Quantitative modeling for prediction of boiling points of phenolic compounds

Year 2019, , 121 - 128, 31.12.2019

Soumaya Kherouf Nabil Bouarra , Djelloul Messadi

https://doi.org/10.32571/ijct.636581

Cited By: 1

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 (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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