Literature DB >> 15267361

Estimation of excess solvation numbers of water and cosolvents from preferential interaction and volumetric experiments.

Seishi Shimizu.   

Abstract

To elucidate, at a molecular level, how cosolvents influence protein stability, it is indispensable to understand the distribution of water and cosolvent molecules around proteins. Calculation of excess solvation numbers of water and cosolvents serves this purpose, and I show that they can be extracted from preferential interaction parameter and volumeric data via the Kirkwood-Buff theory. This scheme was applied to trehalose and glycerol (stabilizers) and urea (denaturant). Important insights from the application include stabilizer-induced enhancement of protein hydration, which, together with the stabilizer's exclusion from protein surfaces, may contribute to protein stabilization at high osmolyte concentrations.

Entities:  

Year:  2004        PMID: 15267361     DOI: 10.1063/1.1646373

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  9 in total

1.  A protein molecule in a mixed solvent: the preferential binding parameter via the Kirkwood-Buff theory.

Authors:  Ivan L Shulgin; Eli Ruckenstein
Journal:  Biophys J       Date:  2005-11-04       Impact factor: 4.033

2.  A contribution to the theory of preferential interaction coefficients.

Authors:  J Michael Schurr; David P Rangel; Sergio R Aragon
Journal:  Biophys J       Date:  2005-07-29       Impact factor: 4.033

3.  Chemical potential derivatives and preferential interaction parameters in biological systems from Kirkwood-Buff theory.

Authors:  Paul E Smith
Journal:  Biophys J       Date:  2006-05-05       Impact factor: 4.033

Review 4.  Recent applications of Kirkwood-Buff theory to biological systems.

Authors:  Veronica Pierce; Myungshim Kang; Mahalaxmi Aburi; Samantha Weerasinghe; Paul E Smith
Journal:  Cell Biochem Biophys       Date:  2007-11-28       Impact factor: 2.194

5.  Kirkwood-Buff theory of molecular and protein association, aggregation, and cellular crowding.

Authors:  Moon Bae Gee; Paul E Smith
Journal:  J Chem Phys       Date:  2009-10-28       Impact factor: 3.488

6.  Preferential binding effects on protein structure and dynamics revealed by coarse-grained Monte Carlo simulation.

Authors:  R B Pandey; D J Jacobs; B L Farmer
Journal:  J Chem Phys       Date:  2017-05-21       Impact factor: 3.488

Review 7.  Biomolecular electrostatics and solvation: a computational perspective.

Authors:  Pengyu Ren; Jaehun Chun; Dennis G Thomas; Michael J Schnieders; Marcelo Marucho; Jiajing Zhang; Nathan A Baker
Journal:  Q Rev Biophys       Date:  2012-11       Impact factor: 5.318

8.  Predicting Protein-Protein Interactions of Concentrated Antibody Solutions Using Dilute Solution Data and Coarse-Grained Molecular Models.

Authors:  Cesar Calero-Rubio; Ranendu Ghosh; Atul Saluja; Christopher J Roberts
Journal:  J Pharm Sci       Date:  2017-12-21       Impact factor: 3.534

9.  Dissecting Dynamic and Hydration Contributions to Sequence-Dependent DNA Minor Groove Recognition.

Authors:  Van L T Ha; Noa Erlitzki; Abdelbasset A Farahat; Arvind Kumar; David W Boykin; Gregory M K Poon
Journal:  Biophys J       Date:  2020-08-20       Impact factor: 4.033

  9 in total

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