Sensitive detection of α-amylase based on host-guest inclusion system of γ-cyclodextrin and dansyl-derived diphenylalanine.

Dansyl Fluorescent probe Host–guest recognition α-Amylase

Journal

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
ISSN: 1873-3557
Titre abrégé: Spectrochim Acta A Mol Biomol Spectrosc
Pays: England
ID NLM: 9602533

Informations de publication

Date de publication:
16 Oct 2024
Historique:
received: 13 08 2024
revised: 10 10 2024
accepted: 13 10 2024
medline: 21 10 2024
pubmed: 21 10 2024
entrez: 20 10 2024
Statut: aheadofprint

Résumé

A highly sensitive detection system for α-amylase was developed via host-guest complexation between γ-cyclodextrin and dansyl-modified diphenylalanine (FF-Dns). The host-guest inclusion of FF-Dns into the cavity of γ-CD in a HEPES buffer solution (10 mM, pH 7.4) significantly enhanced the fluorescence intensity, and the emission wavelength gradually shifted from 558 to 535 nm. The hydrolysis of γ-CD by the addition of α-amylase released FF-Dns, leading to the recovery of the fluorescence emission characteristics. Therefore, the FF-Dns/γ-CD host-guest complexation system can serve as a platform for the sensitive detection of α-amylase with good selectivity against potential interference. The limit of detection (LOD) of the system was 0.004 U/mL, with a linear working range of 0-6 U/mL. The detection assay was successfully applied in 0.1 % serum, achieving an LOD of 0.017 U/mL and a linear working range of 0-10 U/mL.

Identifiants

pubmed: 39427389
pii: S1386-1425(24)01457-4
doi: 10.1016/j.saa.2024.125291
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

125291

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Yu Liu (Y)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China.

Yutian Jiao (Y)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China.

Longjun Xiong (L)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China.

Gongli Wei (G)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China.

Baocai Xu (B)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China.

Guiju Zhang (G)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China.

Ce Wang (C)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China.

Li Zhao (L)

School of Light Industry, Beijing Technology and Business University, Beijing 100048, PR China. Electronic address: zhaol@btbu.edu.cn.

Classifications MeSH