Solvent-solute descriptor models

H-bonding is an important, but not the sole, interatomic interaction. Thus, total energy is usually calculated as the sum of steric, electrostatic, H-bonding and other components of interatomic interactions. A similar situation holds with QSAR studies of any property (activity) where H-bond parameters are used in combination with other descriptors. For example, five molecular descriptors are applied in the solvation equation of Kamlet-Taft-Abraham excess of molecular refraction (Rj), which models dispersion force interactions arising from the polarizability of n- and n-electrons the solute polarity/polarizability (ir ) due to solute-solvent interactions between bond dipoles and induced dipoles overall or summation H-bond acidity (2a ) overall or summation H-bond basicity (2(3 ) and McGowan volume (VJ [53] ... 

How well can continuum solvation models distinguish changes in one or another of these solvent properties This is illustrated in Table 2, which compares solvation energies for three representative solutes in eight test solvents. Three of the test solvents are those shown in Table 1, one is water, and the other four were selected to provide useful comparisons on the basis of their solvent descriptors, which are shown in Table 3. Notice that all four solvents in Table 3 have no acidity, which makes them more suitable, in this respect, than 1-octanol or chloroform for modeling biomembranes. Table 2 shows that the SM5.2R model, with gas-phase geometries and semiempirical molecular orbital theory for the wave function, does very well indeed in reproducing all the trends in the data. 

Among the large number of existing lipophilicity parameters [31], the descriptor frequently estimated by in silica methods is the partition coefficient of a solute between 1-octanol and water, expressed as log Poet [32]. However, lipophilicity determination in different solvent systems, such as alkane/water system, proved its utility in (Q)SAR studies and therefore some predictive methods also emerged in this field. Many publically available databases include numerous experimental values collected through the literature the quality of the experimental data represents the cornerstone of most of the models developed to predict lipophilicity. 

A linear solvation energy relationship (LSER) has been developed to predict the water-supercritical CO2 partition coefficients for a published collection of data. The independent variables in the model are empirically determined descriptors of the solute and solvent molecules. The LSER approach provides an average absolute relative deviation of 22% in the prediction of the water-supercritical CO2 partition coefficients for the six solutes considered. Results suggest that other types of equilibrium processes in supercritical fluids may be modeled using a LSER approach (Lagalante and Bruno, 1998). 

During the drug discovery process the solubility in a mixture of water with another cosolvent like DM SO is commonly measured. The compounds are usually dissolved first in DMSO and then diluted in water and/or buffer solution. Therefore, a classification model has been successfully derived to predict the solubility in this solvent mixture using the VolSurf type of descriptors (Fig. 10.9(b)) for a set of 150 compounds with two latent variables (Table 10.2). 

Electric polarization, dipole moments and other related physical quantities, such as multipole moments and polarizabilities, constitute another group of both local and molecular descriptors, which can be defined either in terms of classical physics or quantum mechanics. They encode information about the charge distribution in molecules [Bbttcher et al, 1973]. They are particularly important in modelling solvation properties of compounds which depend on solute/solvent interactions and in fact are frequently used to represent the -> dipolarity/polarizability term in - linear solvation energy relationships. Moreover, they can be used to model the polar interactions which contribute to the determination of the -> lipophilicity of compounds. 

The connectivity indices and the polarizability parameters, however, relate a solutes solubility directly to its molecular structure, and thus could be more useful in the design and evaluation of new chemicals. A particular drawback of the polarizability parameter used here is that, unlike the LSER descriptors, it is not universally applicable to all solute-solvent interactions. It has to be defined and optimized for each property being studied. The log p descriptor is purely empirical, and does not poru ay any direct mechanistic significance in relation to the solutes molecular structure. Further, since Model 1 is significantly improved by including melting point data, it can be noted that log p alone docs not encode sufficient information relating aqueous solubility. 

Jover et al. (2007JQCS385) utihzed ANN to compose a multicomponent system to correlate pIQ of 94 phenols in protic (water, methanol, isopropanol, and tert-butanol) and aprotic (DMSO, N,N-dimethylformamide (DMF), AN, nitromethane, acetone, and N,N-dimethylacetamide (DMA)) solvents. The phenols were characterized hy CODESSA descriptors and the solvents hy several physical properties and the most used multiparametric polarity solvent scales. The final model contained seven descriptors—five of them belonging to the solutes and the remaining two to the solvents. RMSE and (R ) of 0.71 (0.982), 0.83 (0.977), and 0.95 (0.975) for the... 

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