Quantum Chemical Prediction of Electron Ionization Mass Spectra of Trimethylsilylated Metabolites

Chemical derivatization, especially silylation, is widely used in gas chromatography coupled to mass spectrometry (GC-MS). By introducing the trimethylsilyl (TMS) group to substitute active hydrogens in the molecule, thermostable volatile compounds are created that can be easily analyzed. While large GC-MS libraries are available, the number of spectra for TMS-derivatized compounds is comparatively small. In addition, many metabolites cannot be purchased to produce authentic library spectra. Therefore, computationally generated in silico mass spectral databases need to take TMS derivatizations into account for metabolomics. The quantum chemistry method QCEIMS is an automatic method to generate electron ionization (EI) mass spectra directly from compound structures. To evaluate the performance of the QCEIMS method for TMS-derivatized compounds, we chose 816 trimethylsilyl derivatives of organic acids, alcohols, amides, amines, and thiols to compare in silico-generated spectra against the experimental EI mass spectra from the NIST17 library. Overall, in silico spectra showed a weighted dot score similarity (1000 is maximum) of 635 compared to the NIST17 experimental spectra. Aromatic compounds yielded a better prediction accuracy with an average similarity score of 808, while oxygen-containing molecules showed lower accuracy with only an average score of 609. Such similarity scores are useful for annotation of small molecules in untargeted GC-MS-based metabolomics, suggesting that QCEIMS methods can be extended to compounds that are not present in experimental databases. Despite this overall success, 37% of all experimentally observed ions were not found in QCEIMS predictions. We investigated QCEIMS trajectories in detail and found missed fragmentations in specific rearrangement reactions. Such findings open the way forward for future improvements to the QCEIMS software.化学衍生化（chemical derivatization），尤其是硅烷化（silylation），被广泛应用于气相色谱-质谱联用（gas chromatography coupled to mass spectrometry，缩写GC-MS）技术中。通过引入三甲基硅基（trimethylsilyl，缩写TMS）取代分子中的活性氢原子，可生成热稳定且易挥发的化合物，便于后续分析检测。尽管目前已有大型GC-MS质谱库，但针对三甲基硅烷化衍生物的质谱谱图数量相对较少。此外，许多代谢物无法通过商品化手段获得以制备标准质谱库谱图。因此，在代谢组学研究中，通过计算方法生成的硅基模拟（in silico）质谱数据库需要将三甲基硅烷化衍生过程纳入考量。量子化学方法QCEIMS是一种可直接基于化合物结构生成电子电离（electron ionization，缩写EI）质谱谱图的自动化方法。为评估QCEIMS方法在三甲基硅烷化衍生物分析中的性能，本研究选取了816种有机酸、醇类、酰胺类、胺类及硫醇类化合物的三甲基硅烷化衍生物，将硅基模拟生成的质谱谱图与NIST17数据库中的实验电子电离质谱谱图进行比对。整体而言，硅基模拟谱图与NIST17实验谱图的加权点得分相似度（满分1000）为635。芳香族化合物的预测准确率更高，平均相似度得分为808；而含氧分子的预测准确率较低，平均得分仅为609。此类相似度得分可用于基于非靶向GC-MS的代谢组学中小分子的结构注释，表明QCEIMS方法可推广应用于实验数据库中未收录的化合物。尽管整体效果良好，但仍有37%的实验观测离子未在QCEIMS的预测结果中被检出。本研究对QCEIMS的计算轨迹进行了详细分析，发现特定重排反应中存在漏检的碎裂过程。此类发现为后续QCEIMS软件的优化改进指明了方向。