Predicting in silico electron ionization mass spectra using quantum chemistry.

Predicting in silico electron ionization mass spectra using quantum chemistry.
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DOI:
10.1186/s13321-020-00470-3
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发表时间:
2020-10-20
影响因子:
8.6
通讯作者:
Fiehn O
Fiehn O
中科院分区:
化学2区
文献类型:
--
作者:
Wang S;Kind T;Tantillo DJ;Fiehn O

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质谱法鉴定化合物需要参考质谱。虽然PubChem中有超过1.02亿种化合物,但从NIST或莫纳质谱数据库中可获得的精选电子电离(EI)质谱不到300,000个。在这里,我们测试量子化学方法(QCEIMS),通过结合分子动力学(MD)与统计方法生成电子轰击质谱(MS)。为了测试预测的准确性,生成了451个小分子的计算机质谱,并将其与NIST 17质谱库的实验光谱进行比较。这些化合物涵盖了43个化学类别,范围高达358 Da。有机含氧化合物的匹配精度较低,而计算时间随分子大小呈指数增长。探讨了参数空间,包括初始温度,MD轨迹的数量和碰撞剩余能量(IEE),以提高预测精度。构象的灵活性是不相关的预测的准确性。总体而言,QCEIMS可以预测70 eV的电子电离光谱的化学品从第一性原理。在大规模产生新分子的QCEIMS质谱之前,仍然需要改进计算势能面(PES)的方法。
Compound identification by mass spectrometry needs reference mass spectra. While there are over 102 million compounds in PubChem, less than 300,000 curated electron ionization (EI) mass spectra are available from NIST or MoNA mass spectral databases. Here, we test quantum chemistry methods (QCEIMS) to generate in silico EI mass spectra (MS) by combining molecular dynamics (MD) with statistical methods. To test the accuracy of predictions, in silico mass spectra of 451 small molecules were generated and compared to experimental spectra from the NIST 17 mass spectral library. The compounds covered 43 chemical classes, ranging up to 358 Da. Organic oxygen compounds had a lower matching accuracy, while computation time exponentially increased with molecular size. The parameter space was probed to increase prediction accuracy including initial temperatures, the number of MD trajectories and impact excess energy (IEE). Conformational flexibility was not correlated to the accuracy of predictions. Overall, QCEIMS can predict 70 eV electron ionization spectra of chemicals from first principles. Improved methods to calculate potential energy surfaces (PES) are still needed before QCEIMS mass spectra of novel molecules can be generated at large scale.
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