Hansch approach, steric

A classical Hansch approach and an artificial neural networks approach were applied to a training set of 32 substituted phenylpiperazines characterized by their affinity for the 5-HTiA-R and the generic arAR [91]. The study was aimed at evaluating the structural requirements for the 5-HTiA/ai selectivity. Each chemical structure was described by six physicochemical parameters and three indicator variables. As electronic descriptors, the field and resonance constants of Swain and Lupton were used. Furthermore, the vdW volumes were employed as steric parameters. The hydrophobic effects exerted by the ortho- and meta-substituents were measured by using the Hansch 7t-ortho and n-meta constants [91]. The resulting models provided a significant correlation of electronic, steric and hydro-phobic parameters with the biological affinities. Moreover, it was inferred that the... 

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 ... 

Based on the earlier work of Meyer and Overton, who showed that the narcotic effect of anesthetics was related to their oil/water partition coefficients, Hansch and his co-workers have demonstrated unequivocally the importance of hydrophobic parameters such as log P (where P is, usually, the octanol/water partition coefficient) in QSAR analysis.28 The so-called classical QSAR approach, pioneered by Hansch, involves stepwise multiple regression analysis (MRA) in the generation of activity correlations with structural descriptors, such as physicochemical parameters (log P, molar refractivity, etc.) or substituent constants such as ir, a, and Es (where these represent hydrophobic, electronic, and steric effects, respectively). The Hansch approach has been very successful in accurately predicting effects in many biological systems, some of which have been subsequently rationalized by inspection of the three-dimensional structures of receptor proteins.28 The use of log P (and its associated substituent parameter, tr) is very important in toxicity,29-32 as well as in other forms of bioactivity, because of the role of hydrophobicity in molecular transport across cell membranes and other biological barriers. 

The Hansch approach is one of the most widely used methods for analysing structure-activity relationships when quantitative data are available. It is named after the founder of modern QSAR, Corwin Hansch (Hansch and Fujita, 1964), who suggested that the biological activity of a molecule was a function of its electronic, steric and hydrophobic properties the last most often being represented by the partition coefficient (P) between water and octanol (equation 2). 

Fuller, Marsh, and Mills (22) applied the Hansch approach to a series of 16 N-(phenoxyethyl)cyclopropylamines which are monoamine oxidase (MAO) inhibitors. The activity is expressed as p/50, the negative logarithm of the concentration of the derivative which inhibits MAO 50%. They used a dummy variable, y, to designate the steric effects of meta substitution. Their results are summarized in Figure 24. 

Approach was used in deriving mechanistic information about odor intensity as well as insight into how this biological activity may be predicted. This paper will first briefly describe the history of QSAR, the QSAR parameters used, and how substituents for QSAR studies are selected. Several examples of the Hansch Approach used in taste and odor quality studies will next be presented. The balance of the paper will deal with the development of quantitative structure odor intensity relationships which will further expand upon the earlier study reported by this author (11). For example, the use of relatively new QSAR steric parameters in correlations with odor intensity data, and correlations of log P with literature odor intensity data determined on animal panels will be presented. This will be followed by conclusions derived from those studies, and areas of future work. 

The use of the QSAR technique known as the Hansch Approach in the investigation of odor intensity and odorant physico-chemical properties has indicated that hydrophobic properties of homologous series of compounds, not steric or polar properties, are highly correlated to the level of odor intensity. This was shown to be the case for literature odor threshold and suprathreshold data determined at different laboratories using various media. The poor correlation between odor intensity and the steric properties of molecules (Taft Steric Constant) which had been reported earlier by this author (11) have been further verified by the use of Charton and Verloop Sterimol steric parameters. 

The criticisms in the previous paragraphs lead to a question If Hansch analysis is of such questionable value, then why has an entire chapter of this textbook been devoted to the subject Despite the fading utility of classical QSAR methods such as Hansch analysis, the logic behind Hansch analysis is invaluable to medicinal chemistry. Synthetic chemists in the pharmaceutical industry intuitively consider the ideas used to construct Hansch equations. Ideas such as electronics, sterics, and lipophilicity underlie traditional SAR approaches in the laboratory. Critical analysis of activity data and emphasis on seeking holes in R-group selection are also fundamental to successful SAR on a lead. Through the study of Hansch analysis, all these crucial ideas are presented in a rational framework that helps demonstrate their relevance. Just as importantly, Hansch analysis provides the foundation for the next generation of QSAR comparative molecular field analysis. 

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. 

On the basis of the origin of molecular descriptors used in calculations, QSAR methods can be divided into three groups. One group is based on a relatively small number (usually many times smaller than the number of compounds in a data set) of physicochemical properties and parameters describing,for example, hydrophobic, steric, and electrostatic effects. Usually, these descriptors are used as independent variables in multiple regression approaches (18) Jn the literature, these methods are typically referred to as Hansch analysis (8).These types of descriptors and corresponding linear optimization methods used in traditional QSAR analyses are discussed extensively in the chapter by Celassie (7) and therefore is not reviewed here. 

A further extension would be to consider a 3D Craig plot using three descriptors, for example, reflecting steric, lipophilic and electronic properties of the substituents. In that case, substituents may be chosen from the eight octants. If one wants to consider even more descriptors, this approach becomes impractical. In that case, more advanced experimental design techniques may be applied. One approach taken by Hansch and Leo was to use CA to define sets of aliphatic and aromatic substituents useful in the design of compounds for synthesis, such that various aspects of the substituents are taken into account in a balanced way. ... 

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. 

Clayton and Purcell have illustrated the predictive utility of this method when applied to selected butyrylcholinesterase inhibitors (94). They obtained quantitative correlations using group dipole moments, and /x in addition to hydrophobic parameters. In addition, Hansch and co-workers have used Taft steric parameters (Es) (60) and pKa values to obtain excellent correlations in various systems (84). E8 has recently been shown to be quantitatively related to van der Waal s radii for symmetrical top-like substituents (98) while pKa values have been used as a measure of electron density distributions (99). Fukuto and co-workers combined Tafts Es and a parameters in a physicochemical approach to the mode of action of organophosphorus insecticides (95). 

QSAR Correlation. Statistical quality of QSAR correlation can be employed as a third criterion of commonality of mechanism. This approach can prove very meaningful when coupled with a mechanistic interpretation of the role of molecular descriptors used in the correlation, and with the significance of the slope and intercept. The quality of statistical fit and the interpretation of the parameter or parameters used in the correlation can provide a valuable insight into molecular mechanism. Recently, Hansch analysis has been combined with molecular graphics and modeling studies in which the activities of a series of substrates to an enzyme receptor have been related to the hydrophobic, electronic, and steric requirements for reversible binding... 

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