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Chemometric modeling of depruration rate constants of polycyclic aromatic hydrocarbons in mussels (Elliptiocomplanata)

Author Affiliations

  • 1Department of Chemistry, Kurukshetra University, Kurukshetra-136119, Haryana, India

Int. Res. J. Environment Sci., Volume 7, Issue (1), Pages 22-27, January,22 (2018)

Abstract

This paper describes the QSAR study to predict the depuration rate constants (kd) of a series of polycyclic aromatic hydrocarbons (PAHs) for mussels, Elliptiocomplanata. The reported Logkd values of 26 compounds have been mapped linearly by means of stepwise multiple linear regression and non-linearly by artificial neural network trained with Levenberg-Marquardt (LM) algorithm, using molecular descriptors derived online from mole-db software. Descriptors selected by SW-MLR were used to develop non-linear model. The models were validated for predictability by both internal and external validation. Both linear and non-linear models satisfy the criteria of external validation as recommended by Golbraikh and Trospha. Comparison of quality of best ANN (R2 = 0.96) model with SW-MLR (R2 = 0.94) model showed that ANN trained with robust LM algorithm has better predictive power. Applicability domain analysis has also revealed that the suggested models have acceptable predictability.

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