Prediction of mixture toxicity with its total hydrophobicity

Based on the C18 Empore disk/water partition coefficient of a mixture, quantitative structure-activity relationships (QSARs) are presented, which are used to predict the toxicity of mixed halogenated benzenes to P. phosphoreum. The predicted toxicity of 10 other related mixtures based on the QSAR model, agree well with the observed data with r2 = 0.973, SE = 0.113 and F = 287.785 at a level of significance P < 0.0001. The joint effect of these chemicals is simple similar action and the toxicity of the mixtures can be predicted from total hydrophobicity and is independent of hydrophobicity of the components or the ratio of the individual chemicals.     

Structure-activity relationships and response-surface analysis of nitroaromatics toxicity to the yeast (Saccharomyces cerevisiae)

Inhibition of growth of the yeast Saccharomyces cerevisiae (Cmiz, the minimum concentration that produced a clear inhibition zone within 12 h) for 24 nitroaromatic compounds was investigated and a quantitative structure-activity relationship (QSAR) developed based on hydrophobicity expressed as the l-octanol/water partition coefficient in logarithm form, log K(ow), electrophilicity based on the energy of the lowest unoccupied orbital (E(lumo)). All nitrobenzene derivatives exhibited enhanced reactive toxicity than baseline. The toxicities of mono-nitrobenzenes and di-nitrobenzenes were elicited by different mechanisms of toxic action. For mono-nitro-derivatives, both significant log K(ow) based and strong E(lumo)-dependent relationships were observed indicating that their toxicities were affected both by the penetration process and the interaction with target sites of interaction. The toxicities of di-nitrobenzenes were greater than mono-nitrobenzenes and no log K(ow)-dependent but highly significant E(lumo)-based relationship was obtained. This suggests that toxicity of di-nitrobenzenes was highly electrophilic and involved mainly their in vivo electrophilic interaction with biomacromolecules. In an effort to model the elevated toxicity of all nitrobenzenes, a response-surface analysis was performed and this resulted in a highly predictive two-variable QSAR without reference to their exact mechanisms (Cmiz = 0.41 log K(ow) - 0.89 E(lumo) - 0.46, r2 = 0.87, Q2 = 0.86, n = 24).     

Mechanism-based quantitative structure-activity relationships for the inhibition of substituted phenols on germination rate of Cucumis sativus

Comparative inhibition activity (GC50) of 42 structurally diverse substituted phenols on seed germination rate of Cucumis sativus was investigated. Quantitative structure-activity relationships (QSARs) were developed by using hydrophobicity (1-octanol/water partition coefficient, logKow) and electrophilicity (the energy of the lowest unoccupied molecule orbital, Eluma) for the toxicity of phenols according to their modes of toxic action. Most phenols elicited their response via a polar narcotic mechanism and a highly significant log Kow-based model was obtained (GC50 = 0.92 log Kow + 1.99, r2 0.84, n = 29). The inclusion of E(lumo) greatly improved the predictive power of the polar narcotic QSAR (GC50 = 0.88 log Kow - 0.30E(lumo) + 1.99, r2 = 0.93, n = 29). pKa proved to be an insignificant influencing factor in this study. Poor correlation with hydrophobicity and strong correlation with electrophilicity were observed for the nine bio-reactive chemicals. Their elevated toxicity was considerably underestimated by the polar narcotic logKow-dependent QSAR. The nine chemicals consist of selected nitro-substituted phenols, hydroquinone, catechol and 2-aminophenol. Their excess toxic potency could be explained by their molecular structure involving in vivo reaction with bio-macromolecules. Strong dissociation of carboxyl group of the four benzoic acid derivatives greatly decreased their observed toxicity. In an effort to model all chemicals including polar narcotics and bio-reactive chemicals, a response-surface analysis with the toxicity, logKow and E(lumo) was performed. This resulted in a highly predictive two-parameter QSAR for most of the chemicals (GC50 = 0. 70 logKow - 0.66E(lumo) + 2.17, r2 = 0.89, n = 36). Catechol and 2,4-dinitrophenol proved to be outliers of this model and their much high toxicity was explained.     

Quantitative structure-activity relationships for the inhibition toxicity to root elongation of Cucumis sativus of selected phenols and interspecies correlation with Tetrahymena pyriformis

The comparative toxicities of selected phenols to higher plants Cucumis sativus were measured and the negative logarithm molar concentration of the root elongation median inhibition (IRC50) were derived. Quantitative structure-activity relationships (QSARs) were developed to explore the toxicity influencing factors and for predictive purpose. The toxicity data, fell into two classes: polar narcosis and bio-reactive. For polar narcotic phenols, a highly significant two-parameter QSAR based on 1-octanol/water partition coefficient (logKow) and energy of the lowest unoccupied orbital (E(lumo)) was derived (IRC50 = 0.77 log Kow - 0.39E(lumo) + 2.36 n = 22 r2 = 0.89). The five bio-reactive chemicals proved to show elevated toxicity due to their typical substructure involved diverse reactive mechanisms. In an effort to model all chemicals, a robust multiple-variable QSAR combining logKow, E(lumo) and Qmax, the most negative net atomic charge, was developed (IRC50 = 0.65 logKow - 0.72E(lumo) + 0.23Qmax + 2.81 n = 27 r2 = 0.94), indicating that hydrophobicity, electrophilicity and hydrogen bond interaction contribute mainly to the phytotoxicity. The toxicological data was compared with Tetrahymena pyriformis 2-d population growth inhibition toxicity (IGC50) and excellent interspecies correlations were observed both for the polar narcotics and for five reactive chemicals (for polar narcotics: IRC50 = 0.95IGC50 + 1.07 n = 16 r2 = 0.89; for bio-reactive chemicals: IRC50 = 0.98IGC50 + 2.19 n = 5 r2 = 0.97; and for all: IRC50 = 0.93IGC50 + 1.63 n = 21 r2 = 0.87). This suggested that T pyriformis toxicity could serve as a surrogate of C. sativus toxicity for phenols and interspecies correlation also could be established for reactive chemicals.     

The effect of nitroaromatics' composition on their toxicity in vivo: novel, efficient non-additive 1D QSAR analysis

Novel 1D QSAR approach that allows analysis of non-additive effects of molecular fragments on toxicity has been proposed. Twenty-eight nitroaromatic compounds including some well-known explosives have been chosen for this study. The 50% lethal dose concentration for rats (LD50) was used as the estimation of toxicity in vivo to develop 1D QSAR models on the framework of Simplex representation of molecular structure. The results of 1D QSAR analysis show that even the information about the composition of molecules provides the main trends of toxicity changes. The necessity of consideration of substituents' mutual impacts for the development of adequate QSAR models of nitroaromatics' toxicity was demonstrated. Statistic characteristics for all the developed partial least squares QSAR models, except the additive ones are quite satisfactory (R2=0.81-0.92; Q2=0.64-0.83; R2 test=0.84-0.87). A successful performance of such models is due to their non-additivity i.e. possibility of taking into account the mutual influence of substituents in benzene ring which plays the governing role for toxicity change and could be mediated through the different C-H fragments of the ring. The correspondence between observed and predicted by these models toxicity values is good. This allowing combine advantages of such approaches and develop adequate consensus model that can be used as a toxicity virtual screening tool.     

Separation of the strength and selectivity of the microbiological effect of synthetic dyes by spectral mapping technique

The growth inhibitory effect of 30 synthetic dyes on 22 bacteria (test organisms) belonging to various taxonomic groups was determined. The strength (potency) and selectivity of the biological effect were separated by the spectral mapping technique, reducing the dimensionality of the selectivity maps to two by the nonlinear mapping technique. The relationship between biological effect and physicochemical parameters of dyes was elucidated by stepwise regression analysis. It has been established that the strength of the effect of anthracene and trityl derivatives was higher than that of azobenzene dyes and significantly depended on the hydrophobicity of the compound. The selectivity of the effect also depended on hydrophobicity and on the nonpolar unsaturated surface area of the dyes. Gram negative and Gram positive bacteria differed in the strength and selectivity of their response to dyes indicating the marked impact of the taxonomical position on the response. Contrary to other multivariate mathematical statistical methods biological activity may be divided by SPM into potency and selectivity values, therefore, application of the technique in future QSAR studies is highly recommended.     

Mechanistic insights into the specificity of human cytosolic sulfotransferase 2A1 (hSULT2A1) for hydroxylated polychlorinated biphenyls through the use of fluoro-tagged probes

Determining the relationships between the structures of substrates and inhibitors and their interactions with drug-metabolizing enzymes is of prime importance in predicting the toxic potential of new and legacy xenobiotics. Traditionally, quantitative structure activity relationship (QSAR) studies are performed with many distinct compounds. Based on the chemical properties of the tested compounds, complex relationships can be established so that models can be developed to predict toxicity of novel compounds. In this study, the use of fluorinated analogues as supplemental QSAR compounds was investigated. Substituting fluorine induces changes in electronic and steric properties of the substrate without substantially changing the chemical backbone of the substrate. In vitro assays were performed using purified human cytosolic sulfotransferase hSULT2A1 as a model enzyme. A mono-hydroxylated polychlorinated biphenyl (4-OH PCB 14) and its four possible mono-fluoro analogues were used as test compounds. Remarkable similarities were found between this approach and previously published QSAR studies for hSULT2A1. Both studies implicate the importance of dipole moment and dihedral angle as being important to PCB structure in respect to being substrates for hSULT2A1. We conclude that mono-fluorinated analogues of a target substrate can be a useful tool to study the structure activity relationships for enzyme specificity.     

Fate and effect of monoalkyl quaternary ammonium surfactants in the aquatic environment

The effect of the alkyl chain of quaternary ammonium-based surfactants on their aquatic toxicity and aerobic biodegradability has been studied. Two families of monoalkylquats surfactants were selected: alkyl trimethyl ammonium and alkyl benzyl dimethyl ammonium halides. Acute toxicity tests on Daphnia magna and Photobacterium phosphoreum were carried out and EC50 values in the range of 0.1-1 mg/l were obtained for the two series of cationic surfactants. Although the substitution of a benzyl group for a methyl group increases the toxicity, an incremental difference in toxicity between homologs of different chain length were not observed. Biodegradability of the different homologs was determined not only in standard conditions but also in coastal water, both tests yielding similar results. An increase in the alkyl chain length or the substitution of a benzyl group for a methyl group reduces the biodegradation rate. The degradation of these compounds in coastal waters was associated with an increase in bacterioplankton density, suggesting that the degradation takes place because the compound is used as a growth substrate.     

A protocol to select high quality datasets of ecotoxicity values for pesticides

The key to any QSAR model is the underlying dataset. In order to construct a reliable dataset to develop a QSAR model for pesticide toxicity, we have derived a protocol to critically evaluate the quality of the underlying data. In developing an appropriate protocol that would enable data to be selected in constructing a QSAR, we concentrated on one toxicity end point, the 96 h LC50 from the acute rainbow trout study. This end point is key in pesticide regulation carried out under 91/414/EEC. The dataset used for this exercise was from the US EPA-OPP database.     

Quantification of joint effect for hydrogen bond and development of QSARs for predicting mixture toxicity

A QSAR model is successfully proposed to predict the toxicity effect on Photobacterium phosphoreum by nonpolar-narcotic-chemical mixtures and/or polar-narcotic-chemical mixtures. For nonpolar-narcotic-chemical mixtures and polar-narcotic-chemical mixtures, their corresponding hydrophobicity-based QSAR models are derived from regression analysis. Comparison of these two QSAR models make us believe that it is the joint effect of hydrogen bond in polar-narcotic-chemical mixture that leads to the difference between these two models. Such joint effect of hydrogen bond can be quantified as AMH and BMH by using the different partition coefficients of mixtures in various organic phase/water systems. And the regression analysis results convinced us that the introduction of AMH does improve the quality of the QSAR model with r2=0.948, S.E.=0.166 and F=745.201 at P=0.000 for total 84 mixtures.     

Treatment of solutions with binary solutes using an admicellar enhanced CSTR: background solute effect

This study presents an admicellar enhanced continuous-flow stirred tank reactor (CSTR). Solutions containing single and binary aliphatic alcohols are introduced into this reactor for breakthrough experiments. Two phenomena occur during experiments with binary solutes: (a) a competitive effect caused by background solutes with relatively high hydrophobicity; (b) a co-solvent effect attributable to background solutes with relatively low hydrophobicity. The competition phenomenon and the corresponding mechanism involved are well demonstrated by directly monitoring the pre-adsolubilized solutes drawn out back to the solution while adsolubilizing other solutes with higher hydrophobicity. On the other hand, adsolubilization kinetics hindered by the background solute, which acts as a co-solvent, significantly alters the slopes of breakthrough curves of the target solute treated in the reactor.     

Toxicity of 58 substituted anilines and phenols to algae Pseudokirchneriella subcapitata and bacteria Vibrio fischeri: comparison with published data and QSARs

A congeneric set of 58 substituted anilines and phenols was tested using the 72-h algal growth inhibition assay with Pseudokirchneriella subcapitata and 15-min Vibrio fischeri luminescence inhibition assay. The set contained molecules substituted with one, two or three groups chosen from -chloro, -methyl or -ethyl. For 48 compounds there was no REACH-compatible algal toxicity data available before. The experimentally obtained EC50 values (mg L⁻¹) for algae ranged from 1.43 (3,4,5-trichloroaniline) to 197 (phenol) and for V. fischeri from 0.37 (2,3,5-trichlorophenol) to 491 (aniline). Only five of the tested 58 chemicals showed inhibitory effect to algae at concentrations >100 mg L⁻¹, i.e. could be classified as “not harmful”, 32 chemicals as “harmful” (10-100 mg L⁻¹) and 21 as “toxic” (1-10 mg L⁻¹). The occupied para-position tended to increase toxicity whereas most of the ortho-substituted congeners were the least toxic. As a rule, the higher the number of substituents the higher the hydrophobicity and toxicity. However, in case of both assays, the compounds of similar hydrophobicity showed up to 30-fold different toxicities. There were also assay/organism dependent tendencies: phenols were more toxic than anilines in the V. fischeri assay but not in the algal test. The comparison of the experimental toxicity data to the data available from the literature as well as to QSAR predictions showed that toxicity of phenols to algae can be modeled based on hydrophobicity, whereas the toxicity of anilines to algae as well as toxicity of both anilines and phenols to V. fischeri depended on other characteristics in addition to logK_ow.     

Quantitative structure-toxicity relationship study of lethal concentration to tadpole (Bufo vulgaris formosus) for organophosphorous pesticides

In the present study more than 1,000 structural parameters of 41 organophosphorus pesticides (OPs) were calculated using the software ChemOffice 8.03 and Dragon 2.1. Then, with multivariate linear regression and best subset regression analyses, different equations were derived to calculate the lethal toxicity, LC(50), for these 41 organophosphorous pesticides found in tadpoles (Bufo vulgaris formosus). An equation was developed for all selected OPs, especially those with relatively low toxicity levels (LC(50)>4.5mM) that accounted for 89.09% of the variability in the toxic effect. The equation indicated that the main contributions to OPs toxicity with tadpoles were the electrostatic contribution qH(+) (maximum net positive H atomic charge), spatial autocorrelation (MATS7 m) and hydrophobicity (lgK(ow)), with the two former being the most important parameters. For OPs with high toxicity, however, different structural parameters were introduced. The following equation was developed with LC(50)<4.5mM. These equations implied that with different levels of toxicity there could have different mechanisms in the tadpole. Furthermore, the results showed that molecular structural parameters had a particular value in modeling chemical reactivity within a homologous series of compounds.     

A Protocol to Select High Quality Datasets of Ecotoxicity Values for Pesticides

Abstract

The key to any QSAR model is the underlying dataset. In order to construct a reliable dataset to develop a QSAR model for pesticide toxicity, we have derived a protocol to critically evaluate the quality of the underlying data. In developing an appropriate protocol that would enable data to be selected in constructing a QSAR, we concentrated on one toxicity end point, the 96 h LC50 from the acute rainbow trout study. This end point is key in pesticide regulation carried out under 91/414/EEC. The dataset used for this exercise was from the US EPA-OPP database.     

Quantitative structure-activity relationships of nitroaromatics toxicity to the algae (Scenedesmus obliguus)

The DFT-B3LYP method, with the basis set 6-311G( * *), was employed to calculate the molecular geometries and electronic structures of 25 nitroaromatics. The acute toxicity (-lgEC(50)) of these compounds to the algae (Scenedesmus obliguus) along with hydrophobicity described by logK(OW), and two quantum chemical parameters-energy of the lowest unoccupied molecular orbital, E(LUMO), and the charge of the nitro group, [ForQ(NO2), were used to establish the quantitative structure-activity relationships (QSARs). For 18 mononitro derivatives, the hydrophobicity parameter logK(OW) could interpret the toxic mechanism successfully. Dinitro aromatic compounds were susceptible to be reduced to aniline for their electrophilic nature. Their toxicity was controlled mainly by electronic factors instead of hydrophobicity. The electronic parameters, E(LUMO) and Q(NO2), were used to yield the following model: -lg EC(50) = 3.746 - 25.053 E(LUMO) + 6.481 Q(NO2) (n=22, R=0.926, SE=0.206, F=56.854, P<0.001). The predicted toxic values using the above equation are in good agreement with the experimental values.     

Ecotoxicity prediction using mechanism- and non-mechanism-based QSARs: a preliminary study

In ecotoxicology, mechanism-based quantitative structure-activity relationships (QSARs) are usually developed with higher quality than QSARs without regard to toxicity mechanism. Correctly determining the mechanism of a compound, which is not always easy, is required to use mechanism-based QSARs for toxicity prediction. The mechanism determination step may introduce extra errors in addition to the intrinsic prediction errors of mechanism-based QSARs, thus compromising these QSARs' performance compared with QSARs regardless of mechanism. In this study, the mechanism identification-toxicity prediction (MI-TP) approach was compared with the direct toxicity prediction (DTP) approach using a data set containing phenol toxicity to Tetrahymena pyriformis. A statistical mechanism classification model for mechanism prediction, four mechanism-based QSARs and a single QSAR without discriminating between mechanisms were developed for toxicity prediction. Toxicity of phenols in an external data set was predicted following the MI-TP and DTP approaches. Results indicated that the mechanisms of several phenols in the external test set were incorrectly predicted which led to significant over- or under-estimation of their toxicity. Overall, the MI-TP approach did not yield more accurate toxicity prediction than the DTP approach.     

QSAR study on the toxicity of substituted benzenes to the algae (Scenedesmus obliquus).

50% effective inhibition concentration 48h-EC50 of 40 substituted benzenes to the algae (Scenedesmus obliquus) was determined. The energy of the lowest unoccupied molecular orbital (E(LUMO)) was calculated by the quantum chemical method MOPAC6.0-AM1. By using E(LUMO) and the hydrophobicity parameter log K(OW) the quantitative structure-activity relationship model (QSAR) was developed: log1/EC50=0.272 logK(OW) - 0.659E(LUMO) + 2.54, R2 = 0.793, S.E. = 0.316, F = 71.07, n = 40. A series of equations were obtained about the measured EC50 values of different subclasses of compounds. For those compounds containing double -NO2, their toxicity may be related chiefly to the intracellular reduction of -NO2 obtaining electron, while for anilines and phenols, K(OW) contributes most to the QSAR and E(LUMO) very little.     

3D QSAR studies of dioxins and dioxin-like compounds using CoMFA and CoMSIA

In the present study we have performed comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) on structurally diverse ligands of Ah (dioxin) receptor to explore the physico-chemical requirements for binding. All CoMFA and CoMSIA models have given q(2) value of more than 0.5 and r(2) value of more than 0.84. The predictive ability of the models was validated by an external test set, which gave satisfactory predictive r(2) values. Best predictions were obtained with CoMFA model of combined modified training set (q(2) = 0.631, r(2) = 0.900), giving predictive residual value = 0.02 log unit for the test compound. Addition of CoMSIA study has elucidated the role of hydrophobicity and hydrogen bonding along with the effect of steric and electrostatic properties revealed by CoMFA. We have suggested a model comprises of four structurally different compounds, which offers a good predictability for various ligands. Our QSAR model is consistent with all previously established QSAR models with less structurally diverse ligands.