Hansch-based molecular descriptors

Doucette and Andren [4] have compared six methods to estimate Kow for highly hydrophobic aromatic compounds such as halogenated benzenes, biphenyls, diben-zofurans, and dibenzo-p-dioxins with log Kow values ranging from 2.13 to 8.58. The comparison includes the GCM of Hansch and Leo, the GCM of Nys and Rekker, and correlations based on the following molecular descriptors HPLC retention times, M, TSA, and MCIs. The method using MCIs had the smallest average percent error. The method is... 

Mudder s (1981) work, which was a pioneer effort in the area of environmental QSARs, was based on real biodegradation data and used 25 molecular descriptors as described by Hansch and Leo. 

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. 

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. 

There are several methods developed for the calculation of logP from molecular structure, based on -> substituent constants, - fragmental constants, - electronic descriptors, -> steric descriptors, - connectivity indices, surface areas, - volume descriptors, and -> chromatographic descriptors [Leo, 1990 Hansch et al., 1995b Carrupt et al., 1997 Reinhard and Drefahl, 1999]. 

One of the initial approaches to decrease these costs were attempted by correlating the biological function of a compound with its chemical structure, expressed in terms of molecular structural descriptors, by means of QSAR techniques. This discipline was promoted by Hansch and his group (Fujita, 1990). It was based on the determination of mathematical equations expressing the biological activities as a function of molecular parameters. 

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