Aromatic compounds descriptors

A set of n = 209 polycyclic aromatic compounds (PAC) was used in this example. The chemical structures have been drawn manually by a structure editor software approximate 3D-structures including all H-atoms have been made by software Corina (Corina 2004), and software Dragon, version 5.3 (Dragon 2004), has been applied to compute 1630 molecular descriptors. These descriptors cover a great diversity of chemical structures and therefore many descriptors are irrelevant for a selected class of compounds as the PACs in this example. By a simple variable selection, descriptors which are constant or almost constant (all but a maximum of five values constant), and descriptors with a correlation coefficient >0.95 to another descriptor have been eliminated. The resulting m = 467 descriptors have been used as x-variables. The y-variable to be modeled is the Lee retention index (Lee et al. 1979) which is based on the reference values 200, 300, 400, and 500 for the compounds naphthalene, phenanthrene, chrysene, and picene, respectively. 

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... 

Several significant correlations between the numbers of chlorines and the molecular descriptors with different number of carbons have been developed. Alcohols show a significant correlation with HOMO, LUMO, and AE aldehydes show an inverse correlation with LUMO and aromatic compounds show a direct correlation with log P. Other classes and descriptors did not show significant correlations (see Figure 5.17). 

In Hammett correlations, the descriptors, such as a.(or a.,J and o, can be used to derive equations for aromatic and aliphatic compounds, respectively. For aromatic compounds, the a., descriptor formulated better Hammett correlations than the om descriptor. Given the value of a molecular descriptor, a Hammett correlation for a particular chemical class may be used to predict kinetic rate constants for compounds with similar chemical structure. The QSAR models for each class of compounds studied by elementary hydroxyl radicals are summarized in Table 5.12. 

A correlation for less structurally related compounds was also developed by Amalric et al. (1996). To develop this correlation, meta- and para-substituted anisoles were studied. These aromatic compounds were substituted with F, Cl, N02, OH, and NH2 groups. The first-order degradation rate constant, kapf was predicted with the octanol/water partition coefficient (log Kow), Brown s constant (o+), and molar refractivity (MR) used as descriptors. The following correlation was developed ... 

Various sets of aromatic compounds and three different molecular descriptors such as EHOmo/ Elumo, and Hammett s constants have been used for other QSAR models. First-order kinetic rates, pseudo first-order kinetic rates, and activation energy were used to correlate with different molecular descriptors. 

A set of four aromatic compounds such as m-cresol, m-hydroxybenzalde-hyde, p-hydroxybenzaldehyde, and phenol was used to correlate pseudo first-order kinetic rates and EHOMO descriptors. From Figure 10.18, it can be observed that the correlation between pseudo first-order kinetic rates and Ehomo descriptors behaved the same as the correlations of aliphatic compounds. In other words, even though the first-order kinetic rate and pseudo first-order kinetic rate were treated as distinct kinetic parameters, these two correlations behaved the same. 

The first set of aromatic compounds that were analyzed using ELUMO as the molecular descriptor and the first-order kinetic rate as the kinetic parameter was composed of 2,4-dichlorophenol, pyridine, phenol, and 1,3-dichlorobenzene. The correlation between the first-order kinetic rates of the compounds and ELUMO reflected a coefficient of r2 = 0.7834. Figure 10.20 shows the correlation of this set of aromatic compounds. From this figure, it can be seen that the kinetic rate increases as ELUMO increases. The F test showed that the level of significance was 2.5%. Because the Fa4)0.975 of 12.56 is larger than 12.2, it can be concluded that a relationship exists between the two variables ... 

The QSAR models can be used to estimate the treatability of organic pollutants by SCWO. For two chemical classes such as aliphatic and aromatic compounds, the best correlation exists between the kinetic rate constants and EHOMO descriptor. The QSAR models are compiled in Table 10.13. By analyzing the behavior of the kinetic parameters on molecular descriptors, it is possible to establish a QSAR model for predicting degradation rate constants by the SCWO for organic compounds with similar molecular structure. This analysis may provide an insight into the kinetic mechanism that occurs with this technology. 

Helguera-Morales et al. [83] used a topological sub-structural molecular design (TOPS-MODE) approach to predict the carcinogenicity of 48 nitro-aromatic compounds in female rodents. Topological descriptors are derived mainly from knowledge of the connectivity between atoms within a molecule, and are based to some extent on information on atom types and their electronic environment. The model was able to describe 79.1% of the experimental data. It was found that the carcinogenic activity of the compounds analyzed increases in the presence of a primary... 

Gini, G., Lorenzini, M., Benfenati, E., Grasso, P., and Bruschi, M., Predictive carcinogenicity a model for aromatic compounds, with nitrogen-containing substituents, based on molecular descriptors using artificial neural network, J. Chem. Inf. Comput. Sci., 39, 1076-1080, 1999. 

In contrast to the expected classification, the obvious effect is the discrimination between aliphatic and aromatic compounds. We achieve a better result by excluding unnecessary information. A clear discrimination occurs by excluding hydrogen atoms from the calculation (Figure 6.11, right). Whereas the normal descriptor describes the aliphatic character of the compounds, the hydrogen-excluded descriptor emphasizes the differences in heteroatoms correctly. 

Panek, J.J., Jezierska, A. and Vracko, M. (2005) Kohonen network study of aromatic compounds based on electronic and nonelectronic structure descriptors. J. Chem. Inf. Model., 45, 264—272. 

Table I. Retention descriptions by multi-combination of two descriptors for aromatic compounds, where the following relationship is assumed ...

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