反褶积
质谱
质谱法
电喷雾电离
质量分布
谱线
化学物理
电荷(物理)
化学
计算物理学
生物系统
分析化学(期刊)
物理
统计物理学
计算机科学
天体物理学
算法
色谱法
生物
银河系
量子力学
作者
Marius Kostelic,Michael T. Marty
出处
期刊:Methods in molecular biology
日期:2022-01-01
卷期号:: 159-180
被引量:5
标识
DOI:10.1007/978-1-0716-2325-1_12
摘要
Intact protein, top-down, and native mass spectrometry (MS) generally requires the deconvolution of electrospray ionization (ESI) mass spectra to assign the mass of components from their charge state distribution. For small, well-resolved proteins, the charge can usually be assigned based on the isotope distribution. However, it can be challenging to determine charge states with larger proteins that lack isotopic resolution, in complex mass spectra with overlapping charge states, and in native spectra that show adduction. To overcome these challenges, UniDec uses Bayesian deconvolution to assign charge states and to create a zero-charge mass distribution. UniDec is fast, user-friendly, and includes a range of advanced tools to assist in intact protein, top-down, and native MS data analysis. This chapter provides a step-by-step protocol and an in-depth explanation of the UniDec algorithm, and highlights the parameters that affect the deconvolution. It also covers advanced data analysis tools, such as macromolecular mass defect analysis and tools for assigning potential PTMs and bound ligands. Overall, this chapter provides users with a deeper understanding of UniDec, which will enhance the quality of deconvolutions and allow for more intricate MS experiments.
科研通智能强力驱动
Strongly Powered by AbleSci AI