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QUANTITATIVE STRUCTURE–PROPERTY RELATIONSHIP (QSPR) STUDY OF KOVATS RETENTION INDICES OF SOME OF ADAMANTANE DERIVATIVES BYTHE GENETIC ALGORITHM AND MULTIPLE LINEAR REGRESSION (GA-MLR) METHOD

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Author(s): Z. Bayat | M. Fakoor Yazdan Abad

Journal: Petroleum and Coal
ISSN 1337-7027

Volume: 53;
Issue: 2;
Start page: 132;
Date: 2011;
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Keywords: Adamantane derivatives | Kovats retention indices(RI) | genetic algorithm | MLR | QSPR.

ABSTRACT
A quantitative structure–property relationship (QSPR) study was performed to develop models those relate the structures of 65 Kovats retention index (RI) of adamantane derivatives. Molecular descriptors derived solely from 3D structures of the molecular compounds. A genetic algorithm was also applied as a variable selection tool in QSPR analysis. The models were constructed using 52 molecules as training set, and predictive ability tested using 13 compounds. Modeling of RI of Adamantane derivatives as a function of the theoretically derived descriptors was established by multiple linear regression (MLR). The usefulness of the quantum chemical descriptors, calculated at the level of the DFT theories using 6-311+G** basis set for QSAR study of adamantane derivatives was examined. The use of descriptors calculated only from molecular structure eliminates the need to experimental determination of properties for use in the correlation and allows for the estimation of RI for molecules not yet synthesized. Application of the developed model to testing set of 13 drug organic compounds demonstrates that the model is reliable with goo predictive accuracy and simple formulation. The prediction results are in good agreement with the experimental value. A multi-parametric equation containing maximum Four descriptors at B3LYP/6-31+G** method with good statistical qualities (R2train=0.913, Ftrain=97.67, R2test=0.770, Ftest=3.21, Q2LOO=0.895, R2adj=0.904, Q2LGO=0.844) was obtained by Multiple Linear Regression using stepwise method.

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