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Updated: Jul 24, 2026

High-throughput Detection Method for Influenza Virus
Published on: February 4, 2012
Peptide-Based Flavivirus Biosensors: From Cell Structure to Virological and Serological Detection Methods
Atqiya Muslihati1,2,3, Ni Luh Wulan Septiani2,4, Gilang Gumilar5
1Doctoral Program of Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Ganesha 10, Bandung 40132, Indonesia.
Abstract:
In tropical and developing countries, mosquito-borne diseases by flaviviruses pose a serious threat to public health. Early detection is critical for preventing their spread, but conventional methods are time-consuming and require skilled technicians. Biosensors have been developed to address this issue, but cross-reactivity with other flaviviruses remains a challenge. Peptides are essentially biomaterials used in diagnostics that allow virological and serological techniques to identify flavivirus selectively. This biomaterial originated as a small protein consisting of two to 50 amino acid chains. They offer flexibility in chemical modification and can be easily synthesized and applied to living cells in the engineering process. Peptides could potentially be developed as robust, low-cost, sensitive, and selective receptors for detecting flaviviruses. However, modification and selection of the receptor agents are crucial to determine the effectiveness of binding between the targets and the receptors. This paper addresses two potential peptide nucleic acids (PNAs) and affinity peptides that can detect flavivirus from another target-based biosensor as well as the potential peptide behaviors of flaviviruses. The PNAs detect flaviviruses based on the nucleotide base sequence of the target's virological profile via Watson-Crick base pairing, while the affinity peptides sense the epitope or immunological profile of the targets. Recent developments in the functionalization of peptides for flavivirus biosensors are explored in this Review by division into electrochemical, optical, and other detection methods.
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