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Quantitative structure activity relationship (QSAR) for toxicity of [An article from: Chemosphere]
Description
This digital document is a journal article from Chemosphere, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Quantitative structure activity relationship (QSAR) were developed to predict toxicity of chlorophenols by correlating LC"5"0 values with five molecular descriptors, chosen to represent lipophilic, electronic and steric effects: the n-octanol/water partition coefficient (logK"o"w), the constant of Hammett (@?@s), the acid dissociation constant (pK"a), the order valence molecular connectivity index (^1@g^v) and the perimeter of the efficacious section (@?D"g). The results of the regression analysis showed that logK"o"w and @?D"g are the dominant (canonical) predictive factors in determining toxicity of chlorophenols to the cells during 24h exposures, while logK"o"w was the only dominant predictive factor contributing to toxicity during in 48h exposures. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to investigate predictive relationships of the cytotoxicity of chlorophenols and develop visual 3D-QSAR models. The CoMFA model, in which the contribution of the electrostatic field to the biological activity was greater than that of the steric field, exhibited both high consistency and predictability (r^2=0.968, Q^2=0.891 for 24h exposure; but the relationship was poorer for the 48h exposure: r^2=0.727, Q^2=0.394). The CoMSIA model used in this study contained three fields: electrostatic, hydrophobic and steric, of which the relative contribution to the biological activity was 0.767:0.225:0.008. In addition, according to the models for 24h and 48h. The time-dependent toxicity and potential mechanisms for inhibition of L929 cells was discussed.
Description:
Quantitative structure activity relationship (QSAR) were developed to predict toxicity of chlorophenols by correlating LC"5"0 values with five molecular descriptors, chosen to represent lipophilic, electronic and steric effects: the n-octanol/water partition coefficient (logK"o"w), the constant of Hammett (@?@s), the acid dissociation constant (pK"a), the order valence molecular connectivity index (^1@g^v) and the perimeter of the efficacious section (@?D"g). The results of the regression analysis showed that logK"o"w and @?D"g are the dominant (canonical) predictive factors in determining toxicity of chlorophenols to the cells during 24h exposures, while logK"o"w was the only dominant predictive factor contributing to toxicity during in 48h exposures. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to investigate predictive relationships of the cytotoxicity of chlorophenols and develop visual 3D-QSAR models. The CoMFA model, in which the contribution of the electrostatic field to the biological activity was greater than that of the steric field, exhibited both high consistency and predictability (r^2=0.968, Q^2=0.891 for 24h exposure; but the relationship was poorer for the 48h exposure: r^2=0.727, Q^2=0.394). The CoMSIA model used in this study contained three fields: electrostatic, hydrophobic and steric, of which the relative contribution to the biological activity was 0.767:0.225:0.008. In addition, according to the models for 24h and 48h. The time-dependent toxicity and potential mechanisms for inhibition of L929 cells was discussed.
