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Using molecular simulation to predict solute solvation and partition coefficients in solvents of different polarity

Title
Using molecular simulation to predict solute solvation and partition coefficients in solvents of different polarity
Type
Article in International Scientific Journal
Year
2011
Authors
Nuno M. Garrido
(Author)
FEUP
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Miguel Jorge
(Author)
FEUP
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António J. Queimada
(Author)
FEUP
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Ioannis G. Economou
(Author)
Other
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Journal
Vol. 13 No. 20
Pages: 9155-9164
ISSN: 1463-9076
Indexing
Publicação em ISI Web of Science ISI Web of Science
INSPEC
Scientific classification
FOS: Engineering and technology > Other engineering and technologies
CORDIS: Technological sciences
Other information
Authenticus ID: P-002-ZB0
Abstract (EN): A methodology is proposed for the prediction of the Gibbs energy of solvation (Delta(Solv)G) based on MD simulations. The methodology is then used to predict DSolvG of four solutes (namely propane, benzene, ethanol and acetone) in several solvents of different polarities (including n-hexane, n-hexadecane, ethylbenzene, 1-octanol, acetone and water) while testing the validity of the TraPPE force field parameters. Excellent agreement with experimental data is obtained, with average deviations of 0.2, 1.1, 0.8 and 1.2 kJ mol(-1), for the four solutes respectively. Subsequently, partition coefficients (log P) for forty different solute/solvent systems are predicted. The a priori knowledge of partition coefficient values is of high importance in chemical and pharmaceutical separation process design or as a measure of the increasingly important environmental fate. Here again, the agreement between experimental data and simulation predictions is excellent, with an absolute average deviation of 0.28 log P units. However, this deviation can be decreased down to 0.14 log P units, just by optimizing partial atomic charges of acetone in the water phase. Consequently, molecular simulation is proven to be a tool with strong physical basis able to predict log P with competitive accuracy when compared to the popular statistical methods with weak physical basis.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 10
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