Predicting Electrophoretic Mobility of Proteoforms for Large-Scale Top-Down Proteomics.

Predicting Electrophoretic Mobility of Proteoforms for Large-Scale Top-Down Proteomics.
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DOI:
10.1021/acs.analchem.9b05578
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发表时间:
2020-03-03
影响因子:
7.4
通讯作者:
Sun L
Sun L
中科院分区:
化学1区
文献类型:
--
作者:
Chen D;Lubeckyj RA;Yang Z;McCool EN;Shen X;Wang Q;Xu T;Sun L

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大规模自上而下的蛋白质组学使用反相液相色谱(RPLC)-串联质谱(MS/MS)或毛细管区带电泳(CZE)-MS/MS以高置信度和高通量在全球范围内表征细胞中的蛋白质组。来自靶诱饵数据库搜索的错误发现率(FDR)通常用于过滤已识别的蛋白质组以确保高置信度识别(ID)。已经证明,自上而下的蛋白质组学中的FDR可能被大大低估。FDR的另一种方法可用于在数据库检索后进一步评估蛋白质型ID的置信度。我们认为,准确预测保留/迁移时间的蛋白质型从RPLC/CZE分离,并比较其预测和实验分离时间可能是一个有用的和实用的方法。据我们所知,在文献中还没有关于使用大的自上而下的蛋白质组学数据集预测蛋白质型分离时间的报道。在这项初步研究中,我们第一次使用CZE-MS/MS的大规模自上而下的蛋白质组学数据集评估了各种半经验模型来预测蛋白质型的电泳迁移率(μef)。大肠杆菌蛋白质组(R2 = 0.98)与一个简单的半经验模型,其中利用的电荷数和分子质量的每一个蛋白质组作为参数。我们的建模数据表明,在CZE分离过程中蛋白质的完全解折叠有利于预测它们的μef。我们的研究结果还表明,N-末端乙酰化和磷酸化都减少了大约一个电荷单位的蛋白形式的电荷。
Large-scale top-down proteomics characterizes proteoforms in cells globally with high confidence and high throughput using reversed-phase liquid chromatography (RPLC)–tandem mass spectrometry (MS/MS) or capillary zone electrophoresis (CZE)–MS/MS. The false discovery rate (FDR) from the target–decoy database search is typically deployed to filter identified proteoforms to ensure high-confidence identifications (IDs). It has been demonstrated that the FDRs in top-down proteomics can be drastically underestimated. An alternative approach to the FDR can be useful for further evaluating the confidence of proteoform IDs after the database search. We argue that predicting retention/migration time of proteoforms from the RPLC/CZE separation accurately and comparing their predicted and experimental separation time could be a useful and practical approach. Based on our knowledge, there is still no report in the literature about predicting separation time of proteoforms using large top-down proteomics data sets. In this pilot study, for the first time, we evaluated various semiempirical models for predicting proteoforms’ electrophoretic mobility (μef) using large-scale top-down proteomics data sets from CZE–MS/MS. We achieved a linear correlation between experimental and predicted μef of E. coli proteoforms (R2 = 0.98) with a simple semiempirical model, which utilizes the number of charges and molecular mass of each proteoform as the parameters. Our modeling data suggest that the complete unfolding of proteoforms during CZE separation benefits the prediction of their μef. Our results also indicate that N-terminal acetylation and phosphorylation both decrease the proteoforms’ charge by roughly one charge unit.
DOI: 10.1021/acs.analchem.7b02532
发表时间: 2017-11-21
影响因子: 7.4
作者:
Lubeckyj RA;McCool EN;Shen X;Kou Q;Liu X;Sun L
通讯作者: Sun L
DOI: 10.1021/acs.analchem.7b04747
发表时间: 2018-01-02
影响因子: 7.4
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期刊: JOURNAL OF CHROMATOGRAPHY
影响因子: --
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通讯作者: COMPTON, BJ
DOI: 10.1007/s13361-019-02206-6
发表时间: 2019-12-01
影响因子: 3.2
作者:
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DOI: 10.1016/0003-2697(91)90379-8
发表时间: 1991-08-15
影响因子: 2.9
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通讯作者: NIELSEN, RG