Quantitative structure-retention relationship model for predicting retention indices of constituents of essential oils of Thymus vulgaris Lamiaceae

Youssouf Driouche, Djelloul Messadi


In this paper, a quantitative structure-retention relationship (QSRR) model was developed for predicting the retention indices (log RI) of 36 constituents of essential oils. First, the chemical structure of each compound was sketched, using the Hyperchem software. Then the molecular descriptors which cover different information of molecular structures, were calculated by Dragon software. The results illustrated that the linear techniques such as multiple linear regression (MLR) combined with a successful variable selection procedure are capable to generate an efficient QSRR model for predicting the retention indices of different compounds. This model, with high statistical significance (R2 = 0.9781, Q2LOO = 0.9691, Q2Ext = 0.9546,Q2L(5)O = 0.9667, F = 245.27), could be used adequately for the prediction and description of the retention indices of other essential oil compounds. The reliability of the proposed model was further illustrated using various evaluation techniques: leave-5-out cross-validation, bootstrap, randomization test and validation through the test set.


essential oils; retention indices; QSRR; multiple linear regression; Thymus vulgaris Lamiaceae

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DOI: https://doi.org/10.2298/JSC180817010D

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