Hansch QSAR

Finally, very recently Pallavicini et al., in continuation of a previous study on ortho-monosubstituted compounds, designed and synthesized a series of 2-[(2-phenox-yethyl) aminomethyl]-l,4-benzodioxanes ortho-disubstituted at the phenoxy moiety [99]. The disubstituted analogues were tested for their binding affinities at the three oq-AR subtypes and for the 5-HT1A-R. The affinity values of the new compounds were compared with those of the enantiomers of the 2,6-dimethoxyphenoxy analogue, the well-known oq-AR antagonist WB-4101 (Scheme 8.1), and of the ortho-monosubstituted derivatives. The results suggested some distinctive aspects in the interaction of the phenoxy moiety of monosubstituted and disubstituted compounds with the cqa-AR and the 5-HTiA receptors. A classical (Hansch) QSAR analysis was applied to the whole... 

Hansch QSAR and related approaches belong to the world of numbers conceptually, knowledge-based expert system approaches do not. Three areas of debate about expert systems have arisen from the distinction. Can you devise ways to generate qualified output from computer-based expert systems without hiding quantitative methods inside them Assuming you can, how do you validate an expert system How can you usefully combine output from different systems—some quantitative and some qualitative—to make predictions more reliable The first of the questions is more a historical than a current one some of the systems described earlier in this chapter demonstrate... 

There are numerous examples of traditional Hansch QSAR studies in the literature. " Some include large sets of descriptors, while others explore just a few. If physicochemical descriptor values are not readily available, indicator variables, denoting presence or absence of a certain structural feature, may be of help. This is the basis of the Free-Wilson (FW) method. 

It was also clear that calculation of log Poet for the immense variety of structures that might be considered in computer-assisted drug design (CADD) would be impractical based on the 7i-system, and thus fragmental and whole molecule approaches have dominated these calculations. Since it plays such a pivotal role in the Hammett-Hansch QSAR methodology, the basis for log Poet calculation will be examined in some detail because, even though they lack a firm, theoretical basis, the calculation details can often be as useful in CADD as the bottom line number. 

As mentioned, the problem has been solved, and it was solved almost 25 years ago [7] But to know about it, one should read QSAR publications coming from mathematical chemistry circles. Obviously, lack of cross-communication between the Hansch QSAR school and the circle around chemical graph theory is the culprit with equal guilt on both sides. 

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 ... 

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). 

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). 

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

Many different approaches to QSAR have been developed since Hansch s seminal work. These include both two-dimensional (2D) and 3D QSAR methods. The major differences among these methods can be analyzed from two viewpoints (1) the strucmral parameters that are used to characterize molecular identities and (2) the mathematical procedure that is employed to obtain the quantitative relationship between a biological activity and the structural parameters. 

C Hansch, A Leo. Exploring QSAR Fundamentals and Applications in Chemistry and Biology. Washington, DC American Chemical Society, 1995. 

C Hansch, A Leo, D Hoekman. Exploring QSAR Hydrophobic, Electronic, and Steric Constants. Washington, DC Am Chem Soc, 1995. 

Hansch C, Leo A, Hoekman D. Exploring QSAR Hydrophobic, electronic, and steric constants. Washington DC American Chemical Society, 1995. 

Martin YC. Distance comparison (DISCO) A new strategy for examining 3D structure-activity relationships. In Hansch C, Fujita T, editors, Classical and 3D QSAR in agrochemistry. Washington, DC American Chemical Society, 1995. p.318-29. 

Hansch C. The QSAR paradigm in the design of less toxic molecnles. Drug Metab Rev 1984 15 1279-94. 

Debnath, A.K. (2001) Quantitative Structure-Activity Relationship (QSAR) Paradigm - Hansch Era to New Millennium. Mini Reviews in Medicinal Chemistry, 1, 187-195. 

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