Ecotoxicological Characterisation and Classification of Existing Chemicals

GOAL, SCOPE AND BACKGROUND: In 1998, the International Council of Chemical Associations (ICCA) launched a global initiative to investigate more than 1,000 HPV chemicals (High Production Volume, > or = 1,000 t/a) within the refocused OECD HPV Chemicals Programme. Up to the OECD SIDS Initial Assessment Meeting in April 2004 (SIAM 18) 147 ICCA dossiers (ca. 230 CAS-No) have been assessed based on a harmonised data set. The environmental profile and an ecotoxicological characterisation of these chemicals are presented here. Data for acute aquatic toxicity were correlated among each other, as well as data for fish (LC50, LD50) and rodents (LD50). The data for acute aquatic toxicity are compared with other existing chemicals. METHODS: Data of the ICCA HPV chemicals from the OECD SIAM 11-18 are presented for: log Kow (as an indicator for bioaccumulation potential), biodegradation, acute aquatic toxicity and availability of long-term toxicity data. Correlation analysis was performed with log transformed data and a linear regression model was fitted to the data, if a significant correlation was found. Acute toxicity for fish and acute oral toxicity for rodents were correlated on a molar basis. Acute aquatic toxicity of the chemicals is compared with data from BUA reports 1-234 and a random EINECS sample (Knacker et al. 1995). RESULTS AND DISCUSSION: According to the dossier information, 71 of the 147 ICCA chemicals are not 'readily biodegradable', 21 have a log Kow > or = 3, and 44 are 'toxic' (LC/EC50 < or = 10 mg/L) or 'very toxic' (LC/EC50 < or = 1 mg/L) to aquatic organisms. For 77, only the base set (acute fish, Daphnia and algae) is available, for the rest at least one long-term test (fish or Daphnia) is available and three tests for a mere 14 others. Based on the data presented, the SIAM gives recommendations for Environment and Human Health. 22 chemicals have been identified as a 'candidate for further work' for Environment and 16 for Human Health. The highest correlation coefficient was obtained correlating fish and Daphnia (r2 = 0.79). LC50 (fish) is significantly correlated with LD50 (rodent), but data are widely scattered. The correlation is not improved after transforming LC50 (fish) to LD50 (fish), using BCF QSAR. Based on acute aquatic toxicity, 25.1% of the chemicals from the BUA reports 1-234 are classified as 'very toxic' (LC/EC50 < or = 1 mg/L). This proportion is 2.5-fold higher than the ICCA HPV chemicals and 1.4-fold higher than the random EINECS sample. CONCLUSIONS: Correlation coefficients for aquatic toxicity data are rather uniform (0.57-0.79) compared with literature data, but also the best correlation was observed between fish and Daphnia. Because the scatter around the regression lines is still considerable, simple predictions of ecotoxicity between species are not possible. Correlation of LC50 (fish) and LD50 (rodent) indicates that toxicity is different. Surprisingly, the correlation of fish and rodent toxicity is not improved by transforming LC50 values to internal LD50s. The selection of ICCA chemicals by market significance (production volume) leads to a classification of toxicity, which is more comparable to a random sample of EINECS chemicals than to German BUA chemicals. The latter were chosen for concern (for Environment or Human Health). RECOMMENDATIONS AND OUTLOOK: Of 147 dossiers assessed between SIAM 11-18, ca. 75% were sponsored by the three following countries: Germany (42), USA (37) and Japan (33). The current output is about 50 dossiers per year (70-100 CAS-No), but a trend for an increase of output is noticeable. Industry, national authorities, and OECD work on a further development to speed up the output. The number of chemicals with 'low priority for further work' and the work recommended for the 'candidates' (mainly exposure assessment) indicate that the data presented were adequate for an initial hazard assessment according to OECD requirements. From the ICCA HPV list (n = 880, state of 1999) 44% of the chemicals have data available to cover all SIDS endpoints for Environment and only 33% for Human Health (Allanou et al. 1999). This indicates the importance of the Initiative to provide information on existing chemicals. The authors agree with the expectation "...that the scientific information provided by this global initiative will be considered as an internationally accepted and harmonised basis for further steps of chemicals management." (ICCA 2002 b).     

QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes

The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R ²) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

     

ECOSAR model performance with a large test set of industrial chemicals

The widely used ECOSAR computer programme for QSAR prediction of chemical toxicity towards aquatic organisms was evaluated by using large data sets of industrial chemicals with varying molecular structures. Experimentally derived toxicity data covering acute effects on fish, Daphnia and green algae growth inhibition of in total more than 1,000 randomly selected substances were compared to the prediction results of the ECOSAR programme in order (1) to assess the capability of ECOSAR to correctly classify the chemicals into defined classes of aquatic toxicity according to rules of EU regulation and (2) to determine the number of correct predictions within tolerance factors from 2 to 1,000. Regarding ecotoxicity classification, 65% (fish), 52% (Daphnia) and 49% (algae) of the substances were correctly predicted into the classes "not harmful", "harmful", "toxic" and "very toxic". At all trophic levels about 20% of the chemicals were underestimated in their toxicity. The class of "not harmful" substances (experimental LC/EC(50)>100 mg l(-1)) represents nearly half of the whole data set. The percentages for correct predictions of toxic effects on fish, Daphnia and algae growth inhibition were 69%, 64% and 60%, respectively, when a tolerance factor of 10 was allowed. Focussing on those experimental results which were verified by analytically measured concentrations, the predictability for Daphnia and algae toxicity was improved by approximately three percentage points, whereas for fish no improvement was determined. The calculated correlation coefficients demonstrated poor correlation when the complete data set was taken, but showed good results for some of the ECOSAR chemical classes. The results are discussed in the context of literature data on the performance of ECOSAR and other QSAR models.     

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.     

Computer-based QSARs for predicting mixture toxicity of benzene and its derivatives

During the past decades, the Quantitative structure-activity relationships (QSARs) have been proven to be reliable tools when little or no empirical data are available in medicinal chemistry, biochemistry, toxicology, and environmental sciences. However, only few studies that quantitatively predict mixtures toxicity have been reported. In this study, the QASR models for the binary mixtures toxicity of 12 benzene and its derivatives, including eight non-polar-narcotic compounds and four polar narcotic compounds were developed, without reference to exact toxicity mechanisms of single compounds. All parameters for the QSAR studies were defined on the basis of quantum mechanical calculations and these parameters were selected by the stepwise procedure. The results of this study provided a simple means of predicting the binary mixtures toxicity from the chemical structure.     

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.     

Statistical evaluation of chronic toxicity data on aquatic organisms for the hazard identification: the chemicals toxicity distribution approach

Presently, in the Globally Harmonised System of Classification and Labelling of Chemicals the classification of substances for long-term effects to aquatic life is based on acute toxicity in combination with degradation and/or bioaccumulation potential. Recently an OECD Working Group was created to develop the classification scheme to accommodate chronic toxicity data related to aquatic organisms for assigning a chronic hazard category. This study focuses on a new approach for setting chronic toxicity cut-off values based on Chemicals Toxicity Distributions (CTDs). A CTD is obtained through statistical fitting of the data used by regulatory bodies for setting hazard-based classifications. The CTDs were made using the lowest aquatic NOEC value of each chemical. A review of different toxicological sources reporting acute aquatic toxicities was carried out. Initially, the data were arranged according to the specific source and distributions for key taxonomic groups (i.e. fishes, crustaceans and algae) were evaluated separately. In most cases, no significant departures from normality were observed. Thereafter, a compiled database containing >900 values was developed and the CTDs were constructed for each taxonomic group. Significant deviation from normality (P < 0.05) was observed in the fishes and crustaceans' CTDs. However, this deviation was apparently produced by the presence of only seven values with NOECs <1 x 10(-5) mg l(-1), while high correlation between the data and the normal scores (r-values>or= 0.989) indicated that the data were samples from normal distributions. From these observations, potential cut-off values would allow quantitative estimations of the percentage of chemicals falling into each specific category. This approach results in a simple classification hazard scheme where most chemicals are covered in one of the categories, allowing a clear distribution of the chemicals among three categories for chronic toxicity.     

Reliable QSAR for estimating Koc for persistent organic pollutants: correlation with molecular connectivity indices

Several recent studies have shown that n-octanol/water partition coefficients may not be a good predictor for estimating soil sorption coefficients of persistent organic pollutants (POPs), defined here as chemicals with log Kow greater than 5. Thus, an alternative QSAR model was developed that seems to provide reliable estimates for the soil sorption coefficients of persistent organic pollutants. This model is based on a set of calculated molecular connectivity indices and evaluated soil sorption data for 18 POPs. The chemical's size and shape, quantified by 1chi, 3chiC and 4chiC(v) indices, have a dominant effect on the soil sorption process of POPs. The developed QSAR model was rationalized in terms of potential hydrophobic interactions between persistent organic pollutants and soil organic matrix. Its high predictive power has been verified by an extensive internal and external validation procedure.     

QSAR models for estimating properties of persistent organic pollutants required in evaluation of their environmental fate and risk

The molecular connectivity indices (MCIs) have been successfully used for over 20 years in quantitative structure activity relationships (QSAR) modelling in various areas of physics, chemistry, biology, drug design, and environmental sciences. With this review, we hope to assist present and future QSAR practitioners to apply MCIs more wisely and more critically. First, we have described the methods of calculation and systematics of MCIs. This section should be helpful in rational selection of MCIs for QSAR modelling. Then we have presented our long-term experience in the application of MCIs through several characteristic and successful QSAR models for estimating partitioning and chromatographic properties of persistent organic pollutants (POPs). We have also analysed the trends in calculated MCIs and discussed their physical interpretation. In conclusion, several practical recommendations and warnings, based on our research experience, have been given for the application of MCIs in the QSAR modelling.     

Selection of non-dioxin-like PCBs for in vitro testing on the basis of environmental abundance and molecular structure

The non-dioxin-like polychlorinated biphenyls (NDL-PCBs) constitute the major proportion of PCBs found in food and human tissues. It is important to improve our understanding of the toxicity, environmental and human risks associated with the NDL-PCBs, since their toxicology is incompletely characterized and a human health risk assessment is required. This paper discusses the selection of a training set of 20 tri- to hepta-chlorinated biphenyls, PCBs 19,28,47,51,52,53,74,95,100,101,104,118,122,128,136,138,153,170,180, and 190. Suggested for comprehensive screening using in vitro assays to identify critical mechanisms of toxicological action. The selected PCBs form a balanced basis for developing of quantitative structure-activity relationship (QSAR) models for prediction of physicochemical and toxicological properties of non-tested PCB congeners. Chemical and physical properties, environmental abundance and toxicological activities of the congeners were considered during the selection process. A complementary set of PCBs, a reference set, was selected using D-optimal onion design including PCBs 18,20,28,30,37,40,50,54,60,77,82,99,122,132,153,161,170,188,192, and 193. Congeners of this set are well suited for validation of QSAR models developed using the training set. For visualization of the chemical diversity of environmentally abundant PCBs and congeners of the training and reference sets, principal component analysis (PCA) was used. Statistical molecular design was used to verify the structural representation. As a reference structure for dioxin-like PCBs, PCB 126 was added in the training set. The selected set of NDL-PCBs is proposed for use in toxicological testing programs to provide rational basis for risk assessment of the NDL-PCBs.     

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.     

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.     

The health effects and ecological significance of chlorine residuals in water

During the past several years, chlorine residuals and chlorinated organic compounds in drinking waters and aquatic environments have become a significant topic of study for scientists concerned about the quality of life in aquatic ecosystems as well as general public health. The effects of direct toxicity and/or carcinogenicity to human and aquatic life are the focal points for this concern.The effects of chloramines and chlorinated organic compounds present in the water distribution system after chlorination treatments are reviewed. Also discussed are the effects of chlorinated discharges from municipal secondary treatment plants and power plants on human health and aquatic life. The toxic significance of environmental chemicals are described.