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Biochim Biophys Acta. 2016 May;1864(5):622-44. doi: 10.1016/j.bbapap.2016.02.017. Epub 2016 Feb 23.

Analytical applications of partitioning in aqueous two-phase systems: Exploring protein structural changes and protein-partner interactions in vitro and in vivo by solvent interaction analysis method.

Author information

1
Cleveland Diagnostics, 3615 Superior Avenue, Suite 4407B, Cleveland, OH 44114, USA. Electronic address: boris.zaslavsky@cleveland-diagnostics.com.
2
Department of Molecular Medicine and Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA. Electronic address: vuversky@health.usf.edu.
3
Cleveland Diagnostics, 3615 Superior Avenue, Suite 4407B, Cleveland, OH 44114, USA. Electronic address: arnon.chait@cleveland-diagnostics.com.

Abstract

This review covers the fundamentals of protein partitioning in aqueous two-phase systems (ATPS). Included is a review of advancements in the analytical application of solute partitioning in ATPS over the last two decades, with multiple examples of experimental data providing evidence that phase-forming polymers do not interact with solutes partitioned in ATPS. The partitioning of solutes is governed by the differences in solute interactions with aqueous media in the two phases. Solvent properties of the aqueous media in these two phases may be characterized and manipulated. The solvent interaction analysis (SIA) method, based on the solute partitioning in ATPS, may be used for characterization and analysis of individual proteins and their interactions with different partners. The current state of clinical proteomics regarding the discovery and monitoring of new protein biomarkers is discussed, and it is argued that the protein expression level in a biological fluid may be not the optimal focus of clinical proteomic research. Multiple examples of application of the SIA method for discovery of changes in protein structure and protein-partner interactions in biological fluids are described. The SIA method reveals new opportunities for discovery and monitoring structure-based protein biomarkers.

PMID:
26923390
DOI:
10.1016/j.bbapap.2016.02.017
[Indexed for MEDLINE]

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