QSRR Study of Organic Dyes by Multiple Linear Regression Method Based on Genetic Algorithm (GA–MLR


Journal: Vol.9, No.3, Summer 2016 - Article 6   Pages :  195 Until 206



Article Code:
PCCC-2016-06-08-328

Authors:
Davoud Beiknejad: University of Mazandaran - Faculty of Chemistry
Mohammad Javad Chaichi: University of Mazandaran - Faculty of Chemistry
Mohammad Hossein Fatemi: University of Mazandaran - Faculty of Chemistry


Article's abstract:

Quantitative structure-retention relationships (QSRRs) are used to correlate paper chromatographic retention factors of disperse dyes with theoretical molecular descriptors. A data set of 23 compounds with known RF values was used. The genetic algorithm-multiple linear regression analysis (GA-MLR) with three selected theoretical descriptors was obtained. The stability and predictability of the model was validated by use of leave-one-out (LOO), leave-many-out (LMO) cross-validation, external validation, Y-randomization and applicability domain (AD) analysis. The GA-MLR revealed a statistically meaningful model showing the dependence of the RF value on sum of topological distances between N and Br atoms (T(N..Br)), global topological charge index (JGT) and R autocorrelation of lag 5 / unweighted (R5u_A) of the compounds.


Keywords:
Disperse dyes, GA-MLR, Paper chromatography, Quantitative structure-retention relationship (QSRR)

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