Quantitative reactivity-activity relationships

The working ligand progress curve (10) directly depends on recorded and computed activity, which in turn depend on the chemical reactivity indices considered, employing what can be called quantitative reactivity-activity relationships (QRAR). For each DFT framework and each reactivity index, a different progress curve for a given ligand-receptor interaction is obtained. The immediate inference can be made that faster consumption of L(f) is involved for the more reactive index, and therefore, a more preeminent reactivity principle is associated. This allows the researcher... 

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). 

There are several properties of a chemical that are related to exposure potential or overall reactivity for which structure-based predictive models are available. The relevant properties discussed here are bioaccumulation, oral, dermal, and inhalation bioavailability and reactivity. These prediction methods are based on a combination of in vitro assays and quantitative structure-activity relationships (QSARs) [3]. QSARs are simple, usually linear, mathematical models that use chemical structure descriptors to predict first-order physicochemical properties, such as water solubility. Other, similar models can then be constructed that use the first-order physicochemical properties to predict more complex properties, including those of interest here. Chemical descriptors are properties that can be calculated directly from a chemical structure graph and can include abstract quantities, such as connectivity indices, or more intuitive properties, such as dipole moment or total surface area. QSAR models are parameterized using training data from sets of chemicals for which both structure and chemical properties are known, and are validated against other (independent) sets of chemicals. 

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 (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. 

The class of the quantitative approaches to SRC studies includes all the well-known approaches called Quantitative Structure-Activity Relationships (QSAR), Quantitative Structure-Property Relationships (QSPR), Quantitative Structure-Reactivity Relationships (QSRR), Quantitative Shape-Activity Relationships (QShAR), the molecular shape being considered as a component of the molecular structure. Quantitative Stmc-... 

Quantitative structure-activity relationship (QSAR) dates back to the nineteenth century and is a computer-based tool that attempts to correlate variations in structural or molecular properties of compounds with their biological activities. These physicochemical descriptors, which include parameters to account for hydrophobicity, topology, electronic properties, and steric effects, are determined empirically or, more recently, by computational methods. The premise is that the structure of a chemical determines the physiochemical properties and reactivities that underlie its biological and toxicological properties. Being able to predict potential adverse effects not only aids in the designed development of new chemicals but also reduces the need for animal testing. It may ultimately or potentially lead to better... 

The interaction of the atoms and electrons within a specific molecule determines the impact of the compound at the molecular level. The contribution of the physical-chemical characteristics of a compound to the observed toxicity is called quantitative structure-activity relationship (QSAR). QSAR has the potential of enabling environmental toxicologists to predict the environmental consequences of toxicants using only structure as a guide. The response of a chemical to ultraviolet radiation and its reactivity with the abiotic constituents of the environment determine the fate of a compound. 

Quantitative Structure-Activity Relationships (QSARs) refer to scientific methods for correlating chemical structures quantitatively with biological activity or chemical reactivity. 

Pires, J.M., Floriano, W.B. and Gaudio, A.C. (1997) Extension of the frontier reactivity indices to groups of atoms and application to quantitative structure-activity relationship studies. J. Mol. Struct. (Theochem), 389, 159-167. 

Additive (group contribution) methods have a long tradition of successful use in predicting the properties of both ordinary molecules and macromolecules (polymers). They have formed the backbone of the quantitative structure-activity relationships (QSAR) [1,2] used to predict the chemical reactivity and the biological activity of molecules in medicinal and agricultural chemistry. They have also been used extensively in many quantitative structure-property relationships (QSPR) developed for the physical and chemical properties of polymers. 

Quantum-chemical molecular descriptors have been actively used in the quantitative structure-activity relationship studies of biological activities [1,2,72]. In the following, examples of QSARs involving quantum-chemical descriptors and applied on the enzymatic reactivity, pharmacological activity, and toxicity of compounds are discussed. 

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