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

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

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

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Title: Predicting the behaviour of proteins in hydrophobic interaction chromatography 1: Using the hydrophobic imbalance (HI) to describe their surface amino acid distribution
Author: Salgado, J. Cristián; Rapaport, Iván; Asenjo, Juan A.
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%.
URI: http://www.captura.uchile.cl/handle/2250/6199
Date: 2006-02-24
dc.identifier.citation: JOURNAL OF CHROMATOGRAPHY A Volume: 1107 Issue: 1-2 Pages: 110-119 Published: FEB 24 2006


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