Theoretical Molecular Descriptors Relevant to the Uptake of Persistent Organic Pollutants from Soil by Zucchini. A QSAR Study

The uptake of persistent organic pollutants (POPs) from soil by plants allows the development of phytoremediation protocols to rehabilitate contaminated areas. The use of diverse theoretical descriptors has been reported in the literature for developing quantitative structure−activity relationship (...

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Veröffentlicht in:Journal of agricultural and food chemistry 2011-04, Vol.59 (7), p.2863-2869
Hauptverfasser: Bordas, Barna, Belai, Ivan, Komives, Tamas
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container_title Journal of agricultural and food chemistry
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creator Bordas, Barna
Belai, Ivan
Komives, Tamas
description The uptake of persistent organic pollutants (POPs) from soil by plants allows the development of phytoremediation protocols to rehabilitate contaminated areas. The use of diverse theoretical descriptors has been reported in the literature for developing quantitative structure−activity relationship (QSAR) models for predicting the bioconcentration factors (BCFs) of POPs in different plants. In this paper an evaluation is given on the molecular properties of POPs in terms of theoretical molecular descriptors that are relevant to the uptake and accumulation of these persistent pollutants from soil by two zucchini varieties. Statistically significant and predictive linear regression models have been developed for the BCF values of 20 polychlorinated dibenzo-p-dioxins/dibenzofurans and 14 polyhalogenated biphenyls in two zucchini varieties based on retrospective data. The relevant parameters have been selected from a set of 1660 DRAGON, 150 VolSurf, and 11 quantum chemical descriptors. The two most significant regression models, containing VolSurf, DRAGON GETAWAY, and quantum chemical descriptors, displayed the following statistical parameters: (eq ) n = 27, R 2 = 0.940, q 2 = 0.922, SE = 0.155, F = 392.1; (eq ) n = 27, R 2 = 0.921, q 2 = 0.898, SE = 0.161, F = 140.4. Predictive capabilities of the equations have been validated by using external validation sets. The QSAR models proposed might contribute to the development of viable soil remediation strategies.
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Statistically significant and predictive linear regression models have been developed for the BCF values of 20 polychlorinated dibenzo-p-dioxins/dibenzofurans and 14 polyhalogenated biphenyls in two zucchini varieties based on retrospective data. The relevant parameters have been selected from a set of 1660 DRAGON, 150 VolSurf, and 11 quantum chemical descriptors. The two most significant regression models, containing VolSurf, DRAGON GETAWAY, and quantum chemical descriptors, displayed the following statistical parameters: (eq ) n = 27, R 2 = 0.940, q 2 = 0.922, SE = 0.155, F = 392.1; (eq ) n = 27, R 2 = 0.921, q 2 = 0.898, SE = 0.161, F = 140.4. Predictive capabilities of the equations have been validated by using external validation sets. 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Statistically significant and predictive linear regression models have been developed for the BCF values of 20 polychlorinated dibenzo-p-dioxins/dibenzofurans and 14 polyhalogenated biphenyls in two zucchini varieties based on retrospective data. The relevant parameters have been selected from a set of 1660 DRAGON, 150 VolSurf, and 11 quantum chemical descriptors. The two most significant regression models, containing VolSurf, DRAGON GETAWAY, and quantum chemical descriptors, displayed the following statistical parameters: (eq ) n = 27, R 2 = 0.940, q 2 = 0.922, SE = 0.155, F = 392.1; (eq ) n = 27, R 2 = 0.921, q 2 = 0.898, SE = 0.161, F = 140.4. Predictive capabilities of the equations have been validated by using external validation sets. 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subjects Benzofurans - chemistry
Benzofurans - metabolism
bioaccumulation
Cucurbita - metabolism
equations
Linear Models
persistent organic pollutants
phytoremediation
Polychlorinated Dibenzodioxins - analogs & derivatives
Polychlorinated Dibenzodioxins - chemistry
Polychlorinated Dibenzodioxins - metabolism
prediction
Quantitative Structure-Activity Relationship
quantitative structure-activity relationships
regression analysis
soil
Soil Pollutants - chemistry
Soil Pollutants - metabolism
soil remediation
zucchini
title Theoretical Molecular Descriptors Relevant to the Uptake of Persistent Organic Pollutants from Soil by Zucchini. A QSAR Study
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