Evaluation Of Quantitative Structure-activity Relationships Research Articles

Incorporation of absorption and metabolism into liver toxicity prediction for phytochemicals: A tiered in silico QSAR approach

An increased use of herbal dietary supplements has been associated with adverse liver effects such as elevated serum enzymes and liver failure. The safety assessment for herbal dietary supplements is challenging since they often contain complex mixtures of phytochemicals, most of which have unknown pharmacokinetic and toxicological properties. Rapid tools are needed to evaluate large numbers of phytochemicals for potential liver toxicity. The current study demonstrates a tiered approach combining identification of phytochemicals in liver toxic botanicals, followed by in silico quantitative structure-activity relationship (QSAR) evaluation of these phytochemicals for absorption (e.g. permeability), metabolism (cytochromes P450) and liver toxicity (e.g. elevated transaminases). First, 255 phytochemicals from 20 botanicals associated with clinical liver injury were identified, and the phytochemical structures were subsequently used for QSAR evaluation. Among these identified phytochemicals, 193 were predicted to be absorbed and then used to generate metabolites, which were both used to predict liver toxicity. Forty-eight phytochemicals were predicted as liver toxic, either due to parent phytochemicals or metabolites. Among them, nineteen phytochemicals have previous evidence of liver toxicity (e.g. pyrrolizidine alkaloids), while the majority were newly discovered (e.g. sesquiterpenoids). These findings help reveal new toxic phytochemicals in herbal dietary supplements and prioritize future toxicological testing.

QSAR Analysis of Substituted 2-Phenylhydrazonoacetamides Acting as Inhibitors of 15-Lipoxygenase

An evaluation of quantitative structure-activity relationships (QSAR) for 28 N1-phenyl-2-phenylhydrazonoacetamides, that are inhibitors of soybean 15-lipoxygenase was carried out with different statistical methods. Initially the variation of structure was characterized by the Free-Wilson method and analyzed by multiple linear regression (MLR) and partial least squares analysis (PLS). Both methods revealed an increase in activity, if the N1-phenyl substituent of the parent molecule is meta-substituted with groups, that show a positive resonance effect at the annular structure. To include physicochemical aspects a combined Free-Wilson-Hansch approach was used. Because of high intercorrelations among some physicochemical parameters a principal component-analysis (PCA) was performed to extract information from those intercorrelated variables in a few principal components (PC's). The resulting equations indicate that besides an electron donating group at the central amidrazone moiety electronic effects at the arylhydrazone substituent play an important role for the biological activity.

Metal toxicity in two rodent species and redox potential: Evaluation of quantitative structure-activity relationships.

A quantitative structure-activity relationship study of acute toxicity in the mouse and rat is described for the soluble salts of a relatively large number of metals (between 25 and 30 in total). Electrode potential is the major determinant of acute metal toxicity (R = 0.85 and 0.86) for an intraperitoneal dose in the mouse, whereas the addition of ionic radius and polarizability enables the inclusion of notable outliers in the original expression, such as beryllium and barium, thus giving a good correlation (R = 0.87) with toxicity for 27 metal compounds. These findings are rationalized on the basis of relative ease of ionization, electron affinity, and transport factors of the metals and their ions, thus being consistent with the hard and soft acids and bases properties of metals and their biological reactivities.

A QSAR evaluation of Ah receptor binding of halogenated aromatic xenobiotics.

Because of their widespread occurrence and substantial biological activity, halogenated aromatic hydrocarbons such as polychlorinated biphenyls (PCBs), polychlorinated dibenzofurans (PCDFs), and polychlorinated dibenzo-p-dioxins (PCDDs) comprise one of the more important classes of contaminants in the environment. Some chemicals in this class cause adverse biological effects after binding to an intracellular cytosolic protein called the aryl hydrocarbon receptor (AhR). Toxic responses such as thymic atrophy, weight loss, immunotoxicity, and acute lethality, as well as induction of cytochrome P4501A1, have been correlated with the relative affinity of PCBs, PCDFs, and PCDDs for the AhR. Therefore, an important step in predicting the effects of these chemicals is the estimation of their binding to the receptor. To date, however, the use of quantitative structure activity relationship (QSAR) models to estimate binding affinity across multiple chemical classes has shown only modest success possibly due, in part, to a focus on minimum energy chemical structures as the active molecules. In this study, we evaluated the use of structural conformations other than those of minimum energy for the purpose of developing a model for AhR binding affinity that encompasses more of the halogenated aromatic chemicals known to interact with the receptor. Resultant QSAR models were robust, showing good utility across multiple classes of halogenated aromatic compounds.

A QSAR Evaluation of Ah Receptor Binding of Halogenated Aromatic Xenobiotics

Because of their widespread occurrence and substantial biological activity, halogenated aromatic hydrocarbons such as polychlorinated biphenyls (PCBs), polychlorinated dibenzofurans (PCDFs), and polychlorinated dibenzo-p-dioxins (PCDDs) comprise one of the more important classes of contaminants in the environment. Some chemicals in this class cause adverse biological effects after binding to an intracellular cytosolic protein called the aryl hydrocarbon receptor (AhR). Toxic responses such as thymic atrophy, weight loss, immunotoxicity, and acute lethality, as well as induction of cytochrome P4501A1, have been correlated with the relative affinity of PCBs, PCDFs, and PCDDs for the AhR. Therefore, an important step in predicting the effects of these chemicals is the estimation of their binding to the receptor. To date, however, the use of quantitative structure activity relationship (QSAR) models to estimate binding affinity across multiple chemical classes has shown only modest success possibly due, in part, to a focus on minimum energy chemical structures as the active molecules. In this study, we evaluated the use of structural conformations other than those of minimum energy for the purpose of developing a model for AhR binding affinity that encompasses more of the halogenated aromatic chemicals known to interact with the receptor. Resultant QSAR models were robust, showing good utility across multiple classes of halogenated aromatic compounds.