Quantitative structure-activity relationship electronic effects

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,). 

As the chemical models mentioned here refer to some fundamental thermochemical and electronic effects of molecules, their application is not restricted to the prediction of chemical reactivity data. In fact, in the development of the models extensive comparisons were made with physical data, and thus such data can also be predicted from our models. Furthermore, some of the mechanisms responsible for binding substrates to receptors are naturally enough founded on quite similar electronic effects to those responsible for chemical reactivity. This suggest the use of the models developed here to calculate parameters for quantitative structure-activity relationships (QSAR). 

Quantitative structure-activity relationship studies are of great importance in modern chemistry. From their origin in the study of organic chemistry dating back to the 19th century, these studies have relied on some empirical and qualitative rules about the reactivity similarities of compounds with similar structures. The most significant development in QSARs occurred with the work of Louis Hammett (1894-1987), who correlated some electronic properties of organic acids and bases with their equilibrium constants and reactivity (Johnson, 1973). Hammett postulated that the effect... 

Quantitative structure-activity relationships represent an attempt to correlate activities with structural descriptors of compounds. These physicochemical descriptors, which include hydrophobicity, topology, electronic properties, and steric effects, are determined empirically or, more recently, by computational methods. The success of a QSAR method depends on two factors the training dataset obtained by testing a group of chemicals and the descriptors obtained from some easily measurable or calculable property of the chemicals. 

Quantitative structure-activity relationships (QSARs) are important for predicting the oxidation potential of chemicals in Fenton s reaction system. To describe reactivity and physicochemical properties of the chemicals, five different molecular descriptors were applied. The dipole moment represents the polarity of a molecule and its effect on the reaction rates HOMo and LUMO approximate the ionization potential and electron affinities, respectively and the log P coefficient correlates the hydrophobicity, which can be an important factor relative to reactivity of substrates in aqueous media. Finally, the effect of the substituents on the reaction rates could be correlated with Hammett constants by Hammett s equation. 

Quantitative structure-activity relationship (QSAR) (Hansch and Klein, 1986 Hansch and Leo, 1995) represents an attempt to correlate structural descriptors of compounds with activities. The physicochemical descriptors include numerical parameters to account for electronic properties, steric effect, topology, and hydrophobicity of analogous compounds. In its simplest form, the biochemical activities are correlated to the numerical substituent descriptors of analogous compounds tested by a linear equation such as... 

The electronic properties of amino acid side chains are summarized in Table 3, and they represent a wide spectrum of measures. The NMR data are derived experimentally (37). The dipole (38), C mull, inductive, field, and resonance effects were derived from QM calculations (15). The VHSE5 (39) and Z3 (25) scales were developed for use in quantitative structure-activity relationship analysis of the biologic activity of natural and synthetic peptides. Both were derived from principal components analysis of assorted physico-chemical properties, which included NMR chemical shift data, electron-ion interaction potentials, charges, and isoelectric points. Therefore, these scales are composites rather than primary measures of electronic effects. The validity of these measures is indicated by their lack of overlap with hydrophobicity and steric parameters and by their ability to predict biologic activity of synthetic peptide analogs (25, 39). Finally, coefficients of electrostatic screening by amino acid side chains (ylocal and Ynon-local) were derived from an empirical data set (40), and they represent a composite of electronic effects. 

Kim, K.H. (1992a). 3D Quantitative Structure-Activity Relationships Description of Electronic Effects Directly from 3D Structures Using a Grid Comparative Molecular Field Analysis (CoMFA) Approach. QuantStruct-ActRelat, 11,127-134. 

Halogens (particularly chlorine) can be replaced by other electron-attracting functions snch as trifluoromethyl or cyano groups. In the antibiotic chloramphenicol, both the chlorine atoms of the dichloroacetic moiety and of the para-nitro-phenyl group yielded productive isosteric replacements (Table 15.6). Many other examples of univalent atoms or groups replacements are found in the chapter dealing with substituent effects (Chapter 20) and with quantitative structure-activity relationships (Chapter 23). 

Kim, KH. (1992) 3D quantitative structure-activity relationships description of electronic effects directly from 3D structures using a grid comparative molecular field analysis (CoMFA) approach. Quant. Struct. -Act. Rdat., 11, 127-134. 

QSAR - Quantitative Structure Activity Relationships - in general terms denotes models, which, based on the variation in structural and/or electronic features in series of selected, molecules, describe variation in a given end-point of these molecules. These end-points may be, e.g., biological effects or physical-chemical parameters, which experimentally can be verified. Based on the developed QSAR model end-points of new, structurally related compounds, hitherto not being experimentally studied, may be predicted. 

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. 

The study of structure-reactivity relationships by the organic chemist Hammett showed that there is often a quantitative relationship between the two-dimensional structure of organic molecules and their chemical reactivity. Specifically, he correlated the changes in chemical properties of a molecule that result from a small change in its chemical structure that is, the quantitative linear relationship between electron density at a certain part of a molecule and its tendency to undergo reactions of various types at that site. For example, there is a linear relationship between the effea of remote substituents on the equilibrium constant for the ionization of an acid with the effect of these substituents on the rate or equilibrium constant for many other types of chemical reaction. The relative value of Hammett substituent constants describes the similarity of molecules in terms of electronic properties. Taft expanded the method to include the steric hindrance of access of reagents to the reaction site by nearby substituents, a quantitation of three-dimensional similarity. In addition, Charton, Verloop, Austel, and others extended and refined these ideas. Finally, Hansch and Fujita showed that biological activity frequently is also quantitatively correlated with the hydrophobic character of the substituents. They coined the term QSAR, Quantitative Structure-Activity Relationships, for this type of analysis. 

Additionally, QSAR (quantitative structure-activity relationship) is used in the optimization process (Seydel et al., 1979 Draber et al., 1992). QSAR represents an attempt to correlate structural or property descriptors of compounds with biological activities. The physicochemical descriptors include parameters to account for hydro-phobicity, topology, electronic properties and steric effects. The method is also used to get informations how to decouple undesired toxic effect from desired biological activity. 

KSC = Kekule structure count QSAR = quantitative structure-activity relationships QSPR = quantitative structure-property relationships SRWAC = self-returning walk atomic code TEMO = topological effect on molecular orbitals TRE = topological resonance energy TREPE = TRE per r-electron. 

The alternatives to mathematical descriptors derived from molecular graphs or molecular geometry are the traditional QSAR (quantitative structure-activity relationship) descriptors and quantum chemically computed parameters. The former include the partition coefficient for oil/water (often octanol/water) (log P), the Hammet sigma value (electronic parameter that measures the electron withdrawal from and the electron release to the aromatic ring by a substituent, the Taft s parameters for the electronic effects of substituents in aliphatic compounds (a ), and a steric parameter for the proximity of substituents on reaction sites (Es)- Also selected molecular properties, such as molar refractivity (MR), polarizability (a), molecular weight (MW), and density (d), have been used. 

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