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Biosensors
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Biosensors Based on Self-Assembly and Molecular Recognition—2nd Edition
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Biosensors Based on Self-Assembly and Molecular Recognition—2nd Edition

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensor and Bioelectronic Devices".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 8218

Special Issue Editor

Dr. Lin Liu

E-Mail Website
Guest Editor
Henan Province of Key Laboratory of New Optoelectronic Functional Materials, Anyang Normal University, Anyang, China
Interests: biosensors; electrocatalysts; self-assembly; metal–peptide complexes; nanomaterials; signal amplification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biosensors show promising prospects in the assays of various targets due to their advantages of high sensitivity, good selectivity, and rapid response. Self-assembled nanomaterials have witnessed tremendous progress in a variety of biosensing and biomedical applications due to their intriguing characteristics, such as facile processability, structure tailoring, and excellent biocompatibility. Molecular recognition is a key event for the development of biosensors. General methods for molecular recognition include covalent coupling reactions and non-covalent interactions of antigen–antibody, aptamer–target, glycan–lectin, avidin–biotin and boronic acid–diol. Various materials have been prepared and used as synthetic receptors for the specific recognition and detection of biomolecules. Contributions to this Special Issue should cover advances in biosensors based on self-assembly and/or molecular recognition. The analytes include small molecules, nucleic acids, proteins, enzymes, exosomes, viruses and cells.

Dr. Lin Liu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Publisher’s Notice

The Special Issue has been added to Section Biosensor and Bioelectronic Devices on 8 September 2025. At the time of the move, there were no publications in this Special Issue.

Keywords

  • biosensors
  • self-assembly
  • molecular recognition
  • boronate affinity
  • metal–organic frameworks
  • covalent organic frameworks
  • hydrogen-bonded organic frameworks
  • organic nanocrystals
  • aggregation-induced emission
  • signal amplification

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Related Special Issue

Published Papers (4 papers)

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Research

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20 pages, 1357 KB  
Article
Fluorescence Immunosensor with Phage Antibodies for Heat Shock Protein 70 Detection
by Olga I. Guliy, Sergei A. Eremin, Liliya I. Mukhametova, Evgeniy S. Kozlov, Vyacheslav S. Grinev, Sergey A. Staroverov, Olga A. Karavaeva, Ksenia K. Fursova, Fedor A. Brovko, Lev A. Dykman and Qingyun Liu
Biosensors 2026, 16(4), 194; https://doi.org/10.3390/bios16040194 - 28 Mar 2026
Viewed by 372
Abstract
The detection of biological markers is critical not only for the early diagnosis of cancer but also for adjustments in antitumor therapy. Rapid, sensitive, and selective detection and monitoring of the content of specific biomarkers in real time are key to point-of-care testing [...] Read more.
The detection of biological markers is critical not only for the early diagnosis of cancer but also for adjustments in antitumor therapy. Rapid, sensitive, and selective detection and monitoring of the content of specific biomarkers in real time are key to point-of-care testing diagnostics. We report the detection of heat shock proteins by fluorescence immunoassay with the appropriate phage antibodies, with a minimum detection limit of 1 ng/mL. The fluorescence immunoassay data were confirmed by dot immunoassay and by circular dichroism studies. The results of the study may help in the adaptation of the fluorescence immunoassay to cancer diagnostics. Full article
(This article belongs to the Special Issue Biosensors Based on Self-Assembly and Molecular Recognition—2nd Edition)
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14 pages, 3170 KB  
Article
Triple-Model Immunoassays with the Self-Assemblies of Three-in-One Small Molecules as Signaling Labels
by Zhaojiang Yu, Wenqi Yuan, Mingyi Qiao and Lin Liu
Biosensors 2025, 15(11), 710; https://doi.org/10.3390/bios15110710 - 24 Oct 2025
Cited by 2 | Viewed by 897
Abstract
Multiple-mode immunoassays have the advantages of self-correction, self-validation, and high accuracy and reliability. In this work, we developed a strategy for the design of triple-mode immunoassays with the self-assemblies of three-in-one small molecules as signal reporters. Pyrroloquinoline quinone (PQQ), with a well-defined redox [...] Read more.
Multiple-mode immunoassays have the advantages of self-correction, self-validation, and high accuracy and reliability. In this work, we developed a strategy for the design of triple-mode immunoassays with the self-assemblies of three-in-one small molecules as signal reporters. Pyrroloquinoline quinone (PQQ), with a well-defined redox peak and excellent spectroscopic and fluorescent signals, was chosen as the signaling molecule. PQQ was coordinated with Cu2+ to form metal–organic nanoparticle as the signal label. Hexahistidine (His6)-tagged recognition element (recombinant streptavidin) was attached to the Cu-PQQ surface through metal coordination interaction between the His6 tag and the unsaturated metal site. The captured Cu-PQQ nanoparticle released a large number of PQQ molecules under an acidic condition, which could be simultaneously monitoring by electrochemical, UV-vis, and fluorescent techniques, thereby allowing for the development of triple-model immunoassays. The three methods were used to determine the concentration of carcinoembryonic antigen (CEA) with the detection limits of 0.01, 0.1, and 0.1 ng/mL, respectively. This strategy opens up a universal route for the preparation of multiple-model signal labels and the oriented immobilization of bioreceptors for molecular recognition. Full article
(This article belongs to the Special Issue Biosensors Based on Self-Assembly and Molecular Recognition—2nd Edition)
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Review

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23 pages, 3772 KB  
Review
Progress in Machine Learning-Assisted Biosensors for Alzheimer’s Disease
by Yan Feng and Changdong Chen
Biosensors 2026, 16(3), 161; https://doi.org/10.3390/bios16030161 - 13 Mar 2026
Viewed by 720
Abstract
Alzheimer’s disease (AD) is the most common cause of dementia, affecting 55 million people worldwide. Its characteristics include the accumulation of senile plaques and neurofibrillary tangles. This disease is associated with changes in the concentration of AD biomarkers, such as microRNAs, amyloid peptides, [...] Read more.
Alzheimer’s disease (AD) is the most common cause of dementia, affecting 55 million people worldwide. Its characteristics include the accumulation of senile plaques and neurofibrillary tangles. This disease is associated with changes in the concentration of AD biomarkers, such as microRNAs, amyloid peptides, Tau protein, and neurofilament light chains. Due to the fact that neuropathological processes begin decades before the onset of cognitive symptoms, accurate detection of AD biomarkers is crucial for its early diagnosis. The combination of analytical techniques and machine learning methods plays a crucial role in medical innovation. Recently, efforts have been made to develop machine learning-assisted biosensors for AD diagnosis. This article provides an overview of the progress in machine learning-assisted sensing of AD biomarkers in bodily fluids. It mainly includes three parts: machine learning algorithms, machine learning-assisted electrochemical and optical biosensors, and challenges and future perspectives. We believe that this work will contribute to the development of innovative analytical devices based on artificial intelligence for monitoring and managing neurodegenerative diseases. Full article
(This article belongs to the Special Issue Biosensors Based on Self-Assembly and Molecular Recognition—2nd Edition)
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26 pages, 5753 KB  
Review
Metal–Phenolic Networks for Sensing Applications
by Ning Xia, Sirui Liang, Dehua Deng, Yong Chang and Xinyao Yi
Biosensors 2025, 15(9), 600; https://doi.org/10.3390/bios15090600 - 11 Sep 2025
Cited by 1 | Viewed by 5843
Abstract
The preparation of new inorganic–organic hybrid materials is beneficial for the development of powerful sensing methods and technologies. Polyphenols, a type of organic molecule containing phenolic hydroxyl groups, are widely present in natural plants and have beneficial effects on human health. Metal ions [...] Read more.
The preparation of new inorganic–organic hybrid materials is beneficial for the development of powerful sensing methods and technologies. Polyphenols, a type of organic molecule containing phenolic hydroxyl groups, are widely present in natural plants and have beneficial effects on human health. Metal ions are ubiquitous in nature and play an important role in the development of inorganic–organic hybrid materials. Metal–phenolic networks (MPNs) are formed by the self-assembly of metal ions and polyphenols through dynamic coordination bonds. Due to their mild synthesis conditions, facilely engineered functionalities, and multiple modification strategies, MPNs have become potential platforms for sensing applications. Timely understanding of the function and application of MPNs in sensing fields will facilitate the development of novel chemical and biological sensors and devices. This article summarizes the typical preparation methods and excellent advantages of MPNs and focuses on their latest achievements in sensing applications. We highlight representative MPN-based sensing examples, including the direct detection of small molecules and biological species, immunoassays, bioimaging, and wearable devices. Finally, the prospects and future directions of MPNs in sensing fields are addressed. Full article
(This article belongs to the Special Issue Biosensors Based on Self-Assembly and Molecular Recognition—2nd Edition)
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