Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, USA.
Bio5 Institute, University of Arizona, Tucson, AZ, USA.
Methods Mol Biol. 2022;2500:159-180. doi: 10.1007/978-1-0716-2325-1_12.
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.
完整蛋白、自上而下和天然质谱（MS）通常需要解卷积电喷雾电离（ESI）质谱，以根据其电荷状态分布分配组件的质量。对于小而分辨率良好的蛋白质，通常可以根据同位素分布来确定电荷状态。然而，对于缺乏同位素分辨率、在重叠电荷状态的复杂质谱中以及在显示加合的天然光谱中较大的蛋白质，确定电荷状态可能具有挑战性。为了克服这些挑战，UniDec 使用贝叶斯解卷积来分配电荷状态并创建零电荷质量分布。UniDec 快速、用户友好，并且包含一系列高级工具来协助完整蛋白、自上而下和天然 MS 数据分析。本章提供了 UniDec 算法的分步协议和深入解释，并强调了影响解卷积的参数。它还涵盖了高级数据分析工具，如大分子质量缺陷分析和用于分配潜在 PTM 和结合配体的工具。总的来说，本章为用户提供了对 UniDec 的更深入了解，这将提高解卷积的质量，并允许进行更复杂的 MS 实验。
