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Automated Strategies To Identify Compounds on the Basis of GC/EI-MS and Calculated Properties

机译:基于GC / EI-MS和计算特性的化合物自动识别策略

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The identification of unknown compounds based on GC/EI-MS spectrum and structure generation techniques has been improved by combining a number of strategies into a programmed sequence. The program MOLGEN-MS is used to determine the molecular formula and incorporate substructural information to generate all structures matching the mass spectral information. Mass spectral fragments are then predicted for each structure and compared with the experimental spectrum using a match value. Additional data are then calculated automatically for each candidate to allow exclusion of candidates that did not match other analytical information. The effectiveness of these "exclusion criteria", as well as the programming sequence, was tested using a case study of 29 isomers of formula C_(12)H_(10)O_(2). The default classifier precision resulted in the generation of too many structures in some cases, which was improved by up to several orders of magnitude by including additional classifiers or restrictions. Combining this with the exclusion of candidates based on a Lee retention index/boiling point correlation, octanol--water partitioning coefficients, steric energies, and finally spectral match values limited the number of candidate structures further from over 1 billion without any restrictions down to less than 6 structures in 10 cases and below 35 in all but 3 cases. This method can be used in the absence of matching database spectra and brings unknown identification based on MS interpretation and structure generation techniques a step closer to practical reality.
机译:通过将多种策略组合到一个程序化的序列中,基于GC / EI-MS光谱和结构生成技术的未知化合物的鉴定得到了改进。程序MOLGEN-MS用于确定分子式并结合子结构信息以生成与质谱信息匹配的所有结构。然后预测每种结构的质谱碎片,并使用匹配值将其与实验光谱进行比较。然后自动为每个候选者计算其他数据,以排除与其他分析信息不匹配的候选者。这些“排除标准”的有效性以及编程顺序,是通过对式C_(12)H_(10)O_(2)的29个异构体进行案例研究来测试的。默认的分类器精度在某些情况下会导致生成过多的结构,通过添加其他分类器或限制,这种结构最多可以提高几个数量级。将其与基于Lee保留指数/沸点相关性的候选物排除在外,辛醇-水分配系数,空间能以及最终的光谱匹配值将候选结构的数量从超过10亿进一步限制为无限制10例中有6个以上的结构,除3例以外,其余所有结构中的35个以下。该方法可在不存在匹配数据库光谱的情况下使用,并使基于MS解释和结构生成技术的未知识别更接近实际。

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