Impact of environmental chemicals on key transcription regulators and correlation to toxicity end points within EPA's ToxCast program

Exposure to environmental chemicals adds to the burden of disease in humans and wildlife to a degree that is difficult to estimate and, thus, mitigate. The ability to assess the impact of existing chemicals for which little to no toxicity data are available or to foresee such effects during early stages of chemical development and use, and before potential exposure occurs, is a pressing need. However, the capacity of the current toxicity evaluation approaches to meet this demand is limited by low throughput and high costs. In the context of EPA's ToxCast project, we have evaluated a novel cellular biosensor system (Factorial (1) ) that enables rapid, high-content assessment of a compound's impact on gene regulatory networks. The Factorial biosensors combined libraries of cis- and trans-regulated transcription factor reporter constructs with a highly homogeneous method of detection enabling simultaneous evaluation of multiplexed transcription factor activities. Here, we demonstrate the application of the technology toward determining bioactivity profiles by quantitatively evaluating the effects of 309 environmental chemicals on 25 nuclear receptors and 48 transcription factor response elements. We demonstrate coherent transcription factor activity across nuclear receptors and their response elements and that Nrf2 activity, a marker of oxidative stress, is highly correlated to the overall promiscuity of a chemical. Additionally, as part of the ToxCast program, we identify molecular targets that associate with in vivo end points and represent modes of action that can serve as potential toxicity pathway biomarkers and inputs for predictive modeling of in vivo toxicity.

Exposure science and the U.S. EPA National Center for Computational Toxicology

The emerging field of computational toxicology applies mathematical and computer models and molecular biological and chemical approaches to explore both qualitative and quantitative relationships between sources of environmental pollutant exposure and adverse health outcomes. The integration of modern computing with molecular biology and chemistry will allow scientists to better prioritize data, inform decision makers on chemical risk assessments and understand a chemical's progression from the environment to the target tissue within an organism and ultimately to the key steps that trigger an adverse health effect. In this paper, several of the major research activities being sponsored by Environmental Protection Agency's National Center for Computational Toxicology are highlighted. Potential links between research in computational toxicology and human exposure science are identified. As with the traditional approaches for toxicity testing and hazard assessment, exposure science is required to inform design and interpretation of high-throughput assays. In addition, common themes inherent throughout National Center for Computational Toxicology research activities are highlighted for emphasis as exposure science advances into the 21st century.

In vitro screening of environmental chemicals for targeted testing prioritization: the ToxCast project

BACKGROUND

Chemical toxicity testing is being transformed by advances in biology and computer modeling, concerns over animal use, and the thousands of environmental chemicals lacking toxicity data. The U.S. Environmental Protection Agency's ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches.

OBJECTIVES

This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity.

METHODS

We tested 309 mostly pesticide active chemicals in 467 assays across nine technologies, including high-throughput cell-free assays and cell-based assays, in multiple human primary cells and cell lines plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed.

RESULTS

Chemicals displayed a broad spectrum of activity at the molecular and pathway levels. We saw many expected interactions, including endocrine and xenobiotic metabolism enzyme activity. Chemicals ranged in promiscuity across pathways, from no activity to affecting dozens of pathways. We found a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also found associations between a small set of in vitro assays and rodent liver lesion formation.

CONCLUSIONS

This approach promises to provide meaningful data on the thousands of untested environmental chemicals and to guide targeted testing of environmental contaminants.

Predictive models for carcinogenicity and mutagenicity: frameworks, state-of-the-art, and perspectives

Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include Vitotox, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-throughput assays combined with innovative data-mining and in silico methods. Various initiatives in this regard have begun, including CAESAR, OSIRIS, CHEMOMENTUM, CHEMPREDICT, OpenTox, EPAA, and ToxCast. In silico methods can be used for priority setting, mechanistic studies, and to estimate potency. Ultimately, such efforts should lead to improvements in application of in silico methods for predicting carcinogenicity to assist industry and regulators and to enhance protection of public health.

Toward a public toxicogenomics capability for supporting predictive toxicology: survey of current resources and chemical indexing of experiments in GEO and ArrayExpress

A publicly available toxicogenomics capability for supporting predictive toxicology and meta-analysis depends on availability of gene expression data for chemical treatment scenarios, the ability to locate and aggregate such information by chemical, and broad data coverage within chemical, genomics, and toxicological information domains. This capability also depends on common genomics standards, protocol description, and functional linkages of diverse public Internet data resources. We present a survey of public genomics resources from these vantage points and conclude that, despite progress in many areas, the current state of the majority of public microarray databases is inadequate for supporting these objectives, particularly with regard to chemical indexing. To begin to address these inadequacies, we focus chemical annotation efforts on experimental content contained in the two primary public genomic resources: ArrayExpress and Gene Expression Omnibus. Automated scripts and extensive manual review were employed to transform free-text experiment descriptions into a standardized, chemically indexed inventory of experiments in both resources. These files, which include top-level summary annotations, allow for identification of current chemical-associated experimental content, as well as chemical-exposure-related (or "Treatment") content of greatest potential value to toxicogenomics investigation. With these chemical-index files, it is possible for the first time to assess the breadth and overlap of chemical study space represented in these databases, and to begin to assess the sufficiency of data with shared protocols for chemical similarity inferences. Chemical indexing of public genomics databases is a first important step toward integrating chemical, toxicological and genomics data into predictive toxicology.

DSSTox chemical-index files for exposure-related experiments in ArrayExpress and Gene Expression Omnibus: enabling toxico-chemogenomics data linkages

SUMMARY

The Distributed Structure-Searchable Toxicity (DSSTox) ARYEXP and GEOGSE files are newly published, structure-annotated files of the chemical-associated and chemical exposure-related summary experimental content contained in the ArrayExpress Repository and Gene Expression Omnibus (GEO) Series (based on data extracted on September 20, 2008). ARYEXP and GEOGSE contain 887 and 1064 unique chemical substances mapped to 1835 and 2381 chemical exposure-related experiment accession IDs, respectively. The standardized files allow one to assess, compare and search the chemical content in each resource, in the context of the larger DSSTox toxicology data network, as well as across large public cheminformatics resources such as PubChem (http://pubchem.ncbi.nlm.nih.gov).

AVAILABILITY

Data files and documentation may be accessed online at http://epa.gov/ncct/dsstox/.

A novel approach: chemical relational databases, and the role of the ISSCAN database on assessing chemical carcinogenicity

Mutagenicity and carcinogenicity databases are crucial resources for toxicologists and regulators involved in chemicals risk assessment. Until recently, existing public toxicity databases have been constructed primarily as "look-up-tables" of existing data, and most often did not contain chemical structures. Concepts and technologies originated from the structure-activity relationships science have provided powerful tools to create new types of databases, where the effective linkage of chemical toxicity with chemical structure can facilitate and greatly enhance data gathering and hypothesis generation, by permitting: a) exploration across both chemical and biological domains; and b) structure-searchability through the data. This paper reviews the main public databases, together with the progress in the field of chemical relational databases, and presents the ISSCAN database on experimental chemical carcinogens.

Future of toxicology--predictive toxicology: An expanded view of "chemical toxicity"

A chemistry approach to predictive toxicology relies on structure-activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. These approaches are less well-suited, however, to the challenges of global toxicity prediction, i.e., to predicting the potential toxicity of structurally diverse chemicals across a wide range of end points of regulatory and pharmaceutical concern. New approaches that have the potential to significantly improve capabilities in predictive toxicology are elaborating the "activity" portion of the SAR paradigm. Recent advances in two areas of endeavor are particularly promising. Toxicity data informatics relies on standardized data schema, developed for particular areas of toxicological study, to facilitate data integration and enable relational exploration and mining of data across both historical and new areas of toxicological investigation. Bioassay profiling refers to large-scale high-throughput screening approaches that use chemicals as probes to broadly characterize biological response space, extending the concept of chemical "properties" to the biological activity domain. The effective capture and representation of legacy and new toxicity data into mineable form and the large-scale generation of new bioassay data in relation to chemical toxicity, both employing chemical structure information to inform and integrate diverse biological data, are opening exciting new horizons in predictive toxicology.

The ToxCast program for prioritizing toxicity testing of environmental chemicals

The U.S. Environmental Protection Agency (EPA) is developing methods for utilizing computational chemistry, high-throughput screening (HTS), and various toxicogenomic technologies to predict potential for toxicity and prioritize limited testing resources toward chemicals that likely represent the greatest hazard to human health and the environment. This chemical prioritization research program, entitled "ToxCast," is being initiated with the purpose of developing the ability to forecast toxicity based on bioactivity profiling. The proof-of-concept phase of ToxCast will focus upon chemicals with an existing, rich toxicological database in order to provide an interpretive context for the ToxCast data. This set of several hundred reference chemicals will represent numerous structural classes and phenotypic outcomes, including tumorigens, developmental and reproductive toxicants, neurotoxicants, and immunotoxicants. The ToxCast program will evaluate chemical properties and bioactivity profiles across a broad spectrum of data domains: physical-chemical, predicted biological activities based on existing structure-activity models, biochemical properties based on HTS assays, cell-based phenotypic assays, and genomic and metabolomic analyses of cells. These data will be generated through a series of external contracts, along with collaborations across EPA, with the National Toxicology Program, and with the National Institutes of Health Chemical Genomics Center. The resulting multidimensional data set provides an informatics challenge requiring appropriate computational methods for integrating various chemical, biological, and toxicological data into profiles and models predicting toxicity.

Chemical structure indexing of toxicity data on the internet: moving toward a flat world

Standardized chemical structure annotation of public toxicity databases and information resources is playing an increasingly important role in the 'flattening' and integration of diverse sets of biological activity data on the Internet. This review discusses public initiatives that are accelerating the pace of this transformation, with particular reference to toxicology-related chemical information. Chemical content annotators, structure locator services, large structure/data aggregator web sites, structure browsers, International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) codes, toxicity data models and public chemical/biological activity profiling initiatives are all playing a role in overcoming barriers to the integration of toxicity data, and are bringing researchers closer to the reality of a mineable chemical Semantic Web. An example of this integration of data is provided by the collaboration among researchers involved with the Distributed Structure-Searchable Toxicity (DSSTox) project, the Carcinogenic Potency Project, projects at the National Cancer Institute and the PubChem database.

Genotoxicity and metabolism of the source-water contaminant 1,1-dichloropropene: activation by GSTT1-1 and structure-activity considerations

1,1-Dichloropropene (1,1-DCPe) is a contaminant of some source waters used to make drinking water. Because of this and the fact that no toxicological data were available for this compound, which is structurally similar to the rodent carcinogen 1,3-dichloropropene (1,3-DCPe), 1,1-DCPe was placed on the Contaminant Candidate List of the US Environmental Protection Agency. Consequently, we have performed a hazard characterization of 1,1-DCPe by evaluating its mutagenicity in the Salmonella assay and its DNA damaging (comet assay) and apoptotic (caspase assay) activities in human lymphoblastoid cells. In Salmonella, 1,1-DCPe was not mutagenic in strains TA98, TA100, TA1535, or TA104 +/-S9 mix. However, it was clearly mutagenic in strain RSJ100, which expresses the rat GSTT1-1 gene. 1,1-DCPe did not induce DNA damage in GSTT1-1-deficient human lymphoblastoid cells, and it induced apoptosis in these cells only at 5 mM. Consistent with its mutagenesis in RSJ100, 1,1-DCPe reacted with glutathione (GSH) in vitro, suggesting an addition-elimination mechanism to account for the detected GSH conjugate. 1,1-DCPe was approximately 5000 times more mutagenic than its ethene congener 1,1-dichloroethylene (1,1-DCE or vinylidene chloride). Neither 1,1-DCE nor 1,3-DCPe showed enhanced mutagenicity in strain RSJ100, indicating a lack of activation of these congeners by GSTT1-1. Thus, 1,1-DCPe is a base-substitution mutagen requiring activation by GSTT1-1, possibly involving the production of a reactive episulfonium ion. This bioactivation mechanism of 1,1-DCPe is different from that of its congeners 1,1-DCE and 1,3-DCPe. The presence of 1,1-DCPe in source waters could pose an ecological or human health risk. Occurrence data for 1,1-DCPe in finished drinking water are needed to estimate human exposure to, and possible health risks from, this mutagenic compound.

Challenges in constructing statistically based structure-activity relationship models for developmental toxicity

Regulatory agencies are increasingly called upon to review large numbers of environmental contaminants that have not been characterized for their potential to pose a health risk. Additionally, there is special interest in protecting potentially sensitive subpopulations and identifying developmental toxicants that may be present in the environment. Thus, there is an urgent need for efficient methods to screen large numbers of chemicals for their potential to pose a developmental hazard. One potential screening method involves the use of statistically based structure-activity relationship (SAR) tools to predict activity of untested chemicals. Such systems rely on statistical analyses to discern relationships between structure and activity for a training set of substances. Predictions can then be made for an untested substance as long as its structural features are encompassed by chemicals of the training set. In theory, such systems could assist regulatory agencies in their screening efforts; however, to date, there has been little independent evaluation of these tools for this use. To contribute to such an evaluation, the International Life Sciences Institute Risk Science Institute (ILSI RSI) convened a Working Group to examine methodology used to construct statistically based SAR systems for developmental toxicity. This document reports on the deliberations of the Working Group, which concluded that an improved process is needed for utilizing developmental toxicity data in the construction of statistically based SAR models. The process must be objective, reproducible, rational and transparent. Moreover, it must be informed by the expertise of developmental toxicologists and biologists and must be subject to peer review.

Comparative mutagenicity of halomethanes and halonitromethanes in Salmonella TA100: structure-activity analysis and mutation spectra

Halonitromethanes (HNMs) are a recently identified class of disinfection by-products (DPBs) in drinking water that are mutagenic in Salmonella and potent inducers of DNA strand breaks in mammalian cells. Here we compared the mutagenic potencies of the HNMs to those of their halomethane (HM) homologues by testing all nine HNMs and seven of the nine HMs (minus bromomethane and chloromethane) under the same conditions (the pre-incubation assay) in Salmonella TA100 +/- S9. We also determined the mutation spectra for several DBPs. In the presence of S9, all nine HNMs, but only three HMs, dibromomethane (DBM), dichloromethane (DCM), and bromochloromethane (BCM), were mutagenic. Only two DBPs of each class were mutagenic in the absence of S9. The HNMs were generally more potent mutagens than their HM homologues, and the brominated forms of both classes of DBPs were more mutagenic and cytotoxic than their chlorinated homologues. The HNMs were at least 10 times more cytotoxic than the HMs, and the cytotoxicity rankings in the presence of S9 were similar for the HNMs and the HMs. The addition of a nitro-group to BCM did not change the mutation spectra significantly, with both homologues inducing primarily (55-58%) GC --> AT transitions. The greater cytotoxic and mutagenic activities of the HNMs relative to the HMs are likely due to the greater intrinsic reactivity conferred by the nitro-group. Energy calculations predicted increased reactivity with increasing bromination and greater reactivity of the HNMs versus the HMs (Elumo values were approximately 20 kcal/mol lower for the HNMs compared to their HM homologues). Given that the HNMs also are potent genotoxins in mammalian cells [Environ. Sci. Technol. 38 (2004) 62] and are more mutagenic and 10x more cytotoxic in Salmonella than the HMs, whose levels are regulated in drinking water, further study of their occurrence and potential health effects is warranted.

Mutagenicity in Salmonella of halonitromethanes: a recently recognized class of disinfection by-products in drinking water

Halonitromethanes (HNMs) are a recently identified class of disinfection by-products (DBPs) in drinking water. They include chloronitromethane (CHN), dichloronitromethane (DCNM), trichloronitromethane (TCNM), bromonitromethane (BNM), dibromonitromethane (DBNM), tribromonitromethane (TBNM), bromochloronitromethane (BCNM),dibromochloronitromethane (DBCNM), and bromodichloronitromethane (BDCNM). Previous studies of TCNM, DCNM, CNM, and TBNM found that all four were mutagenic in bacteria, and a recent study showed that all nine induced DNA damage in CHO cells. Here, all nine HNMs were evaluated in the Salmonella plate-incorporation assay +/- S9 using strains TA98, TA100, TA104, TPT100, and the glutathione transferase theta (GSTT1-1)-expressing strain RSJ100. All were mutagenic, most with and without S9. In the absence of S9, six were mutagenic in TA98, six in TA100, and three in TA104; in the presence of S9, these numbers were five, seven, and three, respectively. Thus, the HNMs-induced base substitutions primarily at GC sites as well as frameshifts. Although five HNMs were activated to mutagens in RSJ100 -S9, they produced < or =2-fold increases in revertants and potencies <506 rev/micromol. The rank order of the HNMs by mutagenic potency in TA100 +S9 was (BCNM DBNM) > (TBNM CNM > BNM DCNM BDCNM) > (TCNM = DBCNM). The mean rev/micromol for the three groupings, respectively, were 1423, 498, and 0, which classifies the HNMs as weak mutagens in Salmonella. Reaction of the dihalo and monohalo HNMs with GSH, possibly GSTT1-1, is a possible mechanism for formation of ultimate mutagenic products. Because the HNMs are mutagenic in Salmonella (present study) and potent clastogens in mammalian cells [Environ. Sci. Technol. 38 (2004) 62], their presence in drinking water warrants further research on their potential health effects.

Identification and Characterization of Novel Stable Deoxyguanosine and Deoxyadenosine Adducts of Benzo[a]pyrene-7,8-quinone from Reactions at Physiological pH

Benzo[a]pyrene (B[a]P) is an archetypal member of the family of polycyclic aromatic hydrocarbons (PAHs) and is a widely distributed environmental pollutant. B[a]P is known to induce cancer in animals, and B[a]P-containing complex mixtures are human carcinogens. B[a]P exerts its genotoxic and carcinogenic effects through metabolic activation forming reactive intermediates that damage DNA. DNA adduction by B[a]P is a complex phenomenon that involves the formation of both stable and unstable (depurinating) adducts. One pathway by which B[a]P can mediate genotoxicity is through the enzymatic formation of B[a]P-7,8-quinone (BPQ) from B[a]P-7,8-diol by members of the aldo-keto-reductase (AKR) family. Once formed, BPQ can act as a reactive Michael acceptor that can alkylate cellular nucleophiles including DNA and peptides. Earlier studies have reported on the formation of stable and depurinating adducts from the reaction of BPQ with DNA and nucleosides, respectively. However, the syntheses and characterization of the stable adducts from these interactions have not been addressed. In this study, the reactivity of BPQ toward 2'-deoxyguanosine (dG) and 2'-deoxyadenosine (dA) nucleosides under physiological pH conditions is examined. The identification and characterization of six novel BPQ-nucleoside adducts obtained from the reaction of BPQ and dG or dA in a mixture of phosphate buffer and dimethylformamide are reported. The structures of these adducts were determined by ultraviolet spectroscopy, electrospray mass spectrometry, and NMR experiments including (1)H, (13)C, two-dimensional COSY, one-dimensional NOE, ROESY, HMQC, HSQC, and HMBC. The reaction of BPQ with dG afforded four unique Michael addition products: two diastereomers of 8-N(1),9-N(2)-deoxyguanosyl-8,10-dihydroxy-9,10-dihydrobenzo[a]pyren-7(8H)-one (BPQ-dG(1,2)) and two diastereomers of 10-(N(2)-deoxyguanosyl)-9,10-dihydro-9-hydroxybenzo[a]pyrene-7,8-dione (BPQ-dG(3,4)). The BPQ-dG(1,2)( )()adducts suggest a 1,6-Michael addition reaction of dG, an oxidation of the hydroquinone to the quinone, a 1,4-Michael addition of water, and an internal cyclization. The BPQ-dG(3,4)( )()adducts suggest a 1,4-Michael addition reaction of dG, an oxidation of the hydroquinone to the quinone, and a 1,6-Michael addition of water. Under similar but extended reaction conditions, the reaction of BPQ with dA produced only one diastereomeric pair of adducts identified as 8-N(6),10-N(1)-deoxyadenosyl-8,9-dihydroxy-9,10-dihydrobenzo[a]pyren-7(8H)-one (BPQ-dA(1,2)). The BPQ-dA(1,2)( )()adducts suggest a 1,4-Michael addition reaction of dA, an oxidation of the hydroquinone to the quinone, a 1,6-Michael addition of water, and an internal cyclization. As considerable efforts have been placed in documenting the genotoxic effects of BPQ, this first report of the identification and characterization of these stable adducts of BPQ formed under physiological pH conditions is expected to contribute significantly to the area of BPQ-mediated genotoxicity and carcinogenesis.

Interaction of organophosphate pesticides and related compounds with the androgen receptor

Identification of several environmental chemicals capable of binding to the androgen receptor (AR) and interfering with its normal function has heightened concern about adverse effects across a broad spectrum of environmental chemicals. We previously demonstrated AR antagonist activity of the organophosphate (OP) pesticide fenitrothion. In this study, we characterized AR activity of analogues of fenitrothion to probe the structural requirements for AR activity among related chemicals. AR activity was measured using HepG2 human hepatoma cells transfected with human AR plus an androgen-responsive luciferase reporter gene, MMTV-luc. AR antagonist activity decreased as alkyl chain length of the phosphoester increased, whereas electron-donating properties of phenyl substituents of the tested compounds did not influence AR activity. Oxon derivatives of fenitrothion, which are more likely to undergo hydrolytic degradation, had no detectable AR antagonist activity. Molecular modeling results suggest that hydrogen-bond energies and the maximum achievable interatomic distance between two terminal H-bond capable sites may influence both the potential to interact with the AR and the nature of the interaction (agonist vs. antagonist) within this series of chemicals. This hypothesis is supported by the results of recent AR homology modeling and crystallographic studies relative to agonist- and antagonist-bound AR complexes. The present results are placed in the context of structure-activity knowledge derived from previous modeling studies as well as studies aimed toward designing nonsteroidal antiandrogen pharmaceuticals. Present results extend understanding of the structural requirements for AR activity to a new class of nonsteroidal, environmental, OP-related chemicals.

Distributed structure-searchable toxicity (DSSTox) public database network: a proposal

The ability to assess the potential genotoxicity, carcinogenicity, or other toxicity of pharmaceutical or industrial chemicals based on chemical structure information is a highly coveted and shared goal of varied academic, commercial, and government regulatory groups. These diverse interests often employ different approaches and have different criteria and use for toxicity assessments, but they share a need for unrestricted access to existing public toxicity data linked with chemical structure information. Currently, there exists no central repository of toxicity information, commercial or public, that adequately meets the data requirements for flexible analogue searching, Structure-Activity Relationship (SAR) model development, or building of chemical relational databases (CRD). The distributed structure-searchable toxicity (DSSTox) public database network is being proposed as a community-supported, web-based effort to address these shared needs of the SAR and toxicology communities. The DSSTox project has the following major elements: (1) to adopt and encourage the use of a common standard file format (structure data file (SDF)) for public toxicity databases that includes chemical structure, text and property information, and that can easily be imported into available CRD applications; (2) to implement a distributed source approach, managed by a DSSTox Central Website, that will enable decentralized, free public access to structure-toxicity data files, and that will effectively link knowledgeable toxicity data sources with potential users of these data from other disciplines (such as chemistry, modeling, and computer science); and (3) to engage public/commercial/academic/industry groups in contributing to and expanding this community-wide, public data sharing and distribution effort. The DSSTox project's overall aims are to effect the closer association of chemical structure information with existing toxicity data, and to promote and facilitate structure-based exploration of these data within a common chemistry-based framework that spans toxicological disciplines.

Improving structure-linked access to publicly available chemical toxicity information

Publicly available toxicity databases serve as the central resource in efforts to develop algorithms for assessing potential chemical toxicity. File standardization and linkage of chemical structures with chemical toxicity information are essential first steps in providing broad access to existing toxicity information, for deriving useful structure-activity relationship (SAR) models, performing analog searches, and estimating the potential toxicity of new chemicals. This review will focus on current efforts to improve structure-linked access to publicly available sources of toxicity information, outlining current web-based resources as well as two new database initiatives for standardizing and consolidating public chemical toxicity information.

An evaluation of the mutagenicity, metabolism, and DNA adduct formation of 5-nitrobenzo[b]naphtho[2,1-d]thiophene

Thioarenes, sulfur-containing polycyclic aromatic compounds, are environmental contaminants suspected of posing human health risks. In this study, 5-nitrobenzo[b]naphtho[2,1-d]thiophene (5-nitro-BNT), a nitrated-thioarene, was examined for its mutagenicity, metabolism and subsequent formation of DNA adducts. 5-Nitro-BNT was weakly mutagenic in Salmonella typhimurium strains TA98 and TA100 without Aroclor-1254-induced rat liver S9 (S9), and its activity was increased in the presence of S9. Anaerobic metabolism of 5-nitro-BNT by S9 or xanthine oxidase (XO) produced one major metabolite, identified as 5-amino-BNT by NMR, MS, and UV spectroscopy and by comparison with an authentic standard. Aerobic S9 metabolism of 5-nitro-BNT produced a major metabolite, identified as trans-9,10-dihydroxy-9,10-dihydro-5-nitro-BNT (5-nitro-BNT-9,10-diol). Also present was a minor amount of 5-amino-BNT and trans-9,10-dihydroxy-9,10-dihydro-5-amino-BNT (5-amino-BNT-9,10-diol). DNA adduct analyses were performed using the (32)P-postlabeling assay and reversed-phase HPLC. Three major XO-derived calf thymus DNA adducts were detected. On the basis of their chromatographic mobilities, two adducts were identified as reaction products of 5-nitro-BNT with 2'-deoxyguanosine and one adduct with 2'-deoxyadenosine. Incorporation of allopurinol (a specific XO inhibitor) in the incubation mixture resulted in loss of all three adducts, confirming enzymatic mediation by XO. Aerobic S9 activation of 5-nitro-BNT with calf thymus DNA produced three adducts. On the basis of their chromatographic mobilities, two were identified as reaction products of 5-nitro-BNT with 2'-deoxyguanosine and one with 2'-deoxyadenosine. Incorporation of 1-aminobenzotriazole (a P450 inhibitor) in the incubation mixture resulted in a loss of these adducts, confirming enzymatic mediation by P450. Aerobic S9-catalyzed metabolism of 5-nitro-BNT-9,10-diol produced the same DNA adducts as observed with 5-nitro-BNT. Aerobic S9-catalyzed metabolism of 5-amino-BNT-9,10-diol produced the same deoxyadenosine-derived DNA adducts as observed with 5-nitro-BNT and 5-nitro-BNT-9,10-diol. These results provide additional information that both ring oxidation and nitroreduction are involved in the metabolism, DNA adduct formation and mutagenicity of 5-nitro-BNT.

Glucagon-like peptide 1 stimulates lipolysis in clonal pancreatic beta-cells (HIT)

Glucagon-like peptide 1 (GLP-1) is the most potent physiological incretin for insulin secretion from the pancreatic beta-cell, but its mechanism of action has not been established. It interacts with specific cell-surface receptors, generates cAMP, and thereby activates protein kinase A (PKA). Many changes in pancreatic beta-cell function have been attributed to PKA activation, but the contribution of each one to the secretory response is unknown. We show here for the first time that GLP-1 rapidly released free fatty acids (FFAs) from cellular stores, thereby lowering intracellular pH (pHi) and stimulating FFA oxidation in clonal beta-cells (HIT). Similar changes were observed with forskolin, suggesting that stimulation of lipolysis was a function of PKA activation in beta-cells. Triacsin C, which inhibits the conversion of FFAs to long-chain acyl CoA (LC-CoA), enhanced basal FFA efflux as well as GLP-1-induced acidification and efflux of FFAs from the cell. Increasing the concentration of the lipase inhibitor orlistat progressively and largely diminished the increment in secretion caused by forskolin. However, glucose-stimulated secretion was less inhibited by orlistat and only at the highest concentration tested. Because the acute addition of FFAs also increases glucose-stimulated insulin secretion, these data suggest that the incretin function of GLP-1 may involve a major role for lipolysis in cAMP-mediated potentiation of secretion.

Mutation spectra in Salmonella of analogues of MX: implications of chemical structure for mutational mechanisms

We determined the mutation spectra in Salmonella of four chlorinated butenoic acid analogues (BA-1 through BA-4) of the drinking water mutagen 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone (MX) and compared the results with those generated previously by us for MX and a related compound, MCF. We then considered relationships between the properties of mutagenic potency and mutational specificity for these six chlorinated butenoic acid analogues. In TA98, the three most potent mutagens, BA-3, BA-4, MX, and the organic extract, all induced large percentages of complex frameshifts (33-67%), which distinguish these agents from any other class of compound studied previously. In TA100, which has only GC sites for mutation recovery, >71% of the mutations induced by all of the agents were GC-->TA transversions. The availability of both GC and TA sites for mutation in TA104 resulted in greater distinctions in mutational specificity than in TA100. MX targeted GC sites almost exclusively (98%); the structurally similar BA-4 and BA-2 produced mutations at similar frequencies at both GC and AT sites; and the structurally similar BA-3 and BA-1 induced most mutations at AT sites (69%). Thus, large variations in structural properties influencing relative mutagenic potency appeared to be distinct from the more localized similar structural features influencing mutagenic specificity in TA104. Among a set of physicochemical properties examined for the six butenoic acids, a significant correlation was found between pK(a) and mutagenic potency in TA100, even when the unionized fraction of the activity dose was considered. In addition, a correlation in CLOGP for BA-1 to BA-4 suggested a role for bioavailability in determining mutagenic potency. These results illustrate the potential value of structural analyses for exploring the relationship between chemical structure and mutational mechanisms. To our knowledge, this is the first study in which such analyses have been applied to structural analogues for which both mutagenic potency and mutation spectra date were available.

Mutation spectra of the drinking water mutagen 3-chloro-4-methyl-5-hydroxy-2(5H)-furanone (MCF) in Salmonella TA100 and TA104: comparison to MX

The chlorinated drinking water mutagen 3-chloro-4-methyl-5-hydroxy-2(5H)-furanone (MCF) occurs at concentrations similar to or greater than that of the related furanone 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone (MX). MCF and MX differ structurally only by replacement of a 3-methyl in MCF with a 3-dichloromethyl in MX; yet, MCF is significantly less mutagenic than MX and produces different adducts when reacted with nucleosides or DNA. To explore further the effects that these structural differences might have on the biological activity of MCF and MX, we determined the mutation spectra of MCF in Salmonella strains TA100 and TA104 and of MX in strain TA104; the spectrum of MX in TA100 had been determined previously. In TA100, which presents only GC targets for mutagenesis, MCF induced primarily (75%) GC --> TA transversions, with most of the remaining revertants (20%) being GC --> AT transitions. This spectrum was not significantly different from that of MX in TA100 (P = 0.07). In TA104, which presents both GC and AT targets, MCF induced a lower percentage (57%) of GC --> TA transversions, with most of the remaining revertants (33%) being AT --> TA transversions. In contrast, MX induced almost only (98%) GC --> TA transversions in TA104, with the remaining revertants (2%) being AT --> TA transversions. Thus, almost all (98%) of the MX mutations were targeted at GC sites in TA104, whereas only 63% of the MCF mutations were so targeted. These results are consistent with the published findings that MX: (1) forms an adduct on guanosine when reacted with guanosine, (2) induces apurinic sites in DNA, and (3) forms a minor adduct on adenosine when reacted with adenosine or DNA. The results are also consistent with evidence that MCF forms adenosine adducts when reacted with adenosine. Our results show that the replacement of the 4-methyl in MCF with a 4-dichloromethyl to form MX not only increases dramatically the mutagenic potency but also shifts significantly the mutagenic specificity from almost equal targeting of GC and AT sites by MCF to almost exclusive targeting of GC sites by MX. Environ. Mol. Mutagen. 35:106-113, 2000 Published 2000 Wiley-Liss, Inc.

Theoretical study of the SNV reaction of trichloroethylene (TCE) and CH3S- as a model for glutathione conjugation of TCE

Trichloroethylene (TCE), a major environmental pollutant, is activated to mutagenic and nephrotoxic intermediates through a glutathione (GSH) conjugation pathway. Three product isomers of GSH-TCE conjugation, having potentially different toxicities, are theoretically possible: cis- or trans-S-(1, 2-dichlorovinyl)glutathione (cis- or trans-1,2-DCVG, respectively) or 2,2-DCVG. This study involved application of ab initio molecular orbital theory to computing potential energy profiles (PEPs) and predicting product outcome of the reaction of CH3S- with TCE as a model for GSH-TCE conjugation in biological systems. A goal of this study was to determine the extent to which a body of chemical knowledge pertaining to nucleophilic vinylic substitution (SNV) reactions, of which the GSH-TCE conjugation is a representative example, is relevant to this biological conjugation problem. PEPs were computed for all studied species at the HF/6-31+G level of theory; electron correlation effects were estimated at the MP2/6-31+G and MP4/6-31+G levels, and the influence of solvation was estimated using the PS-GVB solvation model. Multiple proposed reaction pathways were considered, including conjugation at the C1 or C2 site on TCE, by in-plane (sigma) or out-of-plane (pi) approach of the nucleophile. Some aspects of the MP2 and HF PEPs were found to differ significantly. However, on the basis of comparison of activation barriers, calculations at all levels of theory predict preference for C2 conjugation over C1 conjugation and formation of the trans-1,2-DCVM product over the cis-1,2-DCVM product. These predictions are consistent with GSH-TCE conjugation results from in vivo experiments. In contrast, relative product energies appear to be a poor indicator of the product outcome for this system. Hence, theoretical consideration of the reaction chemistry in the vicinity of the site of nucleophilic addition appears to be necessary and sufficient to predict the outcome of the enzyme-mediated GSH-TCE conjugation.

Commercial toxicology prediction systems: a regulatory perspective

The use of commercial toxicity prediction systems in a regulatory setting must consider both the limitations and capabilities of the methods, as well as the ultimate use of the predictions, e.g. for testing prioritization, screening, or supporting regulatory decisions. Current systems are better suited to hazard identification (i.e. positive identification of activity-conferring features) than to ruling out hazard. Two recent examples (an EPA testing prioritization exercise for water disinfection byproducts and a regulatory action on 2,4,6-tribromophenol) illustrate issues involved in regulatory applications of SAR and commercial prediction systems. The challenge for the future will be to improve technologies for prediction within the constraints of available data, make optimal use of new test data, and better integrate elements of quantitative modeling (QSAR), empirical association, and biological and chemical mechanisms towards the goal of toxicity prediction.

Structure-based methods for predicting mutagenicity and carcinogenicity: are we there yet?

There is a great deal of current interest in the use of commercial, automated programs for the prediction of mutagenicity and carcinogenicity based on chemical structure. However, the goal of accurate and reliable toxicity prediction for any chemical, based solely on structural information remains elusive. The toxicity prediction challenge is global in its objective, but limited in its solution, to within local domains of chemicals acting according to similar mechanisms of action in the biological system; to predict, we must be able to generalize based on chemical structure, but the biology fundamentally limits our ability to do so. Available commercial systems for mutagenicity and/or carcinogenicity prediction differ in their specifics, yet most fall in two major categories: (1) automated approaches that rely on the use of statistics for extracting correlations between structure and activity; and (2) knowledge-based expert systems that rely on a set of programmed rules distilled from available knowledge and human expert judgement. These two categories of approaches differ in the ways that they represent, process, and generalize chemical-biological activity information. An application of four commercial systems (TOPKAT, CASE/MULTI-CASE, DEREK, and OncoLogic) to mutagenicity and carcinogenicity prediction for a particular class of chemicals-the haloacetic acids (HAs)-is presented to highlight these differences. Some discussion is devoted to the issue of gauging the relative performance of commercial prediction systems, as well as to the role of prospective prediction exercises in this effort. And finally, an alternative approach that stops short of delivering a prediction to a user, involving structure-searching and data base exploration, is briefly considered.

Quantitative structure-based modeling applied to characterization and prediction of chemical toxicity

Quantitative modeling methods, relating aspects of chemical structure to biological activity, have long been applied to the prediction and characterization of chemical toxicity. The early linear free-energy approaches of Hansch and Free Wilson provided a fundamental scientific framework for the quantitative correlation of chemical structure with biological activity and spurred many developments in the field of quantitative structure-activity relationships (QSARs). In addition to modeling of chemical toxicity, these methods have been extensively applied to modeling of medicinal properties of chemicals. However, there are important differences in the nature and objectives of these two applications, which have led to the evolution of different modeling approaches (namely, the need for treating sets of noncongeneric toxic compounds). In this paper are discussed those approaches to chemical toxicity that have taken a more "personalized" configuration and have undergone implementation into software programs able to perform the various steps of the assessment of the hazard posed by the chemicals. These models focus both on a variety of toxicological endpoints and on key elements of toxicity mechanisms, such as metabolism.

Theoretical evaluation of two plausible routes for bioactivation of S-(1,1-difluoro-2,2-dihaloethyl)-L-cysteine conjugates: thiirane vs thionoacyl fluoride pathway

The selective nephrotoxicity of halogenated alkenes has been attributed to a glutathione (GSH) S-conjugate pathway involving enzymatic hydrolysis to the cysteine S-conjugate and beta-lyase bioactivation to thiolates, which are presumed to give rise to the ultimate mutagenic or cytotoxic reactive species. Studies have shown that the brominated S-(2,2-dihalo-1,1-difluoroethyl)-L-cysteine conjugates are mutagenic in the Ames test, whereas the nonbrominated analogues are nonmutagenic. While careful experimentation has contributed much to current understanding, the ultimate reactive species responsible for the differing mutagenic effects remain unknown. Computational methods were applied to the investigation of two proposed metabolic pathways leading from the thiolate to either a thiirane or thionoacyl fluoride intermediate, both electrophilic species presumed capable of binding to proteins or DNA. Studied were six F-, Cl-, and Br-substituted 2,2-dihalo-1,1-difluoroethane-1-thiolates (2,2-dihalo-DFETs). Pathway preference was determined for each thiolate by comparison of reaction energy profiles and activation energies. At all but the lowest level of ab initio theory, a thionoacyl fluoride pathway was predicted for 2,2-difluoro-DFET, while a thiirane pathway was energetically preferred for the brominated 2,2-dihalo-DFETs. These results offer a clear mechanism-based rationale for distinguishing 2,2-difluoro-DFET from the brominated 2,2-dihalo-DFETs, while the results are less clear for the 2,2-dichloro and 2-chloro-2-fluoro-DFETs, which at the highest level of ab initio treatment had a relatively small energy preference (2.4 kcal/mol) for the thiirane pathway. The predicted clear preference for a thiirane pathway for the brominated 2,2-dihalo-DFETs is not consistent with a recently proposed pathway involving alpha-thiolactone formation through a thionoacyl fluoride intermediate [Finkelstein, M. B., et al. (1995) J. Am. Chem. Soc. 117, 9590-9591], but is supported by results of a recent study providing experimental evidence for thiirane formation from the brominated 2,2-dihalo-DFETs [Finkelstein, M. B., et al. (1996) Chem. Res. Toxicol. 9, 227-231].

Glutathione S-transferase-mediated induction of GC-->AT transitions by halomethanes in Salmonella

Halomethanes are among the most common mutagenic and carcinogenic disinfection by-products present in the volatile/semivolatile fraction of chlorinated drinking water. Recent studies have demonstrated that the mutagenicity of dichloromethane (CH2Cl2) and bromodichloromethane (BrCHCl2) can be mediated by a theta-class glutathione S-transferase (GSTT1-1). These studies used strain RSJ100 of Salmonella, which is a derivative of the base-substitution strain TA1535 (hisG46, rfa, delta uvrB), into which has been cloned the GSTT1-1 gene from rat. In the present report, we have extended these studies by demonstrating that the mutagenicity of two additional brominated trihalomethanes, bromoform (CHBr3) and chlorodibromomethane (CICHBr2), are also mediated by GSTT1-1 in RSJ100. Using a Tedlar bag vaporization technique, the mutagenic potencies (revertants/ppm) for these two compounds as well as the compounds tested previously rank as follows: CHBr3 approximately CICHBr2 > BrCHCl2 approximately CH2Cl2. To explore the mutational mechanism, we determined the mutation spectra of all four halomethanes at the hisG46 allele by performing colony probe hybridizations of approximately 100 revertants induced by each compound. The majority (96-100%) of the mutations were GC-->AT transitions, and 87-100% of these were at the second position of the CCC/GGG target. In contrast, only 15% of mutants induced by CH2Cl2 were GC-->AT transitions in the absence of the GSTT1-1 gene in strain TA100 (a homologue of TA1535 containing the plasmid pKM101). The ability of GSTT1-1 to mediate the mutagenicity of these di- and trihalomethanes and the induction of almost exclusively GC-->AT transitions by these compounds suggest that these halomethanes are activated by similar pathways in RSJ100, possibly through similar reactive intermediates. The implications of these findings are discussed in relation to previous experimental work on the GST-mediated bioactivation of dihalomethanes, which includes the possible formation of GSH intermediates and/or GSH-DNA adducts.

QSARS of mutagens and carcinogens: two case studies illustrating problems in the construction of models for noncongeneric chemicals

There is a strong motivation to develop QSAR models for toxicity prediction for use in screening, for setting testing priorities, and for reducing reliance on animal testing. Decisions must be made daily by toxicologists in governments and industry to direct limited testing to the most urgent public health problems, and to direct the types of chemical synthesis and product development efforts undertaken. This need has motivated attempts to construct general QSAR models (e.g., for rodent carcinogenicity), not tailored to congeneric series of chemicals. These various attempts have provided interesting and important scientific evidence; however, they have also shared a limited overall performance. The goal of this paper is to illustrate, by two unrelated actual examples of QSARs for mutagens and carcinogens, some fundamental problems relative to the application of general QSAR approaches to noncongeneric chemicals. Both examples consider data sets that are noncongeneric in a chemical structure and mechanism of action sense: in the first case, a mean mutagenic potency defined as an average over multiple genetic toxicity endpoints, and, in the second case, the NTP two-sexes, two species rodent carcinogenicity bioassay results for 280 carcinogens and noncarcinogens. The problems encountered with the QSAR analyses of these two cases indicate that a successful approach to the problem of QSAR modeling of noncongeneric data will need to consider the multidimensional nature of the problem in both a chemical and a biological sense. Since different chemical classes represent largely independent action mechanisms, some means for extracting local QSARs for constituent classes will be necessary. Alternatively, a general QSAR derived for a noncongeneric data set will need to be scrutinized and decomposed along chemical class lines in order to establish boundaries for application and confidence levels for prediction.

Quantitative structure-activity relationships for the developmental toxicity of haloacetic acids in mammalian whole embryo culture

Developmental toxicity in mouse whole embryo culture assay has been reported for acetic acid (AA) and a series of ten haloacetic acids, including mono-, di-, tri-fluoro (MFA, DFA, TFA), chloro (MCA, DCA, TCA), bromo (MBA, DBA, TBA), and monoiodo (MIA) acetic acids. Benchmark concentrations (BCm), calculated as the lower 95% confidence limit of molar acid concentration producing a 5% increase in embryos with neural tube defects, provided potency estimates for development of quantitative structure-activity relationships (QSARs). The best overall regression was obtained for the ten halo-acids (excluding AA) and related log (1/BCm) to the energy of the lowest unoccupied molecular orbital (Elumo) and acid dissociation constant (pKa) with a correlation coefficient of r = 0.97, and a sample size-adjusted r2 = 0.92. This QSAR suggested a common basis for the mechanism of HA activity, which would imply additivity for mixtures of these acids. Examination of QSARs for subsets of the total data set (e.g., monohaloacids) highlighted parameter relationships embedded in the total QSAR, helping to unravel the separate contributions of Elumo and pKa to the overall potency. The relevance of these parameters is discussed in terms of postulated mechanisms of developmental toxicity involving changes in intercellular pH and redox metabolism. The whole embryo assay results pertain to direct embryo exposure and toxicity without the confounding influence of maternal factors. The resulting QSAR model offers possible insight into the mechanism of embryo toxicity that will hopefully contribute to understanding of the more complex, in vivo teratogenicity problem.

Conformational aspects of glutathione conjugates of chlorinated alkenes: a computational study

The nephrotoxicity of halogenated alkenes is due to the beta-lyase mediated bioactivation of the hepatic glutathione (GS) conjugate to mutagenic or cytotoxic reactive species in kidney. Experimental evidence obtained for regioisomers and geometric isomers of haloalkene GS conjugates indicates that different isomers may be metabolized and excreted at different rates, follow different metabolic pathways, and exhibit different toxicities. Computational methods were applied in the present work to a conformational study of GS-haloalkene conjugates to determine the relative stabilities of possible regioisomers and geometric isomers of the conjugates. The halogenated alkenes studied were 1,1,2-trichloroethylene (TCE), hexachloro-1,3-butadiene (HCBD), and 1,1,2-trichloro-3,3,3-trifluoro-1-propene (TCTFP). Calculated energies of GS conjugate products were used to approximately infer relative product abundance under synthetic and in vivo conditions. This approach neglects differential solvent effects and enzyme selectivity and assumes a late transition state for GS conjugation and/or some thermodynamic control of the conjugation process. Relative population predictions of GS conjugate isomers, based on computed energies, were in agreement with experimental synthetic and in vivo isomer determinations in the case of TCE, where careful analytical characterization of the isomers was definitive. In the case of HCBD, where analytical determinations were not performed and isomer assignments were based on general reactivity concepts, calculations from the present study supported one GS conjugate isomer assignment and disagreed with the other. Finally, in the case of TCTFP, the calculations predicted that three isomers would have similar populations, whereas only two were detected in the experimental study.

Role of computational chemistry in support of hazard identification (ID): mechanism-based SARs

A mechanism-based structure-activity relationship (SAR) study examines the structural basis for a chemical/biological activity by targeting a single or a few stages in a postulated mechanism of action. Computational chemistry approaches provide a valuable complement to experiment for probing such associations, but require a highly focused viewpoint that neglects much of the full biological and chemical interaction problem. Research questions are formulated in terms of fundamental structure and reactivity properties and are designed to test key assumptions of a postulated mechanism of activity. The results of such studies can aid in the generation of new hypotheses, suggest new experiments, and provide scientific rationale for extrapolation in hazard identification (ID). Toxicologists and computational chemists bring very different, yet complementary viewpoints, approaches, and expertise to bear on the hazard ID problem. However, improved communication and interaction between these two groups is needed to most productively address hazard ID issues.

Synthesis and characterization of adducts of alachlor and 2-chloro-N-(2,6-diethylphenyl)acetamide with 2'-deoxyguanosine, thymidine, and their 3'-monophosphates

Adducts of the preemergence herbicide 2-chloro-N-(methoxymethyl)-N-(2,6-diethylphenyl)-acetamide (alachlor) and 2-chloro-N-(2,6-diethylphenyl)acetamide (CDEPA) with 2'-deoxyguanosine, thymidine, 2'-deoxyguanosine 3'-monophosphate, and thymidine 3'-monophosphate have been synthesized and characterized. Under mildly basic conditions alachlor and CDEPA form N-1 adducts with 2'-deoxyguanosine and N-3 adducts with thymidine as a result of chlorine displacement. In addition, alachlor formed an N-7 adduct with 2'-deoxyguanosine, 7-[[(N-(methoxymethyl)-N-(2,6-diethylphenyl)carbamoyl]methyl]guani ne. N-1 adducts of alachlor and CDEPA with 2'-deoxyguanosine 3'-monophosphate and N-3 adducts with thymidine 3'-monophosphate are also described. In addition to spectroscopic data, structural proof included the dephosphorylation of each nucleotide adduct to its corresponding nucleoside adduct by nuclease P1. Alachlor and alachlor adducts but not CDEPA and CDEPA adducts exhibited rotational isomerism as evidenced by proton and 13C NMR studies. These rotamers were attributed to hindered rotation about the shortened N-carbonyl bond. Computational methods employing molecular mechanics and quantum mechanics were used to characterize the structures and energies of these rotamers to account for the patterns of duplicate NMR resonances observed.

International Commission for Protection Against Environmental Mutagens and Carcinogens. Application of SAR methods to non-congeneric data bases associated with carcinogenicity and mutagenicity: issues and approaches

In both industry and government, structure-activity relationships (SAR) are capable of playing an important decision-support role in estimating the potential mutagenicity or carcinogenicity of chemicals for which bioassay test results are unavailable. Traditional SAR modeling approaches, however, are usually restricted to the consideration of structurally similar chemical congeners. The highly structurally diverse nature of current carcinogenicity and mutagenicity data bases has motivated development of more general SAR approaches, potentially applicable to the treatment of diverse, non-congeneric mutagenicity and carcinogenicity data bases. Three specific approaches are considered in some detail--Ashby's structural alerts model, classified as a "rule-based" SAR approach, and the computerized CASE fragment-based method and TOPKAT linear discriminant equation method, both classified as "correlative" SAR approaches. Relative strengths and limitations, and a number of common features and important distinctions between these 3 methods are discussed. Rule-base methods are highly flexible and able to incorporate many different types of relevant information, yet are biased towards current knowledge, viewpoints, and mechanistic assumptions, that may or may not hold true. Correlative SAR methods are less biased and offer the promise of "discovering" potentially new SAR associations that could lend fresh insight into the basis for a structure-activity association. However, problems associated with their application to non-congeneric data bases relate to: modeling multiple or overlapping mechanisms of action with a single relationship; defining the range of applicability of models in complex multi-dimensional structure-activity space; assigning confidence levels to predictions in the absence of knowledge concerning mechanisms of activity; and determining the potential mechanistic significance of diverse model parameters. It is argued that many of these concerns can be partially alleviated by careful application of statistical procedures, scrutiny of model results, and establishment of reasoned limits to the range of model applicability. The most significant confidence-building measure, however, will be a rationalization of the correlative SAR model and model parameters in terms of principles of chemical reactivity and postulated molecular mechanism(s) for the biological activity. Hence, it is recommended that models and model descriptors be designed to facilitate mechanistic interpretation and hypothesis generation. Finally, problems in comparing the relative predictive capabilities of different SAR approaches are discussed, and strategies for SAR investigation involving integration of existing techniques are suggested.

Structure-activity study of paracetamol analogues: inhibition of replicative DNA synthesis in V79 Chinese hamster cells

Experimental and theoretical evidence pertaining to cytotoxic and genotoxic activity of paracetamol in biological systems was used to formulate a simple mechanistic hypothesis to explain the relative inhibition of replicative DNA synthesis by a series of 19 structurally similar paracetamol analogues, 5 of which were specifically analyzed for the current study. It was hypothesized that the observed activity variation of the paracetamol analogues was based on the relative abilities of these compounds to undergo H atom loss at the phenolic oxygen, and on the relative stabilities of the resulting free-radical species. Three calculated parameters were found to be relevant--the partial atomic charge on the ring carbon attached to the phenolic oxygen, the partial charge on the phenoxy radical oxygen, and the energy difference between the parent phenolic paracetamol analogue and the corresponding radical dissociation products. The variation in parameter values was significantly correlated with the relative inhibition of DNA synthesis and was easily rationalized in terms of the mechanistic hypothesis proposed. More specifically, competitive reaction with a tyrosyl radical species involving the transfer of a hydrogen atom at the active site of ribonucleotide reductase was suggested as the underlying mechanistic basis for the observed activity variation of the paracetamol analogues. Comparison of calculated parameters for a model tyrosyl species and the paracetamol analogues was entirely consistent with this view.

A CASE-SAR analysis of polycyclic aromatic hydrocarbon carcinogenicity

A CASE SAR analysis was performed on a selected database of PAHs to investigate the possible use of the CASE method as an aid for preliminary assessment of carcinogenic potential of untested environmental PAHs. A data set, denoted LEARN, consisting of 78 PAHs and their experimental carcinogenicities was used to 'train' the CASE method and derive the CASE fragments. 8 activating fragments and 4 inactivating fragments were identified. These fragments predicted the activities of 94% of the LEARN set correctly. The biological significance of several of these fragments are rationalized in light of the current theories of PAH carcinogenesis. Using these fragments, the potential activities of a database of 106, mostly untested PAHs, denoted TEST, were predicted. These were compared to 'expert judgement' predictions based on mechanistic considerations in order to evaluate the extent of concordance between these two methods and their respective strengths and weaknesses. Initial poor agreement (64%) was attributed to limitations of the LEARN database involving inadequate representation of 2- and 3-ring PAH subclasses. When these subclasses were excluded from the TEST database, the concordance improved to 90%. The CASE fragments were also used to predict the activities of a database of 24 PAHs, denoted VALIDATE (not included in the LEARN set) for which carcinogenicity data were available. The total prediction accuracy of 75% (89% of the actives correctly identified), despite the structural diversity of the VALIDATE set, provided independent evidence of the utility of the present CASE results. A close examination of the CASE incorrect predictions was conducted to delineate inadequancies of these CASE results in order to provide cautionary guidance for future application of the method. Finally, the present results were compared to the results of a previous CASE analysis based on a more limited PAH data set, and were found to be of greater general utility. It is concluded that the CASE fragments derived in the current study should provide a useful tool for assisting and complementing 'expert judgement' in the preliminary screening of PAHs for carcinogenic activity.

Strategies for the use of computational SAR methods in assessing genotoxicity

The relationship between computational SAR studies and relevant data gathering and generation activities is complex. First, the chemical class to be studied is selected on the basis of information requirements for hazard identification and assessment. Membership in the class is determined by consideration of chemical structure and reactivity. Compilation of the existing bioassay data for this chemical class follows immediately from the specification of the class. Bioassay data, qualitative knowledge of general chemical reactivities in this class, and knowledge concerning potential interactions with biomolecular targets all contribute to the derivation of possible mechanisms for biological activity. Computational studies based on modeling the proposed mechanism of action and/or the existing data base can provide a quantitative basis for the differentiation between chemicals. There is the opportunity for continuing feedback between the quantitative computational studies and the development of a relevant bioassay data base for this chemical class. The qualitative and quantitative information on the potential biological responses obtained will provide a rational basis for extrapolation from the extant data base to the chemicals of interest, and to biological responses significant to the assessment for which complete data are unavailable. Knowledge concerning possible mechanisms of action and preexisting data determine the type of computational study that will be most useful.