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Quantifying the Molecular Origins of Opposite Solvent Effects on Protein-Protein Interactions

Overview of attention for article published in PLoS Computational Biology, May 2013
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Title
Quantifying the Molecular Origins of Opposite Solvent Effects on Protein-Protein Interactions
Published in
PLoS Computational Biology, May 2013
DOI 10.1371/journal.pcbi.1003072
Pubmed ID
Authors

Vincent Vagenende, Alvin X. Han, Han B. Pek, Bernard L. W. Loo

Abstract

Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments.

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The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 2%
Korea, Republic of 1 2%
United Kingdom 1 2%
Canada 1 2%
United States 1 2%
Unknown 36 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 24%
Researcher 9 22%
Student > Master 7 17%
Student > Doctoral Student 4 10%
Student > Bachelor 3 7%
Other 6 15%
Unknown 2 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 32%
Biochemistry, Genetics and Molecular Biology 9 22%
Chemistry 9 22%
Chemical Engineering 3 7%
Engineering 3 7%
Other 3 7%
Unknown 1 2%