Quantitative structure–retention relationship model for predicting retention indices of constituents of essential oils of Thymus vulgaris (Lamiaceae) (Short communication)

Youssouf Driouche, Djelloul Messadi

Abstract


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 HyperChem software. Then, molecular descriptors covering dif­fer­ent information of molecular structures were calculated by Dragon software. The results illustrated that linear techniques, such as multiple linear regression (MLR), combined with a successful variable selection procedure are capable of generating 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.


Keywords


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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