A bioinspired fluorescent probe based on metal–organic frameworks to selectively enrich and detect amyloid-β peptide

荧光 化学 检出限 选择性 配体(生物化学) 金属有机骨架 组合化学 生物物理学 生物化学 色谱法 受体 有机化学 生物 量子力学 物理 吸附 催化作用
作者
Wang Zi-yuan,Yi Jiao,Qingyuan Ding,Song Yanjie,Qingqing Ma,Huan Ren,Kun Lü,Shiru Jia,Jiandong Cui
出处
期刊:Chemical Engineering Journal [Elsevier BV]
卷期号:470: 144124-144124 被引量:12
标识
DOI:10.1016/j.cej.2023.144124
摘要

Amyloid-β peptide (Aβ) in serum is an effective biomarker for the early diagnosis of Alzheimer's disease (AD). However, there are serious challenges to monitor subtle changes of Aβ in the blood due to its low expression and the complex interference from the environment. Inspired by the delicate structure of natural enzymes, the metal site coordination, hydrophobic microenvironment, and the size selectivity feature, herein, a fluorescent probe based on bi-ligand zinc metal–organic frameworks is designed for accurate detection of Aβ in serum. By chelating with Zn2+, the fluorescent small molecule N-(6-(benzothiazol-2-yl)pyridin-3-yl)-5-(dimethylamino)naphthalene-1-sulfonamide (BPNS) participated in the self-assembly process as one of the organic linkers to form this novel flower-shaped probe Zn-FBIFs. As proposed, the synergism of hydrophobic nature and size-exclusion effect made Zn-FBIFs can rapidly and selectively enrich Aβ and exhibit excellent anti-interference ability towards interfering proteins in serum. Then by competitively binding to Zn2+, Aβ replaced the BPNS in Zn-FBIFs and the released BPNS gave a fluorescence signal for Aβ detection. The detection limit in undiluted serum was as low as 3.22 nM and that was two orders of magnitude decreased compared with the reported detection limit by BPNS calculated in 80-fold diluted serum. The results demonstrated our proposal of the bioinspired probe is effective in significantly improving the detection accuracy and that would give new insight into the development of novel probes for trace substance detection in complex biosamples.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
彭于晏应助猫车高手采纳,获得10
刚刚
薯片发布了新的文献求助10
刚刚
Jokerc发布了新的文献求助10
1秒前
小王发布了新的文献求助10
1秒前
1秒前
跳跃的玉米完成签到,获得积分10
1秒前
大模型应助zz采纳,获得10
2秒前
00hello00发布了新的文献求助10
2秒前
科研通AI2S应助自然的冬莲采纳,获得10
2秒前
3秒前
罗恩发布了新的文献求助10
3秒前
细腻冰岚发布了新的文献求助10
3秒前
peike完成签到,获得积分10
3秒前
orixero应助小槿采纳,获得10
3秒前
小杨完成签到,获得积分10
5秒前
华仔应助yyyxxx采纳,获得10
6秒前
qqs发布了新的文献求助10
6秒前
4324发布了新的文献求助10
6秒前
小二郎应助prigogin采纳,获得10
7秒前
Haucicy发布了新的文献求助10
8秒前
baijiaxiaoshaoye完成签到,获得积分10
9秒前
Jokerc完成签到,获得积分10
9秒前
9秒前
sanshu发布了新的文献求助10
10秒前
11秒前
完美世界应助辞忧采纳,获得10
12秒前
12秒前
12秒前
13秒前
传奇3应助prigogin采纳,获得10
13秒前
灵巧怀曼完成签到,获得积分10
14秒前
14秒前
14秒前
朗朗书生发布了新的文献求助10
15秒前
Hodlumm完成签到,获得积分10
15秒前
16秒前
神勇芝麻发布了新的文献求助10
16秒前
阿萨十大完成签到,获得积分20
16秒前
zz发布了新的文献求助10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Römisch-Germanische Forschungen 1000
The Oxford Handbook of Digital Classical Studies 550
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7618047
求助须知:如何正确求助?哪些是违规求助? 9193289
关于积分的说明 19703470
捐赠科研通 7190486
什么是DOI,文献DOI怎么找? 3272095
关于科研通互助平台的介绍 2434881
邀请新用户注册赠送积分活动 2267339