HPLC columns partition by chemometric methods based on peptides retention
HPLC columns partition by chemometric methods based on peptides retention
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DOI：
10.1016/j.jchromb.2006.10.048
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发表时间：
2007-01-15
影响因子：
3
通讯作者：
Jonsson, Tobias
中科院分区：
文献类型：
--
作者：
Buszewski, Boguslaw;Kowalska, Sylwia;Jonsson, Tobias
近年来，多变量技术被用于评价反相高效液相色谱数据。在本研究中，根据12种多肽的保留因子，采用高效液相色谱（HPLC）柱将其分为几组。采用主成分分析（PCA）和聚类分析（CA）对柱和肽进行比较和分组。CA结果表明，由于固定相的结构和性质，所有的固定相通常可以分成几个簇。另一方面，使用PC获得了有趣的结果。分类色谱柱在新色谱柱空间上几乎呈线性关系，这与色谱柱在其负载值中所反映的意义有关。第一个组分描述了肽的非极性性质，而第二个组分则装载了具有低得多的对数P值的极性肽。PCA和CA也用于多肽比较，但多肽分组的完整解释仍不清楚。(c) 2006 Elsevier B.V.版权所有
In recent years, multivariate techniques have been utilized to evaluate reversed-phase high-performance liquid chromatographic data. In the present study, I I high-performance liquid chromatography (HPLC) columns were divided into several groups according to the retention factors of 12 peptides. Principal component analysis (PCA) and cluster analysis (CA) were used in column and peptides' comparison and grouping. CA results indicated that all stationary phases may be generally grouped into several clusters, due to stationary phase structure and properties. On the other hand, interesting results were obtained with the use of PC. There is almost linear relationship between classified HPLC columns in the space of new PCs, which is connected with meaning of the PC's reflected in their loading values. The first component describes non-polar properties of peptides, whereas the second component is loaded with polar peptides having much lower log P values. PCA and CA were also used in peptides comparison however, complete explanation of peptides grouping still remains unclear. (c) 2006 Elsevier B.V. All rights reserved.