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简约电荷去卷积用于天然质谱。

Parsimonious Charge Deconvolution for Native Mass Spectrometry.

机构信息

Protein Metrics, Inc. , San Carlos, California 94070, United States.

Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Science4Life, Utrecht University and Netherlands Proteomics Centre , Padualaan 8, 3584 CH Utrecht, The Netherlands.

出版信息

J Proteome Res. 2018 Mar 2;17(3):1216-1226. doi: 10.1021/acs.jproteome.7b00839. Epub 2018 Feb 8.

Abstract

Charge deconvolution infers the mass from mass over charge (m/z) measurements in electrospray ionization mass spectra. When applied over a wide input m/z or broad target mass range, charge-deconvolution algorithms can produce artifacts, such as false masses at one-half or one-third of the correct mass. Indeed, a maximum entropy term in the objective function of MaxEnt, the most commonly used charge deconvolution algorithm, favors a deconvolved spectrum with many peaks over one with fewer peaks. Here we describe a new "parsimonious" charge deconvolution algorithm that produces fewer artifacts. The algorithm is especially well-suited to high-resolution native mass spectrometry of intact glycoproteins and protein complexes. Deconvolution of native mass spectra poses special challenges due to salt and small molecule adducts, multimers, wide mass ranges, and fewer and lower charge states. We demonstrate the performance of the new deconvolution algorithm on a range of samples. On the heavily glycosylated plasma properdin glycoprotein, the new algorithm could deconvolve monomer and dimer simultaneously and, when focused on the m/z range of the monomer, gave accurate and interpretable masses for glycoforms that had previously been analyzed manually using m/z peaks rather than deconvolved masses. On therapeutic antibodies, the new algorithm facilitated the analysis of extensions, truncations, and Fab glycosylation. The algorithm facilitates the use of native mass spectrometry for the qualitative and quantitative analysis of protein and protein assemblies.

摘要

电荷去卷积通过解卷积质荷比 (m/z) 测量值来推断质量。当应用于较宽的输入 m/z 或较宽的目标质量范围时,电荷去卷积算法可能会产生伪质量,例如在正确质量的一半或三分之一处出现伪质量。事实上,MaxEnt(最常用的电荷去卷积算法)目标函数中的最大熵项倾向于具有许多峰的去卷积光谱,而不是具有较少峰的去卷积光谱。这里我们描述了一种新的“简约”电荷去卷积算法,该算法产生的伪质量更少。该算法特别适合于完整糖蛋白和蛋白质复合物的高分辨率天然质谱。由于盐和小分子加合物、多聚体、宽质量范围以及较少和较低的电荷状态,天然质谱的去卷积具有特殊的挑战。我们在一系列样品上展示了新去卷积算法的性能。在高度糖基化的血浆调理蛋白糖蛋白上,新算法可以同时对单体和二聚体进行去卷积,并且当聚焦于单体的 m/z 范围时,对于先前使用 m/z 峰而不是去卷积质量进行手动分析的糖型,给出了准确且可解释的质量。在治疗性抗体上,新算法促进了扩展、截断和 Fab 糖基化的分析。该算法促进了天然质谱在蛋白质和蛋白质组装的定性和定量分析中的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b300/5838638/7cc4c12b90e8/pr-2017-008393_0001.jpg

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