Hansch

Boyd G T, Shen Y R and Hansch T W 1986 Continuous-wave second-harmonic generation as a surface microprobe Opt. Lett. 11 97-9... 

The work by Hammett and Taft in the 1950s had been dedicated to the separation and quantification of steric and electronic influences on chemical reactivity. Building on this, from 1964 onwards Hansch started to quantify the steric, electrostatic, and hydrophobic effects and their influences on a variety of properties, not least on the biological activity of drugs. In 1964, the Free-Wilson analysis was introduced to relate biological activity to the presence or absence of certain substructures in a molecule. 

The fundamental assumption of SAR and QSAR (Structure-Activity Relationships and Quantitative Structure-Activity Relationships) is that the activity of a compound is related to its structural and/or physicochemical properties. In a classic article Corwin Hansch formulated Eq. (15) as a linear frcc-cncrgy related model for the biological activity (e.g.. toxicity) of a group of congeneric chemicals [37, in which the inverse of C, the concentration effect of the toxicant, is related to a hy-drophobidty term, FI, an electronic term, a (the Hammett substituent constant). Stcric terms can be added to this equation (typically Taft s steric parameter, E,). 

The first use of QSARs to rationalise biological activity is usually attributed to Hansc [Hansch 1969]. He developed equations which related biological activity to a molecmle electronic characteristics and hydrophobicity. For example ... 

The Hammett substituent parameter was used by Hansch as a concise measure of th electronic characteristics of the molecules. Hammett and others (such as Taft) showed the... 

History and Objectives of Quantitative Drug Design. In Hansch C, P G Sammes and J B lor (Editors) Comprehensive Medicinal Chemistry Volume 4. Oxford, Pergamon Press, pp. 1-31. emd H van de 1995. Chemometric Methods in Molecular Design. Weinheim, VCH Publishers. 

C. Hansch, A. Leo, Exploring QSAR American Chemical Society, Washington (1995). L. B. Kier, L. H. Hall, Molecular Connectivity in Structure-Activity Analysis Research Studies Press, Chichester (1986). 

This section includes veterinary applications. The antiviral, bactericidal, and antimicrobial applications of 2-aminothiazoles and 2-imino-4-thiazolines are summarized in Table VI-7. They show a marked anti-trichonomicidal activity, which has even been quantitatively measured by the Hansch approach (797). The antiparasitic action of these compounds has been investigated for some compounds and is summarized in Table VI-8 interesting results were obtained with aminotrozal (1348). 

R. M. Muir and C. Hansch, "Chemical Stmcture and Growth-Activity of Substituted Benzoic Acids," in Ref. 27. 

The correlations between chemical descriptors of molecular properties and biological activity, especially the activity of herbicides and/or plant growth regulators has been described (12). Several alternatives or improvements on the Hansch-Fujita QSAR system have been developed (13—15). 

C. Hansch and A. J. Leo, Substituent Constantsfor Correlation Analysis in Chemistry andBiolog, [Pg.284]

The amino group is readily dia2oti2ed in aqueous solution, and this reaction forms a basis for the assay of sulfas. Aldehydes also react to form anils, and the yellow product formed with 4-(dimethylamino)hen2a1dehyde can be used for detection in thiu-layer and paper chromatography. Chromatographic retention values have been deterrnined in a number of thiu layer systems, and have been used as an expression of the lipophilic character of sulfonamides (23). These values have corresponded well with Hansch lipophilic parameters determined in an isobutyl alcohol—water system. 

R. Mumgan and co-workers, CHEMTECH, 17 (June, 1994) C. Hansch and A. Leo, "Exploring QSAR Eundamentals and AppHcation in... 

Quantitative stmcture—activity relationships have been estabUshed using the Hansch multiparameter approach (14). For rat antigoiter activities (AG), the following (eq. 1) was found, where, as in statistical regression equations, n = number of compounds, r = regression coefficient, and s = standard deviation... 

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