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Updated: Jun 11, 2025

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

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在R (coADAPTr) 中用于高吞吐量的共价标签自动化数据分析平台:用于共价标签实验的全蛋白体数据分析平台

Raquel L Shortt¹, Lindsay K Pino², Emily E Chea³

¹Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland 21201, United States.

Journal of the American Society for Mass Spectrometry

|October 2, 2024

概括

我们开发了coADAPTr,这是一个开源软件,用于分析共价标记质谱数据. 这种工具显著加快了全蛋白质组结构分析,为蛋白质结构研究提供了更高的准确性和图形解释.

科学领域:

结构生物学结构生物学
蛋白质组学是指蛋白质组学.
生物化学生化学

背景情况:

与质谱学相结合的共价标签对于研究蛋白质高阶结构至关重要.
量化不同状态的蛋白质修饰揭示了相互作用部位和构造变化.
现有的量化软件可能会耗费大量时间,特别是在全蛋白质组研究中.

研究的目的:

介绍coADAPTr,一个开源软件,用于有效量化共价标记质谱.
为传统分析方法提供更快,更易于使用的替代方案,如Excel的Power Pivot.
为了实现高吞吐量,全蛋白质组结构洞察力与改进的数据解释.

主要方法:

开发一个开源软件平台,coADAPTr,使用R.
实施功能以提高数据保真度和吞吐量,包括重复数据过器和算术平均数量计.
模仿PowerPivot的基本功能,以进行简化分析.

主要成果:

与传统方法相比,coADAPTr处理共价标记质谱数据的速度高达200倍.
验证研究证实了coADAPTr的准确性和效率.
该软件提供了增强的图形解释,以获得全蛋白质组的洞察力.

结论:

coADAPTr在结构蛋白质组学数据分析方面取得了重大进展.
它的开源性质和用户友好的界面使其可用于各种研究应用.
该平台使研究人员能够有效地解读复杂的结构生物学数据,这些数据来自诸如基蛋白足迹 (HRPF) 等方法.

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