G0 Cell Unit, Okinawa Institute of Science and Technology, Graduate University, Onna, Okinawa, Japan.
Anal Chem. 2012 May 15;84(10):4396-403. doi: 10.1021/ac3000418. Epub 2012 Apr 26.
Mass spectrometry is commonly applied to qualitatively and quantitatively profile small molecules, such as peptides, metabolites, or lipids. Modern mass spectrometers provide accurate measurements of mass-to-charge ratios of ions, with errors as low as 1 ppm. Even such high mass accuracy, however, is not sufficient to determine the unique chemical formula of each ion, and additional algorithms are necessary. Here we present a universal software tool for predicting chemical formulas from high-resolution mass spectrometry data, developed within the MZmine 2 framework. The tool is based on the use of a combination of heuristic techniques, including MS/MS fragmentation analysis and isotope pattern matching. The performance of the tool was evaluated using a real metabolomic data set obtained with the Orbitrap MS detector. The true formula was correctly determined as the highest-ranking candidate for 79% of the tested compounds. The novel isotope pattern-scoring algorithm outperformed a previously published method in 64% of the tested Orbitrap spectra. The software described in this manuscript is freely available and its source code can be accessed within the MZmine 2 source code repository.
质谱通常用于定性和定量分析小分子，如肽、代谢物或脂质。现代质谱仪可以提供离子质荷比的精确测量，误差低至 1ppm。然而，即使如此高的质量精度，也不足以确定每个离子的独特化学式，还需要额外的算法。在这里，我们展示了一种基于 MZmine 2 框架的用于从高分辨率质谱数据中预测化学式的通用软件工具。该工具基于使用启发式技术的组合，包括 MS/MS 碎片分析和同位素模式匹配。该工具的性能使用使用 Orbitrap MS 检测器获得的真实代谢组学数据集进行了评估。对于测试化合物中的 79%，正确确定了最高排名候选物作为真实公式。新的同位素模式评分算法在 64%的测试 Orbitrap 光谱中优于之前发表的方法。本文中描述的软件是免费提供的，其源代码可以在 MZmine 2 源代码存储库中访问。
