4.6 Article

Predicting protein partition coefficients in aqueous two phase system

Journal

JOURNAL OF CHROMATOGRAPHY A
Volume 1470, Issue -, Pages 50-58

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2016.09.072

Keywords

Protein partitioning; Aqueous two-phase system; Collander equation; Semi-empirical model; Partition coefficient prediction

Funding

  1. Fundacao para a Ciencia e a Tecnologia (FCT) [SFRH/BPD/70409/2010]
  2. FCT (Portuguese Foundation for Science and Technology) [UID/BIO/04565/2013]
  3. Programa Operacional Regional de Lisboa [007317]
  4. FCT [UID/CBQ/04612/2013]
  5. Fundação para a Ciência e a Tecnologia [SFRH/BPD/70409/2010] Funding Source: FCT

Ask authors/readers for more resources

The present work aims to achieve an additional insight into the protein partitioning behavior in aqueous two phase systems (ATPSs), together with a study on the viability of a semi-empirical model based on continuum electrostatics to predict the protein partition characteristics. The partitioning behaviors of 14 globular proteins, with different properties, were explored in three polymer/polymer ATPSs. By the Collander equation, a linear correlation between protein partitioning coefficients in all systems was observed. Using the semi-empirical model it was possible to predict the partitioning behavior of proteins. The electrostatic energy depends on the protein size and ATPSs characteristics and varies in agreement with the difference in phase dielectric constants. Linear correlation of nonpolar energy, and the solvent accessible surface area was observed. Polymer structure and concentration have a significant influence on model viability. A good qualitative prediction of preferred phase for studied proteins was observed. (C) 2016 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available