Literature DB >> 21674662

Quantitation of protein-protein interactions by thermal stability shift analysis.

Curtis J Layton1, Homme W Hellinga.   

Abstract

Thermal stability shift analysis is a powerful method for examining binding interactions in proteins. We demonstrate that under certain circumstances, protein-protein interactions can be quantitated by monitoring shifts in thermal stability using thermodynamic models and data analysis methods presented in this work. This method relies on the determination of protein stabilities from thermal unfolding experiments using fluorescent dyes such as SYPRO Orange that report on protein denaturation. Data collection is rapid and straightforward using readily available real-time polymerase chain reaction instrumentation. We present an approach for the analysis of the unfolding transitions corresponding to each partner to extract the affinity of the interaction between the proteins. This method does not require the construction of a titration series that brackets the dissociation constant. In thermal shift experiments, protein stability data are obtained at different temperatures according to the affinity- and concentration-dependent shifts in unfolding transition midpoints. Treatment of the temperature dependence of affinity is, therefore, intrinsic to this method and is developed in this study. We used the interaction between maltose-binding protein (MBP) and a thermostable synthetic ankyrin repeat protein (Off7) as an experimental test case because their unfolding transitions overlap minimally. We found that MBP is significantly stabilized by Off7. High experimental throughput is enabled by sample parallelization, and the ability to extract quantitative binding information at a single partner concentration. In a single experiment, we were able to quantify the affinities of a series of alanine mutants, covering a wide range of affinities (∼ 100 nM to ∼ 100 μM).
Copyright © 2011 The Protein Society.

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Year:  2011        PMID: 21674662      PMCID: PMC3189529          DOI: 10.1002/pro.674

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


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