Platinum-Group Metal Nanoparticles as Peroxidase Mimics: Implications for Biosensing

Platinum-Group Metal Nanoparticles as Peroxidase Mimics: Implications for Biosensing
复制标题

DOI:
10.1021/acsanm.2c03365
复制
发表时间:
2022-12
影响因子:
5.9
通讯作者:
Alexander Biby;Harry E. Crawford;Xiaohu Xia
Alexander Biby;Harry E. Crawford;Xiaohu Xia
中科院分区:
材料科学2区
文献类型:
--
作者:
Alexander Biby;Harry E. Crawford;Xiaohu Xia

文献摘要

相似文献

在过去的几十年里,由铂族金属纳米颗粒(PGM NPs)制成的过氧化物酶模拟物已经被积极开发并应用于各种生物传感平台。然而,目前还缺乏一个全面的研究,比较的过氧化物酶样活性的PGM纳米颗粒和它们的性能在生物传感。在这里,我们报告了一个系统的研究PGM纳米粒子作为过氧化物酶模拟物,包括钯,铂,铑,铱纳米粒子。这些元素的纳米粒子被均匀地合成,并探测它们的纳米级特征,以确保表面上一致的尺寸、形状和化学配体。我们的测量结果表明,Ir NP是最活跃的一个,催化常数高达6.27 × 105 s-1,其次是Pt,Rh和Pd NP。还定量分析和比较了催化过程中纳米粒子与过氧化物酶底物的结合亲和力。使用酶联免疫吸附测定作为模型生物传感平台,评估PGM NPs在检测癌胚抗原(癌症生物标志物)中的性能。结果表明,检测灵敏度与PGM NPs的催化活性相关,其中Ir NPs达到最高灵敏度,检测限在低皮克/毫升的水平。
Over the past few decades, peroxidase mimics made of platinum-group metal nanoparticles (PGM NPs) have been actively developed and applied to various biosensing platforms. Nevertheless, there is a lack of a comprehensive study that compares the peroxidase-like activities of PGM NPs and their performance in biosensing. Here, we report a systematic study of PGM NPs as peroxidase mimics, including Pd, Pt, Rh, and Ir NPs. NPs of these elements were uniformly synthesized and their nanoscale features were probed to ensure a consistent size, shape, and chemical ligand on the surface. Our measurements indicate that the Ir NP is the most active one with a catalytic constant as high as 6.27 × 105s–1, followed by Pt, Rh, and Pd NPs. The binding affinities of NPs to peroxidase substrates during catalysis were also quantitively analyzed and compared. Using enzyme-linked immunosorbent assay as a model biosensing platform, the performance of PGM NPs in detecting carcinoembryonic antigen (a cancer biomarker) was evaluated. The results showed that the detection sensitivity was correlated to the catalytic activity of PGM NPs, where Ir NPs achieved the highest sensitivity with a limit of detection at the level of low picogram per milliliter.