Heterocovariance Based Metabolomics as a Powerful Tool Accelerating Bioactive Natural Product Identification
Heterocovariance Based Metabolomics as a Powerful Tool Accelerating Bioactive Natural Product Identification
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DOI：
10.1002/slct.201600744
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发表时间：
2016-07-01
期刊：
影响因子：
2.1
通讯作者：
Skaltsounis, Leandros A.
中科院分区：
文献类型：
--
作者：
Aligiannis, Nektarios;Halabalaki, Maria;Skaltsounis, Leandros A.
新的活性天然产物的发现受到费力的纯化过程的阻碍，这些纯化过程通常最终导致已知化合物的重新分离。我们在这里证明，反映组分浓度波动的光谱数据可以在统计学上与可测量的剂量依赖性特性相关的基础上的异协方差方法去卷积的活性组分结构。提取物成分的方差是通过从不同的科，属，种的植物的统计学意义的集合。这种波动也是通过分离技术对单一植物提取物进行分馏而获得的。记录提取物和级分的NMR和HRMS光谱，以及它们抑制酪氨酸酶或5-脂氧合酶的能力。在任何纯化之前，通过异方差方法将生物活性与解读活性化合物的光谱数据统计学相关。
The discovery of new active natural products is hampered by laborious purification processes that often end up to the re-isolation of known compounds. We demonstrate here that, spectral data reflecting concentration fluctuations of components can correlate statistically with measurable dose-dependent properties on the basis of a Heterocovariance approach deconvoluting the active components structure. Variance of extract constituents was achieved through statistically meaningful collections of plants from different families, genus, and species. This fluctuation was also obtained through the fractionation of a single plant extract by separation techniques. The NMR and HRMS spectra of the extracts and fractions were recorded, as well as their ability to inhibit tyrosinase or 5-lipoxygenase enzymes. Biological activity was statistically correlated with spectral data deciphering the active compounds through the Heterocovariance approach prior to any purification.