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Prediction of the partitioning behaviour of proteins in aqueous two-phase systems using only their amino acid composition
Indexado
WoS WOS:000252477400016
Scopus SCOPUS_ID:37449019890
DOI 10.1016/J.CHROMA.2007.11.064
Año 2008
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



The prediction of the partition behaviour of proteins in aqueous two-phase systems (ATPS) using mathematical models based on their amino acid composition was investigated. The predictive models are based on the average surface hydrophobicity (ASH). The ASH was estimated by means of models that use the three-dimensional structure of proteins and by models that use only the amino acid composition of proteins. These models were evaluated for a set of 11 proteins with known experimental partition coefficient in four-phase systems: polyethylene glycol (PEG) 4000/phospate, sulfate, citrate and dextran and considering three levels of NaCl concentration (0.0% w/w, 0.6% w/w and 8.8% w/w). The results indicate that such prediction is feasible even though the quality of the prediction depends strongly on the ATPS and its operational conditions such as the NaCl concentration. The ATPS 0 model which use the three-dimensional structure obtains similar results to those given by previous models based on variables measured in the laboratory. In addition it maintains the main characteristics of the hydrophobic resolution and intrinsic hydrophobicity reported before. Three mathematical models, ATPS I-III, based only on the amino acid composition were evaluated. The best results were obtained by the ATPS I model which assumes that all of the amino acids are completely exposed. The performance of the ATPS I model follows the behaviour reported previously, i.e. its correlation coefficients improve as the NaCl concentration increases in the system and, therefore, the effect of the protein hydrophobicity prevails over other effects such as charge or size. Its best predictive performance was obtained for the PEG/dextran system at high NaCl concentration. An increase in the predictive capacity of at least 54.4% with respect to the models which use the three-dimensional structure of the protein was obtained for that system. In addition, the ATPS I model exhibits high correlation coefficients in that system being higher than 0.88 on average. The ATPS I model exhibited correlation coefficients higher than 0.67 for the rest of the ATPS at high NaCl concentration. Finally, we tested our best model, the ATPS I model, on the prediction of the partition coefficient of the protein invertase. We found that the predictive capacities of the ATPS I model are better in PEG/dextran systems, where the relative error of the prediction with respect to the experimental value is 15.6%. (c) 2007 Elsevier B.V. All rights reserved.

Revista



Revista ISSN
Journal Of Chromatography A 0021-9673

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Disciplinas de Investigación



WOS
Chemistry, Analytical
Biochemical Research Methods
Scopus
Biochemistry
Analytical Chemistry
Organic Chemistry
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 SALGADO-HERRERA, JOSE CRISTIAN Hombre Universidad de Chile - Chile
2 ANDREWS-FARROW, BARBARA ANNE Mujer Universidad de Chile - Chile
3 ORTUZAR-LATHROP, MARIA FERNANDA Mujer Universidad de Chile - Chile
4 ASENJO-DE LEUZE, JUAN ALFONSO Hombre Universidad de Chile - Chile

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Origen de Citas Identificadas



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Citas identificadas: Las citas provienen de documentos incluidos en la base de datos de DATACIENCIA

Citas Identificadas: 13.79 %
Citas No-identificadas: 86.21000000000001 %

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Citas identificadas: Las citas provienen de documentos incluidos en la base de datos de DATACIENCIA

Citas Identificadas: 13.79 %
Citas No-identificadas: 86.21000000000001 %

Financiamiento



Fuente
Fondo Nacional de Desarrollo Científico y Tecnológico
Fondo de Fomento al Desarrollo Científico y Tecnológico
Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica
Fondo de Fomento al Desarrollo Científico y Tecnológico

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Agradecimientos



Agradecimiento
This work was supported by FONDECYT PostDoctoral Research Project 3070031, FONDEF project D04-1-1374 and the Millennium Scientific Initiative ICM project P05-001-F.

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