiluminescence, electrochemiluminescence, surface-enhanced Raman scattering, colorimetry, and surface plasmon resonance. Finally, the major challenges are discussed, and future development directions are proposed. This review aims to provide systematic theoretical references and useful insights for the rational design, performance improvement, and clinical translation of MIP-based optical biosensors for protein detection.

Authors

Institutions

Publication Details

Journal
Biosensors
Published
2026-10-26
DOI
https://doi.org/10.3390/bios16110606
Primary Topic
Analytical chemistry methods development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Overview of Molecularly Imprinted Polymer-Based Optical Biosensors for Protein Detection

Fengli Gao, Ning Xia, Xinyao Yi, Shuang Li et al.
Biosensors
Analytical chemistry methods development
article

Overview of Molecularly Imprinted Polymer-Based Optical Biosensors for Protein Detection

Fengli Gao, Ning Xia, Xinyao Yi, Shuang Li, Shixuan Zhang, Ruohan Wang, Yaoxing Mao
article en

Abstract

Protein biomarkers play an indispensable role in the early diagnosis, prognosis assessment, therapeutic monitoring, and treatment evaluation of diseases. Optical biosensors have emerged as promising alternatives for protein detection due to their label-free, real-time, and highly sensitive characteristics. Molecularly imprinted polymers (MIPs), known as “plastic antibodies,” can provide chemically stable, low-cost, and tailorable recognition elements through the formation of target-complementary cavities in polymer matrices, making them highly attractive for integration with optical sensing platforms. In this work, we systematically summarize the advances in MIP-based optical biosensors for protein detection. The fundamental principles of biosensors and recognition elements are introduced, followed by a brief overview of the key components of imprinting technology, such as imprinting materials, functional monomers, cross-linking agents, polymerization mechanisms, template fixation strategies, and template removal conditions. Then, we comprehensively evaluate the integration of MIPs with various optical transduction techniques, including fluorescence, chemiluminescence, electrochemiluminescence, surface-enhanced Raman scattering, colorimetry, and surface plasmon resonance. Finally, the major challenges are discussed, and future development directions are proposed. This review aims to provide systematic theoretical references and useful insights for the rational design, performance improvement, and clinical translation of MIP-based optical biosensors for protein detection.

BiosensorsVol. 16(11)
Central South University (CN), Anyang Normal University (CN)
Openalex Percentile: Top 18%
Analytical chemistry methods development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon