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Year : 2023, Volume : 16, Issue : 5
First page : ( 358) Last page : ( 362)
Print ISSN : 0974-4169. Online ISSN : 0974-4150. Published online : 2023  13.
Article DOI : 10.52711/0974-4150.2023.00057

Development of QSRR model of a set of Polycyclic Aromatic Hydrocarbons (PAHs) using simple regression analysis in silico

Ziani Nadia1,4, Amirat Khadidja2,4, Meneceur Souhaila3,4, Bouafia Abderrhmane3,*

1Faculty of Science, Chemistry DepartmentBadji Mokhtar University Annaba, Annaba, Algeria

2Faculty of Science, Department of ChemistryUniversity of Sétif 1 – Ferhat Abbas, El Bez, Setif19000

3Department of Process Engineering and Petrochemistry, Faculty of Technology, University of El Oued, 39000El-Oued, Algeria

4Renewable Energy Development Unit in Arid Zones (UDERZA), University of El OuedEl-Oued, Algeria

*Corresponding Author E-mail: abdelrahmanebouafia@gmail.com

Online Published on 13 February, 2024.

Received:  30  November,  2022; Accepted:  19  September,  2023.

Abstract

A structure/retention indices relationship was searched for 59 PAHs while promoting the simple linear regression by genetic algorithm MOBIDYGS software, the structural parameters being calculated with the software Spartan and DRAGON. Among about a hundred of one-regression models gotten, we selected the one that present best values of the prediction parameter (Q2) and of the determination coefficient (R2). The robustness of obtaining model were illustrated using different techniques: leave-many-out, external-validation, randomization test, applicability domain.

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Keywords

Molecular descriptors, PAHs, Software, Structure/ retention indices, Genetic algorithm.

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