Descriptors, chemical

Quantum chemical descriptors such as atomic charges, HOMO and LUMO energies, HOMO and LUMO orbital energy differences, atom-atom polarizabilities, super-delocalizabilities, molecular polarizabilities, dipole moments, and energies sucb as the beat of formation, ionization potential, electron affinity, and energy of protonation are applicable in QSAR/QSPR studies. A review is given by Karelson et al. [45]. 

CODESSA (calculation of a series of difFerent descriptors including quantum chemical descriptors) Semichem Inc. - 7204 Mullen, Shawnee, KS 66216, USA http //www.semichem.com... 

Descriptors have to be found representing the structural features which are related to the target property. This is the most important step in QSPR, and the development of powerful descriptors is of central interest in this field. Descriptors can range from simple atom- or functional group counts to quantum chemical descriptors. They can be derived on the basis of the connectivity (topological or... 

A number of properties can be computed from various chemical descriptors. These include physical properties, such as surface area, volume, molecular weight, ovality, and moments of inertia. Chemical properties available include boiling point, melting point, critical variables, Henry s law constant, heat capacity, log P, refractivity, and solubility. 

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). 

Sorich MJ, McKinnon RA, Miners JO, Winkler DA, Smith PA. Rapid prediction of chemical metabolism by human UDP-glucuronosyltransferase isoforms using quantum chemical descriptors derived with the electronegativity equalization method. J Med Chem 2004 47 5311-7. 

Chemical Backgrounders is maintained by the National Safety Council and contains chemical descriptors including properties, health effects, exposure and regulatory information. (1 can t access is membership required ). 

In the last decades not only thousands of chemical descriptors but also many advanced, powerful modeling algorithms have been made available, The older QSAR models were linear equations with one or a few parameters. Then, other tools have been introduced, such as artificial neural network, fuzzy logic, and data mining algorithms, making possible non linear models and automatic generation of mathematical solutions. 

More typically the process of building up the QSAR models requires more complex chemical information. For a set of compounds, with known property value, the descriptors are calculated. The process of model building proceeds through a reduction of the molecular descriptors, in order to indentify the most important ones. Then, using these selected chemical descriptors and a suitable algorithm, the model is developed. Finally, the model so obtained has to be validated. 

A few decades ago the range of chemical descriptors used was very limited. Let us take the example of Corwin Hansch s studies, in which he described the relationship between ecotoxicity and a series of parameters, including log P... 

Over time other descriptors have been investigated in an attempt to better explain certain factors, such as chemical reactivity and molecular size. Nowadays thousands of chemical descriptors can be calculated and thousands of fragments can be obtained using other programs. 

There are some chemometric (chemometrics is a statistical area which combines statistics and chemistry) tools which use the chemical descriptors and/or fragments of the chemicals used to build up the model, and compare if the chemical descriptors and/or fragments of the target chemical are similar. An example of this approach is given by the freely available software AMBIT. A major disadvantage of this approach is that it is based only on the chemical information. 

When suitable data sets are defined, different approaches can be used to codify the chemical information within chemical descriptors. Nowadays we have powerful tools to describe them in different ways by their physicochemical properties, surface properties, or their 3D fields generated by interactions with different chemical probes. Typically many chemical descriptors are calculated (up to thousands) and then the important ones are selected. We briefly explain some of the most common approaches used, trying to classify them in families to simplify the overview. 

Karelson, M. and Lobanov, V.S. (1996). Quantum-chemical descriptors in QSAR/ QSPR studies. Chemical Reviews 96 1027-1043. 

Dearden, J. C. (1990) Physico-chemical descriptors. In Practical Applications of Quantitative Structure-Activity Relationships (QSAR) in Environmental Chemistry and Toxicology. Karcher, W. and Devillers, J., Eds., pp. 25-60. Kluwer Academic Publisher, Dordrecht, The Netherlands. 

Since experimental mechanistic investigations measure activation volumes, Rotzinger proposed to use in calculations, the currently well-accepted quantum chemical descriptor difference of sums ofr(M-O) , A Sr, for the volume of activation, AV (160). As the structures are all similar (Table I) this descriptor is in all four cases identical. 

In which the terms Ha refers to the number of free electron pairs, MW is the molecular weight, and clogP is the computed lipophilicity. While this method could be stated to be "partially in silico" because it utilizes some chemical descriptors, the need for in vivo animal data and their dominance in the individual terms really makes this approach more of an animal-human correlation than an in silico method. Finally, in the same report, the authors describe a regression based solely in animal data. Overall, the performance of these... 

Using a 70-drug set, Ghafourian et al., conducted a statistical analysis of computed chemical descriptors to predict human VD [36]. The descriptors found to provide a predictive model included logP, logDi, and Pmm (a measure of dipole moment), in a linear regression ... 

Cross-compound correlation including chemical descriptors Human VD is related to animal VD and chemical structure VDSS in rat and dog, computed chemical parameters [13]... 

ANN VD is a function of specific chemical attributes Computed chemical descriptors [37]... 

Although one could consider the electron density as just one of the many quantum chemical descriptors available, it deserves special attention. In QSM, it is the only descriptor used for a number of reasons. The idea of using the electron density as the ultimate molecular descriptor is founded on the basic elements of quantum mechanics. First of all, it is the all-determinmg quantity in density functional theory (DFT) [11] and also holds a very close relation to the wave function. Convincing arguments were given by Handy and are attributed to Wilson [12], although initial ideas can also be traced back to Bom [13] and von... 

DFT reactivity theory is a perturbative approach in which the chemical descriptors are defined for isolated chemical moieties. For this reason, they provide only an indirect and approximative description of the actual reaction between two reagents, which approach each other at a chemical bond distance in well-defined physicochemical conditions (temperature, pressure, salt, etc.). It is legitimate to have doubts about the relevance of the DFT descriptors for chemistry. Are the DFT descriptors really useful The answer to this provocative question is yes for the following reasons. 

Basak, S. C., Mills, D., Hawkins, D. M. Predicting allergic contact dermatitis A hierarchical structure-activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors. J. Comput. Aided Mol. Des., 2008, 22, 339-343. 

Kortvelyesi, T., Gorgenyi, M., Heberger, K. Anal. Chim. Acta 428, 2001, 73-82. Correlation between retention indices and quantum-chemical descriptors of ketones and aldehydes on stationary phases of different polarity. 

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