Time-dependence in mixture toxicity prediction.

The value of time-dependent toxicity (TDT) data in predicting mixture toxicity was examined. Single chemical (A and B) and mixture (A+B) toxicity tests using Microtox(®) were conducted with inhibition of bioluminescence (Vibrio fischeri) being quantified after 15, 30 and 45-min of exposure. Single chemical and mixture tests for 25 sham (A1:A2) and 125 true (A:B) combinations had a minimum of seven duplicated concentrations with a duplicated control treatment for each test. Concentration/response (x/y) data were fitted to sigmoid curves using the five-parameter logistic minus one parameter (5PL-1P) function, from which slope, EC25, EC50, EC75, asymmetry, maximum effect, and r(2) values were obtained for each chemical and mixture at each exposure duration. Toxicity data were used to calculate percentage-based TDT values for each individual chemical and mixture of each combination. Predicted TDT values for each mixture were calculated by averaging the TDT values of the individual components and regressed against the observed TDT values obtained in testing, resulting in strong correlations for both sham (r(2)=0.989, n=25) and true mixtures (r(2)=0.944, n=125). Additionally, regression analyses confirmed that observed mixture TDT values calculated for the 50% effect level were somewhat better correlated with predicted mixture TDT values than at the 25 and 75% effect levels. Single chemical and mixture TDT values were classified into five levels in order to discern trends. The results suggested that the ability to predict mixture TDT by averaging the TDT of the single agents was modestly reduced when one agent of the combination had a positive TDT value and the other had a minimal or negative TDT value.

Experimental reactivity parameters for toxicity modeling: application to the acute aquatic toxicity of SN2 electrophiles to Tetrahymena pyriformis.

A diverse set of 60 haloaliphatic compounds were evaluated for reactivity with cysteine thiol groups in the previously described RC(50) assay using glutathione (GSH) as a model nucleophile. Reactivity was quantified by the RC(50) value, the concentration of test compound that produced 50% reaction of the GSH thiol groups in 120 min. Under standard conditions, RC(50) values are mathematically proportional to reciprocal rate constants. Quantitative structure-activity relationship (QSAR) analysis correlating acute aquatic toxicity (IGC(50)) to Tetrahymena pyriformis with RC(50) values was carried out. It was found that subdivision of the compounds into subdomains according to their reaction mechanism characteristics enabled toxicity-reactivity relationships to be identified. The largest subdomain consisting of 22 compounds in which a primary halogen is alpha to a carbonyl or other electronegative unsaturated group and which can be confidently assigned as S(N)2 electrophiles fits the equation pIGC(50) (mM) = 0.94 (+/-0.07) pRC(50) (mM) + 1.34 (+/-0.07), n = 22, r(2) = 0.889, r(2)(adj) = 0.884, s = 0.27, and F = 161. Compounds in which the halogen is not alpha to an unsaturated group are not reactive in the GSH assay and do not exhibit reactive toxicity to T. pyriformis. Compounds tested in which the halogen is alpha to an unsaturated nonelectronegative group were found to be less toxic in the assay than predicted by the above QSAR equation. Within a subdomain of 21 compounds having a halogen alpha to an electronegative unsaturated group that, in the absence of experimental evidence, could not be confidently assigned as S(N)2 electrophiles, 2-bromoalkanoates of general structure R(1)CHBrCO(2)R(2), 2-bromopropionamide, and 2-haloalkanoic acids of general formula R(1)CHXCO(2)H (nine compounds in total) are all well-predicted by the above equation. Of the other 12 compounds of this subdomain, eight are substantially less toxic than predicted by the above equation and are considered to react differently, whereas the alpha-halonitriles (four compounds) are more toxic than predicted and fit a correlation of their own: pIGC(50) = 1.01 (+/-0.05) pRC(50) + 2.04 (+/-0.05), n = 4, r(2) = 0.995, r(2)(adj) = 0.992, s = 0.08, and F = 381, with a similar slope but larger intercept. An explanation in terms of their physical chemistry and possible involvement of released cyanide ion is suggested.

Verification of the structural alerts for Michael acceptors.

A diverse series of polarized alpha,beta-unsaturated and related compounds were evaluated for reactivity with a spectrophotometric assay using the sulfhydryl group in the form of the cysteine residue of the tripeptide GSH as a model nucleophile. The reactive end point (RC 50) calculations were compared to previously described structural alerts based on conventional organic chemistry. This comparison focused on polarized alpha,beta-unsaturates, including ones containing an aldehyde, ketone, ester, sulfoxide, sulfone, sulfonate, nitro, or cyano moiety as well as ortho- and para-pyridino compounds and ortho- and para-quinones. The alerts were coded by substructure and are available in open-source software ( http://sourceforge.net/projects/chemeval). Comparisons of reactivity between selected analogues revealed that only the polarized alpha,beta-unsaturates were reactive. These results verified the coded structural alerts that define the applicability domain for Michael acceptor electrophiles.

Saccharomyces cerevisiae BLYAS, a new bioluminescent bioreporter for detection of androgenic compounds.

A Saccharomyces cerevisiae strain, capable of autonomous bioluminescence, was engineered to respond to androgenic chemicals. The strain, S. cerevisiae BLYAS, contains the human androgen receptor in the chromosome and was constructed by inserting a series of androgen response elements between divergent yeast promoters GPD and ADH1 on pUTK401 that constitutively expressed luxA and luxB to create pUTK420. Cotransformation of this plasmid with a second plasmid (pUTK404), containing the genes required for aldehyde synthesis (luxCDE) and FMN reduction (frp), yielded a bioluminescent bioreporter responsive to androgenic chemicals. Using dihydrotestosterone (DHT) as a standard, the response time and the 50% effective concentration values were 3 to 4 h and (9.7 +/- 4.6) x 10(-9) M, respectively. The lower limit of detection in response to DHT was 2.5 x 10(-9) M, and in response to testosterone it was 2.5 x 10(-10) M. This strain is suitable for high-throughput screening of chemicals with potential for remote environmental monitoring systems because of the assay speed, sensitivity, and self-containment.

Comparative quantitative structure-activity-activity relationships for toxicity to Tetrahymena pyriformis and Pimephales promelas.

An approach for predicting acute aquatic toxicity, in the form of a quantitative structure-activity-activity relationship (QSAAR), is described. This study assessed relative toxic effects to a fish, Pimephales promelas, and a ciliate, Tetrahymena pyriformis, and attempted to form relationships between them. A good agreement between toxic potencies (R2 = 0.754) was found for a chemically diverse dataset of 364 compounds, when using toxicity to the ciliate as a surrogate to that for fish. This relationship was extended by adding three theoretical structural descriptors of the molecules. The inclusion of these descriptors improved the relationship further (R2 = 0.824). The structural features that were found to improve the extrapolation between the toxicity to the two different species were related to the electron distribution of the carbon skeleton of the toxicant, its hydrogen-bonding ability, and its relative nitrogen content. Such a QSAAR approach provides a potential tool for predicting the toxicities of chemicals for environmental risk assessment and thus for reducing animal tests.

Abiotic sulfhydryl reactivity: a predictor of aquatic toxicity for carbonyl-containing alpha,beta-unsaturated compounds.

A diverse series of aliphatic alpha,beta-unsaturated esters, ketones, and aldehydes were evaluated for reactivity with the model nucleophile sulfhydryl group in the form of the cysteine residue of the tripeptide glutathione; the reactive end point (RC50) was then related to aquatic toxicity (IGC50) assessed in the Tetrahymena pyriformis population growth impairment assay. The substructure specific to all tested reactive substances, an olefin conjugated to a carbonyl group, is inherently electrophilic and conveys the potential to act by way of Michael-type nucleophilic addition. All such unsaturated compounds are inherently acutely toxic. However, their toxicity is difficult to model with conventional descriptors since toxicity is independent of both hydrophobicity and molecular orbital electrophilicity but dependent on the specific molecular structure. While methacrylates typically did not attain an RC50 value at saturation, a linear relationship [log (IGC50(-1)) = 0.936[log (RC50(-1))] + 0.508, where n = 41, r2 = 0.846, q2 = 0.832, s = 0.35, F = 214, and Pr > F = 0.0001] was observed between aquatic toxicity and reactivity for the other carbonyl-containing alpha,beta-unsaturated chemicals.

Aquatic toxicity and abiotic thiol reactivity of aliphatic isothiocyanates: Effects of alkyl-size and -shape.

Aquatic toxicity data in the TETRATOX assay and reactivity data in an abiotic thiol assay were collected for a series of aliphatic isothiocyanates. These compounds can act as Michael-type acceptors with N-hydro-C-mercapto-addition to cellular thiols as a molecular mechanism of action. Comparison of both toxicity and reactivity among the analogues revealed that derivatives with a branch hydrocarbon moiety, especially branched in the ß-position were less toxic and less reactive. In contrast, the di-isothiocyanate and the allyl and propargyl derivatives are more toxic than their 1-alkyl homologues. The toxicity and reactivity differences are consistent but except for the tert-butyl-derivative not remarkable. The differences are due to variations in steric hindrance at the reaction center. For the mono-isothiocyanates compounds toxicity (IGC(50)) is linearly related to thiol reactivity (EC(50)): log(1/IGC(50))=1.33(log(1/EC(50)))-0.41; n=23, s=0.24, r(2)=0.911, q(2)=0.907, F=215.

Chemical mixture toxicity testing with Vibrio fischeri: combined effects of binary mixtures for ten soft electrophiles.

The toxicity of 30 binary combinations of 10 soft electrophiles was examined in Microtox using dose-response curve (DRC) analysis. Chemicals from three groups of soft electrophiles-vinyl Michael acceptors (I--react with a thiol group), dicarbonyl reactive agents (II--react with a primary amine), and alpha-haloactivation compounds (III--react with a thiol group)--were selected for testing to evaluate the relationship between molecular site of chemical action and combined toxic effect. For each combination tested, each single agent was tested alone at six duplicated concentrations and three 1:1 mixtures of the agents were also tested, each at six duplicated concentrations. Exposure duration was 15 min for each single agent and mixture test. Sigmoid DRCs for each single chemical and mixture were constructed and the single chemical curves were used to develop a theoretical dose-addition DRC for the combination. Additivity quotient (AQ) values for slope and EC50 were calculated by dividing the actual mixture slope or EC50 for a given combination by the predicted slope or EC50, respectively, from the theoretical dose-addition DRC. Three criteria were selected for value in determining the combined effect obtained for each combination: (1) slope AQ 95% confidence interval (CI) overlap with 1.0 (1.0=dose addition), (2) EC50 AQ 95% CI overlap with 1.0, and (3) mean mixture data point 95% and 99% CI overlap with the theoretical dose-addition DRC. Each of three sham combinations showed combined effects consistent with dose addition for each criterion. Dose addition was expected for 15 nonsham combinations (nine within-group combinations and six group I:III combinations) and a nondose-additive effect was expected for 12 combinations (all I:II and II:III combinations). Actual combined effects obtained by incorporating all three criteria (noted above) showed only six instances of dose addition. Therefore, time-dependent toxicity (TDT) tests of each soft electrophile alone and for three nonpolar narcotic chemicals alone were conducted, using 15-, 30-, and 45-min exposure durations, to assess the time-dependent nature of the toxicity. Results of the TDT tests suggested that five had fully (or nearly fully) TDT (interpreted as an irreversible effect representing one molecular site of action), five of the soft electrophiles had partially TDT (i.e., representing two or more molecular sites of action for the agents, one irreversible and one reversible), and the three nonpolar narcotics had no TDT (i.e., a fully reversible toxic effect). With this TDT information, the combined effects for 25 of the 27 mixtures, although rather complex, could be explained. It is noteworthy that all combined effects obtained, whether concluded to be dose-additive or not, were close to dose-additive for hazard assessment purposes.

Use of Saccharomyces cerevisiae BLYES expressing bacterial bioluminescence for rapid, sensitive detection of estrogenic compounds.

An estrogen-inducible bacterial lux-based bioluminescent reporter was developed in Saccharomyces cerevisiae for applications in chemical sensing and environmental assessment of estrogen disruptor activity. The strain, designated S. cerevisiae BLYES, was constructed by inserting tandem estrogen response elements between divergent yeast promoters GPD and ADH1 on pUTK401 (formerly pUA12B7) that constitutively express luxA and luxB to create pUTK407. Cotransformation of this plasmid with a second plasmid (pUTK404) containing the genes required for aldehyde synthesis (luxCDE) and FMN reduction (frp) yielded a bioluminescent bioreporter responsive to estrogen-disrupting compounds. For validation purposes, results with strain BLYES were compared to the colorimetric-based estrogenic assay that uses the yeast lacZ reporter strain (YES). Strains BLYES and YES were exposed to 17beta-estradiol over the concentration range of 1.2 x 10(-8) through 5.6 x 10(-12) M. Calculated 50% effective concentration values from the colorimetric and bioluminescence assays (n = 7) were similar at (4.4 +/- 1.1) x 10(-10) and (2.4 +/- 1.0) x 10(-10) M, respectively. The lower and upper limits of detection for each assay were also similar and were approximately 4.5 x 10(-11) to 2.8 x 10(-9) M. Bioluminescence was observed in as little as 1 h and reached its maximum in 6 h. In comparison, the YES assay required a minimum of 3 days for results. Strain BLYES fills the niche for rapid, high-throughput screening of estrogenic compounds and has the ability to be used for remote, near-real-time monitoring of estrogen-disrupting chemicals in the environment.

QSARs for the aquatic toxicity of aromatic aldehydes from Tetrahymena data.

The aim of the study was to develop quantitative structure-activity relationships (QSARs) for a large group of 77 aromatic aldehydes tested for acute toxicity to the ciliate Tetrahymena pyriformis using mechanistically interpretable descriptors. The resulting QSARs revealed that the 1-octanol/water partition coefficient (log K(ow)), is the most important descriptor of aldehyde aquatic toxic potency. The model with log K(ow) was improved by adding electronic descriptor (the maximum acceptor superdelocalizability in a molecule--A(max)) based on calculations with the semi-empirical AM1 model. The two descriptors reflect the two main processes responsible for demonstration of acute aquatic toxicity, namely penetration through cell membranes (log K(ow)) and interaction with the biomacromolecules (A(max)) into the cells. Results showed that generally the studied group of aldehydes could be modeled by this simple two-descriptor approach. However, the group of 2- and/or 4-hydroxylated aldehydes demonstrates enhanced toxicity compared to the other aldehydes. Transformation to quinone-like structures is proposed as the explanation for this enhanced potency. The 2- and/or 4-hydroxylated aldehydes are modeled successfully by [log(1/IGC50) = 0.540(0.038) log K(ow) + 8.30(2.88)A(max) - 3.11(0.92), n = 25, R2 = 0.916, R(CV)2 = 0.896, s = 0.141, F = 120], while the other aldehydes are modeled by the relationship [log(1/IGC50) = 0.583 (0.034)log K(ow) + 9.80(2.62)A(max) - 4.04 (0.85), n = 52, R2 = 0.864, R(CV)2 = 0.844, s = 0.203, F = 156], which is similar to the general benzene model.

Chemistry-toxicity relationships for the effects of di- and trihydroxybenzenes to Tetrahymena pyriformis.

This paper presents a mechanistic analysis of aquatic toxicity data, quantified as pIGC(50) assessed in the 40 h Tetrahymena pyriformis population growth impairment assay, for 40 polyhydroxybenzene derivatives. The toxicity trends of these phenolic compounds have been shown to be consistent with mechanistic organic chemistry principles. Thus, it is shown that the compounds can be grouped into two chemical mechanism of action domains, according to whether they can be oxidized to electrophilic quinones or quinone methides. Compounds in which the hydroxy groups are oriented meta, but not ortho or para, to one another cannot be oxidized to electrophilic quinones or quinone methides and act as polar narcotics. Their toxicities are found to be well-correlated with hydrophobicity (modeled by log D): pIGC(50) = 0.83 (+/-0.04) log D - 1.27 (+/-0.09): n = 10, r(2) (adj) = 0.981, q(2) = 0.974, s = 0.15, and F = 460. Compounds with hydroxy groups oriented ortho or para to one another are more toxic than predicted by this equation, and the toxicity trends within this group of compounds are rationalized in terms of the electrophilic chemistry of their oxidation products. A quantitative correlation is demonstrated between toxicity and electrophilicity of the oxidation products, as modeled by the activation energy index (AEI), a new molecular orbital parameter derived from the computed highest occupied molecular orbital (HOMO) and HOMO-1 orbital energies of the electrophiles and the intermediates for Michael addition of n-butylamine: pIGC(50) (adj) = -0.49 (+/-0.06) AEI + 6.85 (+/-0.69): n = 18, r(2) (adj) = 0.810, q(2) = 0.774, s = 0.24, and F = 73. Outliers to these quantitative structure-activity relationships (QSARs) are easily rationalized in terms of their chemistry (tetrabromocatechol, 4,6-dinitro-1,2,3-trihydroxybenzene, and 2,3,4-trihydroxybenzophenone) or in a demonstrable deficiency in the descriptor (the methyl-substituted hydroquinones, for which the AEI parameter as defined here fails to model the electron donation effects of the methyl groups). The AEI parameter is a mechanism-based molecular orbital parameter new to QSAR and, on the basis of the present findings, it shows promise for further applications. However, some deficiencies have been identified with it, particularly with regard to modeling the electronic effects of methyl (and presumably other alkyl) groups, and there is scope to refine the concept so as to deal with these deficiencies.

Structure-toxicity relationships for the effects to Tetrahymena pyriformis of aliphatic, carbonyl-containing, alpha,beta-unsaturated chemicals.

Toxicity data for 82 aliphatic chemicals with an alpha,beta-unsaturated substructure were compiled. Toxicity was assessed in the 2-day Tetrahymena pyriformis population growth impairment assay. Toxic potency [log(IGC50(-1))] for most of these chemicals was in excess of baseline narcosis as quantified by the 1-octanol/water partition coefficient (log K(ow)). The toxicity of the alpha,beta-unsaturated aldehydes was modeled well by log K(ow) in conjunction with the sum of partial charges on the vinylene carbon atoms (Q(C4) + Q(C3)) and the energy of the lowest unoccupied molecular orbital (E(lumo)). These electronic descriptors were also successful at modeling the toxicity of alpha,beta-unsaturated ketones. The toxicity of a range of acrylates was constant within about 0.2 of a log unit. Conversely, the toxicity of methacrylates and esters containing the vinylene group varied considerably and was explained by their hydrophobicity. The comparison of the quantitative structure-activity relationship (QSAR) for the methacrylates and esters with that for non-polar narcosis showed little significant difference and hence suggested that substitution on the carbon-carbon double bond in the methacrylates and vinylene unsaturated esters does not enhance toxicity over that of baseline. Substitution on the carbon-carbon double bond in the alpha,beta-unsaturated aldehydes resulted in toxicity that was similar to that for saturated derivatives. Although an excellent hydrophobicity-dependent QSAR was developed for the esters containing ethynylene group, these compounds are considered to act as Michael-type acceptors. Attempts to combine different groups of Michael-type acceptors into a single QSAR, based on mechanistically derived descriptors, were unsuccessful. Thus, the modeling of the toxicity of the alpha,beta-unsaturated carbonyl domain is currently limited to models for narrow subdomains.

Interspecies quantitative structure-activity relationship model for aldehydes: aquatic toxicity.

The present study proposes a generic interspecies quantitative structure-activity relationship (QSAR) model that can be used to predict the acute toxicity of aldehydes to most species of aquatic organisms. The model is based on the flow-through fathead minnow (Pimephales promelas) 50% lethal concentration (LC50) data combined with other selected fish acute toxicity data and on the static ciliate (Tetrahymena pyriformis) 50% inhibitory growth concentration (IGC50) data. The toxicity of Schiff-base acting aldehydes was defined using hydrophobicity, as the calculated log 1-octanol/water partition coefficient (log Kow), and reactivity, as the donor delocalizability for the aldehyde O-site (D(O-atom)). The fish model [log 1/LC50 = -2.503(+/-1.950) + 0.480(+/-0.052) log Kow + 18.983(+/-6.573) D(O-atom), n = 62, r2 = 0.619, s2 = 0.241, F = 48.0, Q2 = 0.587] compares favorably with the ciliate model [log 1/IGC50 = -0.985(+/-1.309) + 0.530(+/-0.044) log Kow + 11.369(+/-4.350) D(O-atom), n = 81, r2 = 0.651, s2 = 0.147, F = 72.9, Q2 = 0.626]. The fish and ciliate surfaces appear to be parallel, because they deviate significantly only by their intercepts. These observations lead to the development of a global QSAR for aldehyde aquatic toxicity [log E(-1) = bE(Organism) + 0.505(+/-0.033) log Kow + 14.315(+/-3.731) D(O-atom), n = 143, r2 = 0.698, s2 = 0.187, S2(Fish) = 0.244, S2(Ciliate) = 0.149, F = 98, Q2 = 0.681]. The general character of the model was validated using acute toxicity data for other aquatic species. The aldehydes global interspecies QSAR model could be used to predict the acute aquatic toxicity of untested aldehydes and to extrapolate the toxicity of aldehydes to other aquatic species.

Population growth impairment of aliphatic alcohols to Tetrahymena.

The toxicity of a series of 120 aliphatic alcohols was evaluated using the Tetrahymena pyriformis population growth impairment assay. For tertiary propargylic alcohols; primary, secondary, and tertiary homopropargylic alcohols; allylic alcohols; and saturated alcohols, a statistically robust structure-activity model was developed for toxicity data [log (IGC(50) (-1))] using the 1-octanol/water partition coefficient (log K(ow)) as the lone descriptor [log (IGC(50))(-1) = 0.74 (log K(ow)) - 1.73; n = 97; r(2) (adj.) = 0.933; r(2) (pred.) = 0.932; s = 0.298; F = 1328; Pr > F = 0.0001]. Analysis of data for the primary propargylic alcohols yielded a separate, high-quality log K(ow)-dependent quantitative structure-activity relationship (QSAR) [log (IGC(50))(-1) = 0.65 (log K(ow)) - 1.22; n = 10; r(2) (adj.) = 0.969; r(2) (pred.) = 0.964; s = 0.222; F = 254; Pr > F = 0.0001]. A comparison of the observed toxicity and that predicted by the first QSAR showed that the primary propargylic alcohols with log K(ow) values < 2.00 exhibited enhanced toxicity and that this increased toxicity was inversely related to hydrophobicity. In sharp contrast, analysis of the data for the secondary propargylic alcohols exhibited little relationship with log K(ow) (r(2) = 0.339). Although the initial QSAR can be used to model the toxicity of any aliphatic alcohol for the T. pyriformis population growth impairment end point, the estimated potency would be underestimated for primary propargylic alcohols with log K(ow) values < 2.00. Moreover, estimates of toxic potency of secondary propargylic alcohols based on this QSAR should be viewed with limited confidence. The findings for beta-unsaturated alcohols in Tetrahymena were sharply different from that reported for fathead minnow acute mortality; this difference in toxicity is a result of a difference in the protocol used rather than in metabolism.

Guidelines for developing and using quantitative structure-activity relationships.

Numerous quantitative structure-activity relationships (QSARs) have been developed to predict properties, fate, and effects of mostly discrete organic chemicals. As the demand for different types of regulatory testing increases and the cost of experimental testing escalates, there is a need to evaluate the use of QSARs and provide some guidance to avoid their misuse, especially as QSARs are being considered for regulatory purposes. This paper provides some guidelines that will promote the proper development and use of QSARs. While this paper uses examples of QSARs to predict toxicity, the proposed guidelines are applicable to QSARs used to predict physical or chemical properties, environmental fate, ecological effects and health effects.

Overview of data and conceptual approaches for derivation of quantitative structure-activity relationships for ecotoxicological effects of organic chemicals.

The use of quantitative structure-activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever-increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well-defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor-mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical-specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.

Molecular quantum similarity analysis of estrogenic activity.

The main objective of this study was to evaluate the capability of 120 aromatic chemicals to bind to the human alpha estrogen receptor (hER alpha) by the use of quantum similarity methods. The experimental data were segregated into two categories, i.e., those compounds with and without estrogenicity activity (active and inactive). To identify potential ligands, semiquantitative structure-activity relationships were developed for the complete set correlating the presence or lack of binding affinity to the estrogen receptor with structural features of the molecules. The structure-activity relationships were based upon molecular similarity indices, which implicitly contain information related to changes in the electron distributions of the molecules, along with indicator variables, accounting for several structural features. In addition, the whole set was split into several chemical classes for modeling purposes. Models were validated by dividing the complete set into several training and test sets to allow for external predictions to be made.

Estrogenicity and acute toxicity of selected anilines using a recombinant yeast assay.

Suspected estrogen modulators include industrial organic chemicals (i.e., xenoestrogens), and have been shown to consist of alkylphenols, bisphenols, biphenylols, and some hydroxy-substituted polycyclic aromatic hydrocarbons. The most prominent structural feature identified to be important for estrogenic activity is a polar group capable of donating hydrogen bonds (i.e., hydroxyl) on an aromatic system. The present study was undertaken to explore the estrogenic activity and acute toxicity of chemicals containing a weaker hydrogen bond donor group on aromatic systems, i.e., the amino substituent. There is a great deal of chemical similarity between aromatic amines (anilines) and aromatic alcohols (phenols). The chemicals chosen for the current study contained an amino-substituted benzene ring with hydrophobic constituents varying in size and shape. Thus, 37 substituted aromatic amines were assayed for estrogenic activity EC50 and acute toxicity LC50 using the Saccharomyces cerevisiae recombinant yeast assay. While the EC50 of 17-beta-estradiol occurs at the 10(-10) range, the aniline with the greatest activity had an EC50 of 10(-6) M. Thus, anilines, in general, are capable only of very weak estrogenic activity in this assay. A comparison of estrogenic potency between the present group of anilines and a set of previously tested analogous phenols indicated that anilines are consistently less estrogenic than phenols. A comparison of hazard indices (EC50/LC50) of these chemicals revealed that, for the vast majority of anilines, the EC50 and LC50 were in the same order of magnitude. More specifically, estrogenic activity of para-substituted alkylanilines increases with alkyl group size up to 5 carbons in length, after which the acute toxicity of the larger alkyl-substituents precluded the ability of the compound to induce the estrogenic response.

An exploratory study of the use of multivariate techniques to determine mechanisms of toxic action.

The most successful quantitative structure-activity relationships have been developed by separating compounds by their mechanisms of toxic action (MOAs). However, to correctly determine the MOA of a compound is often not easy. We investigated the usefulness of discriminant analysis and logistic regression in determining MOAs. The discriminating variables used were the logarithm of octanol-water partition coefficients (logKow) and the experimental toxicity data obtained from Pimephales promelas and Tetrahymena pyriformis assays. Small total error rates were obtained when separating nonpolar narcotic compounds from other compounds, however, relatively high total error rates were obtained when separating less reactive compounds (polar, ester, and amine narcotics) from more reactive compounds (electrophiles, proelectrophiles, and nucleophiles).

Essential and desirable characteristics of ecotoxicity quantitative structure-activity relationships.

Quantitative structure-activity relationships (QSAR) developed and applied in the prediction of ecotoxic potencies far out number those in other areas, such as health effects. There are yet to be any formal guidelines for the development of ecotoxicological QSARs. Despite this, the depth and breadth of our knowledge of QSARs as they apply to ecotoxicology, especially short-term aquatic toxicity, allow for the formulation of characteristics that appear to be essential and/or desirable for high-quality QSARs. The three components of a QSAR are the biological activity, the property/structural descriptors, and the statistical methodology. Problems may arise from all three components and may be compounded by interactions between them. In an effort to minimize any tribulations associated with development and application of ecotoxic QSARs, a number of essential or desirable characteristics have been identified. Ecotoxicological data used in formulating the QSAR must be reliable, of high quality, and reflect a well-defined and continuous endpoint; this dataset should be diverse both in terms of potency and chemical structure (i.e., property). Descriptors used in formulating the QSAR should be of high quality, reproducible, of a number and type consistent with the endpoint being modeled, and when possible allow for a mechanistic interpretation of the QSAR. The statistical process used in formulating a QSAR should be as rigorous as possible, appropriate for the endpoint being modeled, and allow for the development of as easily interpretable (i.e., transparent) QSARs as possible. The resultant QSAR should be validated, only used within the descriptor space and chemical domain of the model, and relied on in relation to the total weight of evidence; precision of the QSAR and expectations from its application need to be related to the error in the original ecotoxicological and descriptor measurements. Finally, development of QSARs should be through the interaction of a group of multidisciplinary experts.