Quantitative structure-activity relationship quantum chemical descriptors

A quantitative structure-activity relationship of 1,4-dihydropyridine calcium channel blockers with electronic descriptors produced by quantum chemical topology... 

Wan, J., Zhang, L., Yang, G. and Zhan, C.-G. (2004) Quantitative structure-activity relationship for cydic imide derivatives of protoporphyrinogen oxidase inhibitors a study of quantum chemical descriptors from density functional theory /. Chem. Inf. Comput. Sci., 44, 2009—2105. 

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. 

The quantum-chemical molecular descriptors have been widely used in the development of quantitative structure-activity relationships for various pharmacological activities of compounds. Again, most of the QSARs developed include the electrostatic and/or MO-related descriptors. 

Other pharmacological activities have also been correlated with quantum-chemically derived descriptors. For instance, the quantitative structure-activity relationship developed for the antibacterial activity of a series of monocyclic (i-lactam antibiotics included the atomic charges, the bond orders, the dipole moment, and the first excitation energy of the compound [103]. The fungicidal activity of A3-l,2,4-thiadiazolines has been correlated with an index of frontier orbital electron density derived from semi-empirical PM3 molecular orbital calculations [104],... 

Vectors A series of scalars can be arranged in a column or in a row. Then, they are called a column or a row vector. If the elements of a column vector can be attributed to special characteristics, e.g., to compounds, then data analysis can be completed. The chemical structures of compounds can be characterized with different numbers called descriptors, variables, predictors, or factors. For example, toxicity data were measured for a series of aromatic phenols. Their toxicity can be arranged in a column arbitrarily Each row corresponds to a phenolic compound. A lot of descriptors can be calculated for each compound (e.g., molecular mass, van der Waals volume, polarity parameters, quantum chemical descriptors, etc.). After building a multivariate model (generally one variable cannot encode the toxicity properly) we will be able to predict toxicity values for phenolic compounds for which no toxicity has been measured yet. The above approach is generally called searching quantitative structure - activity relationships or simply QSAR approach. 

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. 

Chemical reactivity and biological activity can be related to molecular structure and physicochemical properties. QSAR models can be established among hydrophobic-lipophilic, electronic, and steric properties, between quantum-mechanics-related parameters and toxicity and between environmental fate parameters such as sorption and tendency for bioaccumulation. The main objective of a QSAR study is to develop quantitative relationships between given properties of a set of chemicals and their molecular descriptors. To develop a valid QSAR model, the following steps are essential ... 

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