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Updated: Jan 16, 2026

Peptide and Protein Quantification Using Automated Immuno-MALDI iMALDI

Peptide and Protein Quantification Using Automated Immuno-MALDI iMALDI

Published on: August 18, 2017

标记的定量MALDIMS分析─选细菌结合从一个甘氨酸-拉链图书馆

Liao Hu¹, C Logan Mackay², David J Clarke¹

¹EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, EH9 3FJ Edinburgh, U.K.

ACS chemical biology

|October 2, 2025

概括

这项研究引入了一种基于的标签方法,用于使用MALDI FT-ICR MS. 的精确化量化. 这种技术增强了高通量查,以发现细菌结合.

科学领域:

分析化学分析化学
生物化学生物化学
质谱测量质量谱测量

背景情况:

矩阵辅助激光吸附离子化质谱 (MALDI MS) 提供速度和灵敏度,但缺乏定量准确性.
这种限制阻碍了其在高通量选和其他定量分析中的应用.
准确的量化对于药物发现和生物标志物识别等应用至关重要.

研究的目的:

使用高分辨率的MALDI FT-ICRMS开发一种新的标签策略,以准确量化.
为了使类库可靠的高通量选,以识别功能性.
克服传统MALDI MS.固有的非定量性质.

主要方法:

开发了一种基于的标签策略,使用酸 (BA) 和4-酸 (IBA) 进行N终端标签.
通过在上替换单个原子来生成内部标准.
使用四个混合物验证了该方法,并将其应用于选抗*Escherichia coli*和*Bacillus subtilis*的甘氨酸-拉链图书馆.

主要成果:

通过使用MALDI FT-ICR MS的标注策略,可以准确量化和库.
对类库的选确定了具有强烈和选择性结合格兰氏阴性和格兰氏阳性细菌的类.
该方法在定量分析中显示出高可靠性和准确性.

结论:

基于的标签策略为的量化提供了一个普遍适用的,具有成本效益的,简单的方法.
这种方法显著提高了通过MALDI FT-ICR MS的高通量体查的准确性和可靠性.
开发的技术有助于发现功能性,例如那些与细菌相互作用的.

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