Structure-activity approach to the identification of environmental estrogens: the MCASE approach.

A sizable number of environmental contaminants and natural products have been found to possess hormonal activity and have been termed endocrine-disrupting chemicals. Due to the vast number (estimated at about 58,000) of environmental contaminants, their potential to adversely affect the endocrine system, and the paucity of health effects data associated with them, the U.S. Congress was led to mandate testing of these compounds for endocrine-disrupting ability. Here we provide evidence that a computational structure-activity relationship (SAR) approach has the potential to rapidly and cost effectively screen and prioritize these compounds for further testing. Our models were based on data for 122 compounds assayed for estrogenicity in the ESCREEN assay. We produced two models, one for relative proliferative effect (RPE) and one for relative proliferative potency (RPP) for chemicals as compared to the effects and potency of 17beta-estradiol. The RPE and RPP models achieved an 88 and 72% accurate prediction rate, respectively, for compounds not in the learning sets. The good predictive ability of these models and their basis on simple to understand 2-D molecular fragments indicates their potential usefulness in computational screening methods for environmental estrogens.

A substructure-based SAR model for odor perception in humans relevant to health risk assessments.

The ability of human to perceive odors is a very complex phenomenon involving the selective binding of molecules to approximately 1000 olfactory receptors. Accordingly, the derivation of a substructure-based SAR model can be expected to be problematic. Yet, based upon published data on odor thresholds of volatile organic chemicals, we were able to derive such an SAR model. An examination of the structural determinants and related modulators indicates that lipophilicity is a major contributor to olfactory perception. The availability of a substructure-based SAR model permits an examination of the relationship between the presence in the environment of odorous chemicals and public health risks.

Prevalence of mutagens in the environment: experimental data versus simulations.

The recent availability of experimental data on the mutagenicity in Salmonella of a subset of high production volume chemicals allowed a comparison with the estimate derived from computer-based simulations. The prevalence of mutagens in the subsets was not significantly different: 20% versus 19.5% based upon experimental and simulation data, respectively. This provides support for the use of the rapid and low-cost simulation approach.

SAR modeling of unbalanced data sets.

The increased acceptance of SAR approaches to hazard identification has led us to investigate methods to improve the predictive performance of SAR models. In the present study we demonstrate that although on theoretical grounds the ratio of active to inactive chemicals in the learning set should be unity, SAR models can "tolerate" an unbalanced range in ratios from 3:1 (i.e., 75% actives) to 1:2 (i.e., 33% actives) and still perform adequately. On the other hand SAR models derived from learning sets with ratios in excess of 4:1 (80% actives), even when corrected for the initial ratio do not perform satisfactorily.

Allergic contact dermatitis and its relationship to carcinogenicity.

The relationship between allergic contact dermatitis (ACD) and carcinogenicity was investigated using a recently developed and validated simulation approach. The analyses indicated that while there are electrophilic and non-electrophilic components to ACD, these were not identical to those operating in carcinogenicity. Accordingly, with respect to carcinogenicity prediction, the results of ACD do not improve the results based upon mutagenicity testing alone, the latter being a surrogate for potential electrophilicity.

Estimating the extent of the health hazard posed by high-production volume chemicals.

We used structure-activity relationship modeling to estimate the number of toxic chemicals among the high-production volume (HPV) group. We selected 200 chemicals from among the HPV chemical list and predicted the potential of each for its ability to induce a variety of adverse effects including genotoxicity, carcinogenicity, developmental, and systemic toxicity. We found a significantly less than expected proportion of toxic chemicals among the HPV sample when compared to a reference set of 10,000 chemicals representative of the universe of chemicals.

Chemical categories for health hazard identification: a feasibility study.

The use of chemical categories has been suggested in order to lower the number of chemicals tested in the High Production Volume (HPV) Chemical Challenge Program. In this investigation we examined the reliability of using organic chemical categories to classify chemicals as either toxic or nontoxic for individual toxicological effects as well as for panels of such endpoints. The analyses indicate that chemical categories are unable to consistently identify groups of chemicals with similar toxic responses either for a multiplicity of endpoints or for single effects. Our analyses suggest that if chemical categories are to be used to identify health hazards, that computer-based SAR approaches appear to be superior to arbitrary chemical categories for predicting specific toxicological effects but they are not, at this time, useful for defining the overall toxicity.

SAR modeling of genotoxic phenomena: the effect of supplementation with physiological chemicals.

Structure-activity relationship (SAR) modeling of toxicological phenomena is optimal when the ratio of toxicants to non-toxicants included in the model is unity. Frequently, however, the experimental data available are enriched with toxicants, this appears to be especially true for genotoxicity data sets. It is demonstrated herein, using a Salmonella mutagenicity data set, that when there is a paucity of non-toxicants, the learning set may be augmented with physiological chemicals on the assumption that they are non-genotoxic.

Computational toxicology and the generation of mechanistic hypotheses: gamma-butyrolactone.

In this study, we use SAR approaches in an attempt to elucidate the action of gamma-butyrolactone (GBL), an illicit drug and a dietary supplement, that can cause coma and deaths in humans while exhibiting low systemic toxicity towards rodents. The lack of systemic toxicity of GBL and of its metabolite(s) was also predicted by validated SAR models. In fact using diverse SAR models, the only significant SAR prediction was that GBL had the potential for inhibiting human cytochrome P4502D6 (CYP2D6). However, inhibition of that isozyme is not necessarily associated with toxicity. It is suggested that GBL users also abuse other substances. When GBL inhibits CYP2D6 this may prevent the CYP2D6-mediated detoxification of other toxicants simultaneously consumed by the GBL user.

A new approach to evaluate mechanistic relationships among genotoxic phenomena: validation.

In order to determine its applicability for the study of genotoxicity, a recently developed method to probe for possible mechanistic relationships among toxicological phenomena was applied to the induction of mutations in Salmonella typhimurium. Since the basis of this phenomenon is understood, this would provide a test of the applicability of the new method to DNA-based mechanisms. The results presented indicate that significant relationships are indeed found among phenomena involving damage to or modification of DNA but not between them and non-genotoxic phenomena. The present results suggest that the newly developed approach could be applied to test mechanistic hypotheses involving genotoxic phenomena.

The high production volume chemical challenge program: the relevance of the in vivo micronucleus assay.

The in vivo rodent bone marrow micronucleus assay (Mnt) has assumed a pivotal role in screening strategies for the identification of substances potentially carcinogenic to humans. The analysis of the results of the current international 5-year effort to provide toxicological data for high production volume chemicals will play a crucial role in developing future strategies for identifying health hazards. As part of that program, consideration is being given to accepting either in vitro genotoxicity data or results of the Mnt. The present analyses indicate that for hazard identification purposes that, in fact, in vitro genotoxicity test results, such as those derived from the Salmonella mutagenicity assay, may be an acceptable alternative.

Exploring the relationship between the inhibition of gap junctional intercellular communication and other biological phenomena.

The mechanistic relationship of the inhibition of gap junctional intercellular communication (GJIC) to other toxicological phenomena was explored using a recently developed method that models the properties of a large population of molecules chosen to represent the 'universe of chemicals'. The analyses indicate that inhibition of GJIC is strongly linked to the carcinogenic process in rodents, to cellular but not systemic toxicity, to biological phenomena that may involve inflammatory processes and to development effects. The inhibition of GJIC appears not to be associated with genotoxic mechanisms. With respect to cancer causation, integration of the analyses suggests that inhibition of GJIC is involved in non-genotoxic cancer induction or in the non-genotoxic phases of the carcinogenic process (such as inflammation, cell toxicity, cell proliferation, inhibition of cell differentiation and apoptosis).

Modeling the mouse lymphoma forward mutational assay: the Gene-Tox program database.

An SAR model of the induction of mutations at the tk(+/-) locus of L5178Y mouse lymphoma cells (MLA, for mouse lymphoma assay) was derived based upon a re-evaluation of experimental results reported by a Gene-Tox (GT) working group [A.D. Mitchell, A.E. Auletta, D. Clive, P.E. Kirby, M.M. Moore, B.C. Myhr, The L5178Y/tk(+/-) mouse lymphoma specific gene and chromosomal mutation assay. A phase III report of the U.S. Environmental Protection Agency Gene-Tox Program, Mutation Res. 394 (1997) 177-303.]. The predictive performance of the GT MLA SAR model was similar to that of a Salmonella mutagenicity model containing the same number of chemicals. However, the structural determinants (biophores) derived from the GT MLA SAR model include both electrophilic as well as non-electrophilic moieties, suggesting that the induction of mutations in the MLA may occur by both direct interaction with DNA and by non-DNA-related mechanisms. This was confirmed by the observation that the set of biophores associated with MLA overlapped significantly with those associated with phenomena related to loss of heterozygosity, chromosomal rearrangements and aneuploidy. The MLA SAR model derived from the GT data evaluation was significantly more predictive than an SAR model previously derived from MLA data reported by the US National Toxicology Program [B. Henry, S.G. Grant, G. Klopman, H.S. Rosenkranz, Induction of forward mutations at the thymidine kinase locus of mouse lymphoma cells: evidence for electrophilic and non-electrophilic mechanisms, Mutation Res. 397 (1998) 331-335.]. Moreover, the latter model appeared to be more complex than the former, suggesting that the GT induction data was both simpler mechanistically and more homogeneous than that of the NTP.

Structural Basis of the Toxicity of Chemicals in Cultured Human HeLa Cells.

The newly developed "chemical diversity approach" was used to determine whether or not it is likely that a panel of in vitro cell toxicity assays capable of predicting in vivo eye irritation could be assembled. The analyses, based upon available and validated structure-activity relationship models of toxicity in cultured human HeLa cells and murine Balb/c 3T3 cells, indicate that a battery of cytotoxicity tests could provide a viable alternative to the animal-based procedure.

A battery of cell toxicity assays as predictors of eye irritation: a feasibility study.

The newly developed "chemical diversity approach" was used to determine whether or not it is likely that a panel of in vitro cell toxicity assays capable of predicting in vivo eye irritation could be assembled. The analyses, based upon available and validated structure-activity relationship models of toxicity in cultured human HeLa cells and murine Balb/c 3T3 cells, indicate that a battery of cytotoxicity tests could provide a viable alternative to the animal-based procedure.

The High Production Volume Chemical Challenge Program : The Rodent LD50 and its Possible Replacement.

The High Production Volume Chemical Challenge Program provides an opportunity to re-examine the usefulness and informational value of tests currently used to obtain preliminary hazard identification data. With a view to assessing the mechanistic information provided by the rodent LD50 test and to ascertain the possibility of replacing it with other "more acceptable" assays, we used a recently developed approach to determine the relationship of the LD50 assay to other toxicological protocols. Our analyses indicate that, of the assays examined, the LD50 was significantly related to toxicity in cultured cells and to binding at the Ah receptor.

Structural determinants of developmental toxicity in hamsters.

A CASE/MULTICASE structure activity relationship (SAR) model of developmental toxicity of chemicals in hamsters (HaDT) was developed. The model exhibited a predictive performance of 74%. The model's overall predictivity and informational content were similar to those of an SAR model of mutagenicity in Salmonella. However, unlike the Salmonella mutagenicity model, the HaDT model did not identify overtly chemically reactive moieties as associated with activity. Moreover, examination of the number and nature of significant structural determinants suggested that developmental toxicity in hamsters was not the result of a unique mechanism or attack on a specific molecular target. The analysis also indicated that the availability of experimental data on additional chemicals would improve the performance of the SAR model.

The mysterious Mauritian red nectar: a selective toxicant?

Using knowledge-based computational structure-activity relationship models, it is hypothesized that the aurone responsible for the uniquely red nectar of several Mauritian bird-pollinated plants functions as a repellant of nectar-robbing or herbivorous mammalian species.

Applications of the case/multicase SAR method to environmental and public health situations.

The availability of validated and characterized SAR models of toxicological phenomena provides a method to apply SAR technology to a variety of environmental, public health and industrial situations. These include (i) the prioritization of environmental pollutants for control and/or regulation, (ii) the design of multi-action optimized therapeutics from which the potential for unwanted side-effects have been engineered out, (iii) the development of SAR-based computer-driven screening procedure to identify candidate therapeutics based upon combinatorial chemistry or compilations of molecular structures, (iv) the generation of toxicological profiles to be used in the selection of benign chemicals in the early stages of product development.