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Thermal Shift as an Entropy-Driven Effect
Author(s) -
Martin Redhead,
Rupert Satchell,
Ciara McCarthy,
Scott J. Pollack,
John Unitt
Publication year - 2017
Publication title -
biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.43
H-Index - 253
eISSN - 1520-4995
pISSN - 0006-2960
DOI - 10.1021/acs.biochem.7b00860
Subject(s) - metric (unit) , entropy (arrow of time) , interpretation (philosophy) , statistical physics , melting temperature , thermal , biological system , macromolecule , computer science , chemistry , thermodynamics , theoretical physics , physics , materials science , biology , biochemistry , operations management , economics , composite material , programming language
Thermal shift assays (TSAs) are among the most commonly used biophysical approaches in drug discovery in both academic and industrial settings. However, the most common interpretation of the data generated by a TSA is purely qualitative, using only the change in melting temperature (ΔT m ) as a metric. This has left many questions surrounding the interpretation of the data as well as whether the TSA truly correlates with other assays. TSAs also lack theoretical descriptions of the melt behavior of proteins in the presence of multiple ligands. Here we describe a novel simplified analytical framework based on "pseudoisothermal" models as well as exact thermodynamic descriptions of protein-ligand melt behavior rooted in changes in the entropy of melting. We show how the models are broad and independently applicable, in that they can describe the behavior of any macromolecule such as a protein or DNA and demonstrate good correlations with other techniques. These models are shown to give good descriptions of assay systems containing single or multiple ligands and can determine the mechanism of interaction. The models are derived from first principles, and the theoretical justification is discussed.

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