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预测蛋白质在疏水相互作用色谱中的行为。1:利用疏水失衡(HI)描述其表面氨基酸分布。

Predicting the behaviour of proteins in hydrophobic interaction chromatography. 1: Using the hydrophobic imbalance (HI) to describe their surface amino acid distribution.

作者信息

Salgado J Cristian, Rapaport Ivan, Asenjo Juan A

机构信息

Centre for Biochemical Engineering and Biotechnology, Department of Chemical and Biotechnology Engineering, University of Chile, Beauchef 861, Santiago, Chile.

出版信息

J Chromatogr A. 2006 Feb 24;1107(1-2):110-9. doi: 10.1016/j.chroma.2005.12.032. Epub 2005 Dec 27.

DOI:10.1016/j.chroma.2005.12.032
PMID:16384569
Abstract

This paper focuses on the prediction of the dimensionless retention time of proteins (DRT) in hydrophobic interaction chromatography (HIC) by means of mathematical models based on characteristics of the surface hydrophobicity distribution. We introduce a new parameter, called hydrophobic imbalance (HI), obtained from the three-dimensional structure of proteins. This parameter quantifies the displacement of the superficial geometric centre of the protein when the effect of the hydrophobicity of each amino acid is considered. This parameter is simpler and less expensive than those reported previously. We use HI as a way to incorporate information about the surface hydrophobicity distribution in order to improve the prediction of DRT. We tested the performance of our DRT predictive models in a set of 15 proteins. This set includes four proteins whose DRTs are known as very difficult to predict. By means of the variable HI, it was possible to improve the predictive characteristics obtained by models based on the average surface hydrophobicity (ASH) by 9.1%. Also, we studied linear multivariable models based on characteristics determined from the HI. By using this multivariable model, a correlation coefficient of 0.899 was obtained. With this model, we managed to improve the predictive characteristics shown by previous models based on ASH by 31.8%.

摘要

本文重点研究基于表面疏水性分布特征的数学模型预测蛋白质在疏水相互作用色谱法(HIC)中的无量纲保留时间(DRT)。我们引入了一个新参数,称为疏水不平衡(HI),它从蛋白质的三维结构中获得。该参数在考虑每个氨基酸的疏水性影响时,量化了蛋白质表面几何中心的位移。该参数比之前报道的参数更简单且成本更低。我们使用HI来纳入有关表面疏水性分布的信息,以改进DRT的预测。我们在一组15种蛋白质中测试了我们的DRT预测模型的性能。该组包括四种已知DRT很难预测的蛋白质。通过可变的HI,基于平均表面疏水性(ASH)的模型所获得的预测特性得以提高9.1%。此外,我们研究了基于从HI确定的特征的线性多变量模型。通过使用这种多变量模型,获得了0.899的相关系数。利用该模型,我们成功地将基于ASH的先前模型所显示的预测特性提高了31.8%。

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