快速准确的蛋白质质谱电荷态反褶积。

IF 6.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Kenneth R Durbin,Matthew T Robey,Joseph B Greer,Ryan T Fellers,Aaron O Bailey
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引用次数: 0

摘要

电荷态反褶积对于高效和有效的蛋白质质谱分析至关重要。高质量的质量分析是必要的,以确定哪些蛋白质形式存在于蛋白质样品和它们的相对丰度。在追求全面的反褶积解决方案的过程中,我们详细介绍了一种名为kDecon的迭代电荷态反褶积算法,该算法经过调整,可以在质量结果中提供高精度,同时还可以对复杂光谱中的低丰度变形形式提供极好的灵敏度。在这里,kDecon作为靶向抗体和高通量蛋白质组学分析的质量测定算法的性能与现有的反卷积解决方案进行了基准测试。虽然不同的反褶积例程都被证明对检测最高丰度的蛋白质物种具有鲁棒性,但kDecon最终在低丰度的蛋白质类群质量分析中显示出同类最佳的精度。此外,与其他算法相比,kDecon结果的误报率减少了7倍,同时速度提高了至少20倍。总的来说,这些反卷积的进展将有助于实现生物治疗药物的常规和彻底的完整质量谱研究,以及提高自上而下的蛋白质组学实验的蛋白质组覆盖范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast and Accurate Charge State Deconvolution of Protein Mass Spectra.
Charge state deconvolution is essential for efficient and effective protein mass spectrometry analysis. High-quality mass profiling is necessary to determine which proteoforms are present in protein samples and their relative abundances. In the pursuit of a well-rounded deconvolution solution, we detail an iterative charge state deconvolution algorithm named kDecon that has been tuned to provide high accuracy in its mass results while also delivering superb sensitivity toward lower abundance proteoforms in complex spectra. Here, the performance of kDecon as a mass determination algorithm for both targeted antibody and high-throughput proteomics analysis was benchmarked against existing deconvolution solutions. While the different deconvolution routines all proved robust for detecting the highest abundance protein species, kDecon ultimately showcased best-in-class precision for lower abundance proteoform mass profiling. Furthermore, kDecon results had up to 7-fold fewer false positives and simultaneously exhibited at least 20-fold speed improvements over the other algorithms. Overall, these deconvolution advances will contribute to enabling both routine and thorough intact mass profiling studies for biotherapeutics as well as improving the proteome coverage of top-down proteomics experiments.
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来源期刊
Analytical Chemistry
Analytical Chemistry 化学-分析化学
CiteScore
12.10
自引率
12.20%
发文量
1949
审稿时长
1.4 months
期刊介绍: Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.
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