Predicting retention indices of PAHs in reversed-phase liquid chromatography: Quantitative structure retention relationship approach

Authors

  • Nabil Bouarra Centre de Recherche Scientifique et Technique en Analyses Physico–Chimiques, BP 384, Zone Industrielle Bou-Ismail, 42004 Tipaza, Algeria https://orcid.org/0000-0001-5438-8678
  • Nawel Nadji Centre de Recherche Scientifique et Technique en Analyses Physico–Chimiques, BP 384, Zone Industrielle Bou-Ismail, 42004 Tipaza, Algeria
  • Loubna Nouri Centre de Recherche Scientifique et Technique en Analyses Physico–Chimiques, BP 384, Zone Industrielle Bou-Ismail, 42004 Tipaza, Algeria
  • Amel Boudjemaa Centre de Recherche Scientifique et Technique en Analyses Physico–Chimiques, BP 384, Zone Industrielle Bou-Ismail, 42004 Tipaza, Algeria
  • Khaldoun Bachari Centre de Recherche Scientifique et Technique en Analyses Physico–Chimiques, BP 384, Zone Industrielle Bou-Ismail, 42004 Tipaza, Algeria https://orcid.org/0000-0003-0624-8480
  • Djelloul Messadi Laboratory of Environmental and Food Safety, Department of Chemistry, Badji Mokhtar– Annaba University, PB 12, 23000, Annaba, Algeria https://orcid.org/0000-0003-3257-9590

DOI:

https://doi.org/10.2298/JSC200219019B

Keywords:

genetic algorithm, multiple linear regression, prediction., molecular descriptors

Abstract

In this work, the liquid chromatography retention time in monomeric and polymeric stationary phases of PAHs was investigated. Quantitative struc­ture retention relationship approach has been successfully performed. At first, 3224 molecular descriptors were calculated for the optimized PAHs structure using Dragon software. Afterwards, the modelled dataset was divided using the CADEX algorithm into two subsets for internal and external validation. The genetic algorithm-based on a multiple linear regression was used for feature selection of the most significant descriptors and the model development. The selected models with five descriptors: nCIR, GGI3, GGI4, JGT and DP14 were used for the monomeric column and nR10, EEig01x, L1m, H5v and HATS6v were introduced for the polymeric column. Robustness and predictive perform­ance of the suggested models were verified by both internal and external sta­tis­tical validation. The good quality of the statistical parameters indicates the sta­bility and predictive power of the suggested models. This study demonstrated the suitability of the established models in the prediction of liquid chromato­graphic retention indices of PAHs.

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Published

2021-01-30

How to Cite

[1]
N. Bouarra, N. Nadji, L. Nouri, A. Boudjemaa, K. Bachari, and D. Messadi, “Predicting retention indices of PAHs in reversed-phase liquid chromatography: Quantitative structure retention relationship approach”, J. Serb. Chem. Soc., vol. 86, no. 1, pp. 63-75, Jan. 2021.

Issue

Section

Theoretical Chemistry