2020

Highly specific recognition of denatured collagen by fluorescent peptide probes with the repetitive Gly-Pro-Pro and Gly-Hyp-Hyp sequences.

Journal of materials chemistry. B Wei W, Li D, Cai X, Liu Z, Bai Z, Xiao J
阅读原文 PDF DOI PubMed

组成图示

示意图生成中

传感器类型

检测对象

检测原理

检测灵敏度

效应效果

传感器的构成

中文摘要

英文摘要

Denatured collagen is a key biomarker for various critical diseases such as cancer. Peptide probes with the repetitive (Gly-Pro-Hyp)n sequences have recently been found to selectively target denatured collagen; however, thermal or UV pretreatment is required to drive the peptides into the monomer conformation, which poses a substantial challenge for clinical applications. We herein construct two peptide probes, FAM-GOO and FAM-GPP, consisting of the repetitive (Gly-Hyp-Hyp)8 and (Gly-Pro-Pro)8 sequences, respectively. The CD, fluorescence and colorimetric studies have consistently revealed that FAM-GOO showed strong capability of forming the triple helical structure, while FAM-GPP pronouncedly displayed the single stranded conformation at temperatures as low as 4 °C. The binding experiments have indicated that both peptide probes could recognize denatured collagen with high specificity, and FAM-GPP remarkably did not need the preheating treatment. The tissue staining results have shown that preheated FAM-GOO and unheated FAM-GPP could target denatured collagen in a wide variety of rat frozen and human FFPE tissue sections. Compared with antibodies specific for a certain type of collagen, both FAM-GOO and FAM-GPP act as broad-spectrum probes for the selective detection of denatured collagen of different types and from different species. Importantly, FAM-GPP possessed the unique capability of maintaining the monomer conformation by itself, thus avoiding the potential risks of the thermal or UV pretreatment. This novel peptide probe provides a handy and versatile biosensor for specifically targeting denatured collagen, which has attractive potential in the diagnosis and therapeutics of collagen-involved diseases.

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