Hydrophobicity congenerity

The hydrophobic constant r is a measure of the contribution of a substituent X to the lipophilidty of compound R-X compared with R-H. The constant representing the solvent/solvent system, analogously to Hammett s p constant for the reaction type, was arbitrarily set to 1 for octanol/water and thus does not appear in Eq. (7). The lipophilidty constant ti allows the estimation of log P values for congeneric series of compounds with various substituents (see Eq. (8)). 

Molecules are characterized by potential hydrogen bonding, polar, hydrophobic, and electrostatic interactions in 3D space, using 3D molecular fields. Techniques such as Comparative Molecular Field Analysis (CoMFA), which considers the 3D distribution of electrostatic and steric fields, have been applied to congeneric series of enzyme substrates or inhibitors generating 3D QSAR equations. Most examples of such applications are to modeling CYP substrate and inhibitor specificity and these have been extensively reviewed in the literature (Ekins et al., 2000 2001 Ter Laak and Vermeulen, 2001 Ter Laak et al., 2002). 

These efforts were guided by the study of quantitative structure-activity relationships (QSAR) following the Hansch approach. In this method linear free-energy related and other electronic, hydrophobic, and steric substituent constants are used for a quantitative analysis of the possible ways in which substituents may modulate bioactivity in a congeneric series. In the QSAR studies of benzoylphenyl ureas the electronic Hammett a-constants and the hydro-phobic Hansch n-constants were used. To measure the steric influences, steric substituent constants of a new type (B1,B2,B3,B4, and L) were applied which had recently been introduced by us and which give improved correlations in comparison with the steric Es constants used in the literature hitherto (21, 22). The constants B- toBj are measures of the widths of substituents in four rectangular directions. The L-constant accounts for the length of a substituent ... 

What has the very limited experience of the past few years using substituent constants and regression analysis contributed to the problem of drug modification as outlined for derivatives of Figure 1 Possibly the most important fact is that the hydrophobic character of the members of almost any congeneric set of drugs must be considered even in... 

The epoch of QSAR (Quantitative Structure-Activity Relationships) studies began in 1963-1964 with two seminal approaches the a-p-7i analysis of Hansch and Fujita " and the Free-Wilson method. The former approach involves three types of descriptors related to electronic, steric and hydrophobic characteristics of substituents, whereas the latter considers the substituents themselves as descriptors. Both approaches are confined to strictly congeneric series of compounds. The Free Wilson method additionally requires all types of substituents to be suflficiently present in the training set. A combination of these two approaches has led to QSAR models involving indicator variables, which indicate the presence of some structural fragments in molecules. 

From the Hammett equation [Hammett, 1935, 1937], the seminal vork of Hammett gave rise to the a—p culture in the delineation of substituent effects on organic reactions, whose aim was to search for linear free energy relationships (LFER) [Hammett, 1938] steric, electronic, and hydrophobic constants were derived for several substituents and used in an additive model to estimate the biological activity of congeneric series of compounds. 

Hansch analysis A QSAR method based on extra-thermodynamic principles which expresses the biological activity of a congeneric series of molecules in terms of additive physical quantities as, e.g., hydrophobicity (log/3, n), electronic effects (pAa, steric effects (Es of Taft). 

Quantitative structure-activity relationships QSAR. The QSAR approach pioneered by Hansch and co-workers relates biological data of congeneric structures to physical properties such as hydrophobicity, electronic, and steric effects using linear regression techniques to estimate the relative importance of each of those effects contributing to the biological effect. The molecular descriptors used can be 1-D or 3-D (3D-QSAR). A statistically sound QSAR regression equation can be used for lead optimization. 

So far we have taken into account only the steric and electrostatic fit of congeneric drug molecules that bind at the same receptor site. This is clearly not sufficient if one aims towards a more detailed description of the structural properties of a receptor. Besides the already mentioned characteristics, hydrophobic areas, regions of charge transfer or several types of different polar interactions can also be distinguished. A receptor map which contains three-dimensional information of this kind is very helpful in the interpretation and understanding of known experimental results but also, which is even more desirable, for the prediction of new, hitherto unknown structures. 

The hydrophobicity term as measured by log P, the log n-octanol/water partition coefficient, indicates that the ability of an odorant to partition from the medium in which it is dissolved into the atmosphere and its ability to partition through mucus and membreine layers to reach olfactory receptor sites is highly correlated to odor intensity. Results of this study also indicated that within a congeneric series, the analogs with the highest volatilities are not necessarily the most intense odorants. 

Indeed, owing to the constant influence of polarity on the lipophilic behavior in a homologous series of small rigid solutes (Eqs. [4] and [5]), the observed relations between partition coefficients and SASA for hydrophobic compounds ° i or for congeneric series > are trivial because variations of lipophilicity in these series depend exclusively on variations in hydro-phobicity. However, even in these simple series, the use of SASA allows one to model the well-known effect of stereochemistry on lipophilicity. Other approaches have been explored to extend the use of SASA to noncongeneric... 

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