School of Environment and Civil Engineering, Dongguan University of Technology, Dongguan, 523808, China.
School of Environment, South China Normal University, Guangdong Provincial Engineering Technology Research Center for Wastewater Management and Treatment, Guangzhou, 510006, China.
Colloids Surf B Biointerfaces. 2021 Apr;200:111574. doi: 10.1016/j.colsurfb.2021.111574. Epub 2021 Jan 12.
We propose a colorimetric sensing array consisting of 4-aminothiophenol (p-ATP)-modified gold nanoparticles (Au NPs), silver nanoparticles (Ag NPs), and core-shell Au@Ag nanocubes (Au@Ag NCs) as sensing elements to identify multiple proteins according to the diverse colorimetric response patterns. In the absence of proteins, the sensor element solution itself did not agglomerate. After interacting with six proteins (lysozyme (LZM), hemoglobin (HGB), peroxidase from horseradish (HRP), bovine liver from peroxidase (CAT), trypsin from bovin pancreas (TRY), and pepsin (PEP)), due to the different binding ability between the sensing elements and various proteins, the sensing array exhibits a unique pattern of colorimetric variations, linear discrimination analysis (LDA) was applied to analyze the pattern and produced a clustering map for a clearer differentiation of these proteins.
我们提出了一个由 4-巯基苯胺（p-ATP）修饰的金纳米粒子（Au NPs）、银纳米粒子（Ag NPs）和核壳 Au@Ag 纳米立方（Au@Ag NCs）组成的比色传感阵列，作为传感元件，根据不同的比色响应模式来识别多种蛋白质。在没有蛋白质的情况下，传感器元件溶液本身不会聚集。与六种蛋白质（溶菌酶（LZM）、血红蛋白（HGB）、辣根过氧化物酶（HRP）、牛肝过氧化物酶（CAT）、牛胰蛋白酶（TRY）和胃蛋白酶（PEP））相互作用后，由于传感元件与各种蛋白质之间的不同结合能力，比色传感阵列呈现出独特的比色变化模式，应用线性判别分析（LDA）对该模式进行分析，并生成聚类图，以便更清晰地区分这些蛋白质。
