MetIDB: A Publicly Accessible Database of Predicted and Experimental 1H NMR Spectra of Flavonoids
MetIDB: A Publicly Accessible Database of Predicted and Experimental 1H NMR Spectra of Flavonoids
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DOI：
10.1021/ac4016837
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发表时间：
2013-09-17
影响因子：
7.4
通讯作者：
Vervoort, Jacques
中科院分区：
文献类型：
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作者：
Mihaleva, Velitchka V.;te Beek, Tim A. H.;Vervoort, Jacques
由于缺乏易于使用和可访问的参考数据库，天然化合物，特别是次生代谢物的鉴定一直受到阻碍。核磁共振（NMR）光谱是鉴定未知代谢物的最具选择性的技术。高质量的H-1核磁共振（质子核磁共振）光谱结合质谱（MS）获得的元素组成对鉴定过程至关重要。本文建立了6000种黄酮类化合物的实验和预测H-1 NMR谱参考数据库MetIDB。通过将立体化学、分子内相互作用和溶剂效应纳入预测模型，对化学位移和耦合进行了高精度预测。已经为MetIDB建立了一个用户友好的基于web的界面，为数据和数据挖掘的可能性提供了各种接口。对于每种化合物，附加信息包括化合物注释，H-1核磁共振谱，具有正确立体化学的2D和3D结构，单同位素质量以及其他网络资源的链接。化学式和H-1 NMR化学位移的结合被证明是非常有效的代谢物鉴定，特别是对等压化合物。使用这个数据库，黄酮类化合物鉴定的过程可以通过避免重复阐明已经描述的化合物而显着缩短。
Identification of natural compounds, especially secondary metabolites, has been hampered by the lack of easy to use and accessible reference databases. Nuclear magnetic resonance (NMR) spectroscopy is the most selective technique for identification of unknown metabolites. High quality H-1 NMR (proton nuclear magnetic resonance) spectra combined with elemental composition obtained from mass spectrometry (MS) are essential for the identification process. Here, we present MetIDB, a reference database of experimental and predicted H-1 NMR spectra of 6000 flavonoids. By incorporating the stereochemistry, intramolecular interactions, and solvent effects into the prediction model, chemical shifts and couplings were predicted with great accuracy. A user-friendly web-based interface for MetIDB has been established providing various interfaces to the data and data-mining possibilities. For each compound, additional information is available comprising compound annotation, a H-1 NMR spectrum, 2D and 3D structure with correct stereochemistry, and monoisotopic mass as well as links to other web resources. The combination of chemical formula and H-1 NMR chemical shifts proved to be very efficient in metabolite identification, especially for isobaric compounds. Using this database, the process of flavonoid identification can then be significantly shortened by avoiding repetitive elucidation of already described compounds.