Quantitative modeling for prediction of boiling points of phenolic compounds

Authors : Soumaya KHEROUF, Nabil BOUARRA, Djelloul MESSADİ

Pages : 121-128

Doi:10.32571/ijct.636581

View : 37 | Download : 7

Publication Date : 2019-12-31

Article Type : Research Paper

Abstract :This work aims to reveal the correlation of the boiling point values of phenolic compounds with their molecular structures using a quantitative structure-property relationship insert ignore into journalissuearticles values(QSPR); approach. A large number of molecular descriptors have been calculated from molecular structures by the DRAGON software. In this study, all 56 phenolic compounds were divided into two subsets: one for the model formation and the other for external validation, by using the Kennard and Stone algorithm. A four-descriptor model was constructed by applying a multiple linear regression based on the ordinary least squares regression method and genetic algorithm/variables subsets selection. The good of fit and predictive power of the proposed model were evaluated by different approaches, including single or multiple output cross-validations, the Y-scrambling test, and external validation through prediction set. Also, the applicability domain of the developed model was examined using Williams plot. The model shows R² = 0.876, Q² LOO = 0.841, Q² LMO = 0.831 and Q² EXT = 0.848. The results obtained demonstrate that the model is reliable with good predictive accuracy.
Keywords : Phenolic compounds, Boiling point, QSPR, MLR, Prediction set

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