QSPR Study on Fluorophilicity

DUCHOWICZ, P. R.; MERCADER, A. G.; SANSERVINO, M. A.; CASTRO, E. A.; FERNANDEZ, F. M.

Ciudad Universitaria, Buenos Aires

Workshop; Eighth J.J. Giambiagi Winter School Part A, "Clusters, Molecules, Biomolecules and Materials"; 2006

QSPR Study on Fluorophilicity Pablo R. Duchowicz*, Andrew G. Mercader, Miguel A. Sanservino, Eduardo A. Castro, Francisco M. Fernández Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA), Facultad de Ciencias Exactas, UNLP, Diag. 113 y 64, Suc. 4, C.C. 16, (1900) La Plata. In the present work we apply the Quantitative Structure-Property Relationships (QSPR) theory[1] to predict the partition of 116 organic substances between organic and fluorinated solvents, a physicochemical property commonly referred as fluorophilicity[2]. The fluorous chemistry of compounds finds many interesting applications in synthesis and catalysis. In particular, the ability of fluorous solvents such as perfluoro(methylcyclohexane), CF3C6F11, to preferentially dissolve heavily fluorinated solutes in a “like dissolves like” manner has been exploited to perform reactions in such media, or to separate desired products from reaction mixtures. Several empirical “rules of thumb” for the design of fluorophilic molecules have been proposed, including a minimum fluorine content of 60%, the presence of one or more fluorous ponytails, and the absence of hydrogen bonding or polar groups which may interact with the organic phase. The different formulations of the QSPR theory suggest mathematical models for estimating relevant physicochemical properties, especially when these can not be experimentally determined for some reason. These studies simply rely on the assumption that the structure of a compound determinates the physicochemical properties it manifests, in present case the fluorophilicity. The molecular structure is therefore translated into numerical variables with physical interpretation, known as molecular descriptors, through mathematical formulae obtained from several theories, such as Chemical Graph Theory, Information Theory, Quantum Mechanics, etc. The most elementary kind of descriptors are the constitutionals, the count of atoms and bond types. There are thousands of molecular descriptors available in the literature, and one usually face the problem of selecting the most representatives for the property under consideration. In order to relate the experimental fluorophilicity values with the molecular structure, many standard statistical techniques can be employed. Recently, our research group has elaborated a very useful algorithm based on linear regressions called “Replacement Method”[3, 4], which enables to find the best molecular descriptors among a thousand of them. This technique is applied on the present data set, and the best model obtained is properly validated by means of the Cross-Validation technique in order to assess its true predictive performance. 1.Hansch C, Leo, A. (1995) Exploring QSAR. Fundamentals and Applications in Chemistry and Biology. American Chemical Society, Washington, D. C. 2.Rocaboy C, Rutherford, D., Bennet, B. L., Gladysz, J. A. (2000) J. Phys. Org. Chem. 13: 596. 3.Duchowicz P. R., Castro, E. A., Fernández, F. M., González, M. P. (2005) Chem. Phys. Lett. 412: 376. 4.Duchowicz P. R, Castro, E. A., Fernández, F. M. (2006) MATCH Commun. Math. Comput. Chem. 55: 179.