The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the Gene-Tox data base

The CASE structure-activity methodology has been applied to a Gene-Tox derived Salmonella mutagenicity data base consisting of 808 chemicals. Based upon qualitative structural features, CASE identified 29 activating and 3 inactivating structural determinants which correctly predicted the probability of carcinogenicity of 93.7% of the known mutagens and non-mutagens in the data base (sensitivity = 0.998, and specificity = 0.704). Additionally, based upon a qualitative structure-activity analysis, CASE's performance was even better, leading to a sensitivity of 0.981 and a specificity of 1.000. Using the structural determinants identified in this data base, CASE gave excellent predictions of the mutagenicity of chemicals not included in the data base. The identified biophores and biophobes can also be used to investigate the structural basis of the mutagenicity of various chemical classes.     

Testing by artificial intelligence: computational alternatives to the determination of mutagenicity.

In order to develop methods for evaluating the predictive performance of computer-driven structure-activity methods (SAR) as well as to determine the limits of predictivity, we investigated the behavior of two Salmonella mutagenicity data bases: (a) a subset from the Genetox Program and (b) one from the U.S. National Toxicology Program (NTP). For molecules common to the two data bases, the experimental concordance was 76% when "marginals" were included and 81% when they were excluded. Three SAR methods were evaluated: CASE, MULTICASE and CASE/Graph Indices (CASE/GI). The programs "learned" the Genetox data base and used it to predict NTP molecules that were not present in the Genetox compilation. The concordances were 72, 80 and 47% respectively. Obviously, the MULTICASE version is superior and approaches the 85% interlaboratory variability observed for the Salmonella mutagenicity assays when the latter was carried out under carefully controlled conditions.     

Classification according to chemical structure, mutagenicity to Salmonella and level of carcinogenicity of a further 42 chemicals tested for carcinogenicity by the U.S. National Toxicology Program

This paper is an extension and update of an earlier review published in this journal (Ashby and Tennant, 1988). A summary of the rodent carcinogenicity bioassay data on a further 42 chemicals tested by the U.S. National Toxicology Program (NTP) is presented. An evaluation of each chemical for structural alerts to DNA-reactivity is also provided, together with a summary of its mutagenicity to Salmonella. The 42 chemicals were numbered and evaluated as an extension of the earlier analysis of 222 NTP chemicals. The activity patterns and conclusions derived from the earlier study remain unchanged for the larger group of 264 chemicals. Based on the extended database of 264 NTP chemicals, the sensitivity of the Salmonella assay for rodent carcinogens is 58% and the specificity for the non-carcinogens is 73%. A total of 32 chemicals were defined as equivocal for carcinogenicity and, of these, 11 (34%) are mutagenic to Salmonella. An evaluation is made of instances where predictions of carcinogenicity, based on structural alerts, disagree with the Salmonella mutagenicity result (12% of the database). The majority of the disagreements are for structural alerts on non-mutagens, and that places these alerts as a sensitive primary screen with a specificity lower than that of the Salmonella assay. That analysis indicates some need for assays complementary to the Salmonella test when screening for potential genotoxic carcinogens. It also reveals that the correlation between structural alerts and mutagenicity to Salmonella is probably greater than 90%. Chemicals predicted to show Michael-type alkylating activity (i.e., CH2 = CHX; where X = an electron-withdrawing group, e.g. acrylamide) have been confirmed as a structural alert, and the halomethanes (624 are possible) have been classified as structurally-alerting. To this end an extended carcinogen-alert model structure is presented. Among the 138 NTP carcinogens now reviewed, 45 (33%) are non-mutagenic to Salmonella and possess a chemical structure that does not alert to DNA-reactivity. These carcinogens therefore either illustrate the need for complementary genetic screening tests to the Salmonella assay, or they represent the group of non-genotoxic carcinogens referred to most specifically by Weisburger and Williams (1981); the latter concept is favoured.     

Structural requirements for the induction of the SOS repair in bacteria by nitrated polycyclic aromatic hydrocarbons and related chemicals.

The CASE (computer-automated structure evaluation) methodology was used to investigate the structural basis of the SOS-inducing activity of 56 nitrated polycyclic aromatic hydrocarbons (nitroarenes, nPAH) and the unsubstituted parent PAH molecules. Based upon the presence and/or absence of structural features, CASE identified 5 activating (biophores) and 4 inactivating (biophobes) fragments responsible for the SOS-inducing activity. Based upon these fragments, CASE correctly calculated the genotoxicity of 94.6% of the molecules in the training set (sensitivity = 0.85, specificity = 1.0). Disregarding the questionable experimental results of the unexpected very weak direct-acting activity of the unsubstituted benzo[a]pyrene, dibenzo[a,h]anthracene and 7,12-dimethylbenz[a]anthracene, the concordance of the prediction was 100%, i.e., sensitivity = 1.0, specificity = 1.0. Additionally, the quantitative analysis of the SOS-inducing potency showed a good correlation between the experimental and predicted results. The present analyses indicate an identity in the structural determinants responsible for SOS induction in E. coli PQ37 (SOS chromotest) and mutagenicity in Salmonella typhimurium.     

Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP.

An analysis is presented in which are evaluated correlations among chemical structure, mutagenicity to Salmonella, and carcinogenicity to rats and mice among 301 chemicals tested by the U.S. NTP. Overall, there was a high correlation between structural alerts to DNA reactivity and mutagenicity, but the correlation of either property with carcinogenicity was low. If rodent carcinogenicity is regarded as a singular property of chemicals, then neither structural alerts nor mutagenicity to Salmonella are effective in its prediction. Given this, the database was fragmented and new correlations sought between the derived sub-groups. First, the 301 chemicals were segregated into six broad chemical groupings. Second, the rodent cancer data were partially segregated by target tissue. Using the previously assigned structural alerts to DNA reactivity (electrophilicity), the chemicals were split into 154 alerting chemicals and 147 non-alerting chemicals. The alerting chemicals were split into three chemical groups; aromatic amino/nitro-types, alkylating agents and miscellaneous structurally-alerting groups. The non-alerting chemicals were subjectively split into three broad categories; non-alerting, non-alerting containing a non-reactive halogen group, and non-alerting chemical with minor concerns about a possible structural alert. The tumor data for all 301 chemicals are re-presented according to these six chemical groupings. The most significant findings to emerge from comparisons among these six groups of chemicals were as follows: (a) Most of the rodent carcinogens, including most of the 2-species and/or multiple site carcinogens, were among the structurally alerting chemicals. (b) Most of the structurally alerting chemicals were mutagenic; 84% of the carcinogens and 66% of the non-carcinogens. 100% of the 33 aromatic amino/nitro-type 2-species carcinogens were mutagenic. Thus, for structurally alerting chemicals, the Salmonella assay showed high sensitivity and low specificity (0.84 and 0.33, respectively). (c) Among the 147 non-alerting chemicals less than 5% were mutagenic, whether they were carcinogens or non-carcinogens (sensitivity 0.04).     

Structural basis of carcinogenicity in rodents of genotoxicants and non-genotoxicants

A set of 189 chemicals tested in the National Toxicology Program Cancer Bioassay was subjected to analysis by CASE, the Computer-Automated Structure Evaluation system. In the data set, 63% of the chemicals were carcinogens, approx. 40% of the carcinogens were non-genotoxic, i.e., they possessed neither "structural alerts" for DNA reactivity as defined by Ashby and Tennant, 1988, nor were they mutagenic for Salmonella. The data base can be characterized as a "combined rodent" compilation as chemicals were characterized as "carcinogenic" if they were carcinogenic in either rats or mice or both. CASE identified 23 fragments which accounted for the carcinogenicity, or lack thereof, of most of the chemicals. The sensitivity and specificity were unexpectedly high: 1.00 and 0.86, respectively. Based upon the identified biophores and biophobes, CASE performed exceedingly well in predicting the activity of chemicals not included among the 189 in the original set. CASE predicted correctly the carcinogenicity of non-genotoxic carcinogens thereby suggesting a structural commonality in the action of this group of carcinogens. As a matter of fact biophores restricted to non-genotoxic carcinogens were identified as were "non-electrophilic" biophores shared by genotoxic and non-genotoxic carcinogens. The findings suggest that the CASE program may help in the elucidation of the basis of the action of non-genotoxic carcinogens.     

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.     

Classification according to chemical structure, mutagenicity to Salmonella and level of carcinogenicity of a further 39 chemicals tested for carcinogenicity by the U.S. National Toxicology Program

This paper is an extension of compilations published previously in this journal. (Ashby and Tennant, 1988; Ashby et al., 1989). A summary of the rodent carcinogenicity bioassay data on a further 39 chemicals tested by the U.S. National Toxicology Program (NTP) is presented. An evaluation of each chemical for structural alerts to DNA-reactivity is also provided, together with a summary of its mutagenicity to Salmonella. Chemicals with an aliphatic nitro group (-C-NO2) have been added to the composite structure of DNA-reactive sub-groups. The 39 chemicals were numbered and evaluated as an extension of the earlier analysis of 264 NTP chemicals. The activity patterns and conclusions derived from the earlier studies are followed by these 39 chemicals, albeit a detailed analysis of the total database of 301 chemicals is reserved for the succeeding paper.     

In silico assessment of chemical mutagenesis in comparison with results of Salmonella microsome assay on 909 chemicals

Genotoxicity is one of the important endpoints for risk assessment of environmental chemicals. Many short-term assays to evaluate genotoxicity have been developed and some of them are being used routinely. Although these assays can generally be completed within a short period, their throughput is not sufficient to assess the huge number of chemicals, which exist in our living environment without information on their safety. We have evaluated three commercially available in silico systems, i.e., DEREK, MultiCASE, and ADMEWorks, to assess chemical genotoxicity. We applied these systems to the 703 chemicals that had been evaluated by the Salmonella/microsome assay from CGX database published by Kirkland et al. We also applied these systems to the 206 existing chemicals in Japan that were recently evaluated using the Salmonella/microsome assay under GLP compliance (ECJ database). Sensitivity (the proportion of the positive in Salmonella/microsome assay correctly identified by the in silico system), specificity (the proportion of the negative in Salmonella/microsome assay correctly identified) and concordance (the proportion of correct identifications of the positive and the negative in Salmonella/microsome assay) were increased when we combined the three in silico systems to make a final decision in mutagenicity, and accordingly we concluded that in silico evaluation could be optimized by combining the evaluations from different systems. We also investigated whether there was any correlation between the Salmonella/microsome assay result and the molecular weight of the chemicals: high molecular weight (>3000) chemicals tended to give negative results. We propose a decision tree to assess chemical genotoxicity using a combination of the three in silico systems after pre-selection according to their molecular weight.     

Structural basis of the in vivo induction of micronuclei.

The structural basis of the in vivo induction of micronuclei was examined with CASE, a structure-activity relational method. The CASE program identified a number of structures associated with this activity. When used to predict the activity of chemicals not included in the learning set, these structural determinants gave a concordance in excess of 83%. The existence of a structural basis for the induction of micronuclei will permit an investigation of the mechanistic basis of this phenomenon.     

What indication is common to different genotoxicity data bases?

This paper studies the relationships among 4 in vitro assays: Salmonella mutation (STY), mouse lymphoma L5178Y cell mutation (MLY), chromosomal aberrations in CHO cells (CHA), and sister-chromatid exchanges in CHO cells (SCE), in 3 different data bases: U.S. National Toxicology Program (NTP), International Program for the Evaluation of Short-Term Tests for Carcinogens (IPESTTC), and International Program on Chemical Safety (IPCS). The analysis is performed by modeling each data base with factor analysis. With this tool, it has been possible to separate the different elements (or components) which play a role in each data base. It has also been possible to demonstrate that--together with some specificities of the data bases--there is a common effect which is independent of the data bases, and which typically represents the 'true' relationships among the assays. This element explains 69% of the information contained in NTP, 50% of that of IPESTTC, and 30% of that of IPCS. This common evidence indicates that the responses of STY and CHA to the 'universe' of chemicals are relatively similar, although STY is a bacterial mutation system and CHA is a mammalian cell test for chromosomal damage. The other similarity apparent from this analysis is the one between MLY (mutation in mouse cells) and SCE (cytogenetic evidence in hamster cells). The implication of this result is 2-fold. On the one hand, it is extremely reassuring that the 3 most important comparative studies agree and show common evidence, and this can be recognized rationally. On the other hand, this evidence implies that the scientists involved in mutagenicity research must face the task of exploring and explaining such relationships.     

Use of a composite polyfunctional model electrophile as a probe to analyze the performance of an artificial intelligence structure-activity method

The CASE structure-activity relational method was applied to the model polyfunctional electrophile proposed by Ashby and associates. The predicted activities from data bases of 'structural alerts', mutagenicity in Salmonella and rodent carcinogenicity were compared. It was thus found that the predictive efficacy of CASE was increased when it employed a combination of human and artificial intelligence, as exemplified by the CASE analysis of 'structural alerts.     

CASE, the computer-automated structure evaluation method, correctly predicts the low mutagenicity for Salmonella of nitrated cyclopenta-fused polycyclic aromatic hydrocarbons

Recently Goldring et al. [Mutation Res., 187 (1987) 67-77] reported the synthesis and purification of a series of nitro-substituted cyclopenta-fused polycyclic aromatic hydrocarbons. On the basis of expected charge distributions, these chemicals were predicted to be potent mutagens and, yet, contrary to expectation, they were found to be only weakly mutagenic for Salmonella. In their discussion, the authors suggest that application of CASE, an artificial intelligence system recently developed in these laboratories, would also not predict the low mutagenicity of this group of chemicals. In the present report, it is shown that CASE, in fact, correctly predicts the low mutagenicity of nitro-substituted cyclopenta-fused polycyclic aromatic hydrocarbons.     

Structural requirements for the mutagenicity of environmental nitroarenes

The nitroarenes comprise a large group of widely distributed environmental agents some of which are extraordinarily mutagenic while others are devoid of such activity. A newly developed computer program has been used to determine which structural features of these molecules might account for this broad spectrum of activities. Using Salmonella mutagenicity data for 53 nitroarenes, 2 fragments associated with activity and 2 deactivating fragments have been identified. The coexistence of an active and a deactivating fragment on the same molecule results in a nitroarene possessing marginal or no mutagenicity. The activity of 47 of 53 nitroarenes was correctly predicted by this procedure. Most of the discrepancies involved hexa- and heptacyclic nitroarenes which were predicted to be active but reported to be inactive. The ‘CASE’ program can be used to predict the mutagenicity of the many untested nitroarenes identified in the ambient environment.     

An illusion of hormesis in the Ames test: statistical significance is not equivalent to biological significance

A recent report (Calabrese et al., Mutat. Res. 726 (2011) 91-97) concluded that an analysis of Ames test mutagenicity data provides evidence of hormesis in mutagenicity dose-response relationships. An examination of the data used in this study and the conclusions regarding hormesis reveal a number of concerns regarding the analyses and possible misinterpretations of the Salmonella data. The claim of hormesis is based on test data from the National Toxicology Program using Salmonella strain TA100. Approximately half of the chemicals regarded as hormetic, and the majority of the specific dose-responses identified as hormetic, were actually nonmutagenic. We conclude that the data provide no evidence of hormetic effects. The Ames test is an excellent measure of bacterial mutagenicity, but the numbers of revertant (mutant) colonies on the plate are the result of a complex interaction between mutagenicity and toxicity, which renders the test inappropriate for demonstrating hormesis in bacterial mutagenicity experiments.     

Herpes simplex virus 1 primase employs watson-crick hydrogen bonding to identify cognate nucleoside triphosphates

We utilized NTP analogues containing modified bases to probe the mechanism of NTP selection by the primase activity of the herpes simplex virus 1 helicase-primase complex. Primase readily bound NTP analogues of varying base shape, hydrophobicity, and hydrogen-bonding capacity. Remarkably, primase strongly discriminated against incorporating virtually all of the analogues, even though this enzyme misincorporates natural NTPs at frequencies as high as 1 in 7. This included analogues with bases much more hydrophobic than a natural base (e.g., 4- and 7-trifluoromethylbenzimidazole), a base of similar hydrophobicity as a natural base but with the Watson-Crick hydrogen-bonding groups in unusual positions (7-beta-d-guanine), bases shaped almost identically to the natural bases (4-aminobenzimidazole and 4,6-difluorobenzimidazole), bases shaped very differently than a natural base (e.g., 5- and 6-trifluoromethylbenzimidazole), and bases capable of forming just one Watson-Crick hydrogen bond with the template base (purine and 4-aminobenzimidazole). The only analogues that primase readily polymerized into primers (ITP and 3-deaza-ATP) were those capable of forming Watson-Crick hydrogen bonds with the template base. Thus, herpes primase appears to require the formation of Watson-Crick hydrogen bonds in order to efficiently polymerize a NTP. In contrast to primase's narrow specificity for NTP analogues, the DNA-dependent NTPase activity associated with the herpes primase-helicase complex exhibited very little specificity with respect to NTPs containing unnatural bases. The implications of these results with respect to the mechanism of the helicase-primase and current fidelity models are discussed.     

Study of the causes of direct-acting mutagenicity in coffee and tea using the Ara test in Salmonella typhimurium

The mutagenic activities of 6 of the chemicals identified in coffee solutions were assayed with the Salmonella Ara test, under experimental conditions optimized for coffee mutagenicity. Caffeine was the only non-mutagenic compound. Among the other 5 chemicals, hydrogen peroxide was the strongest mutagen and chlorogenic acid the weakest; methylglyoxal, glyoxal and caffeic acid exhibited intermediate mutagenicities. The minimal mutagenic doses of these components correlated negatively with their relative concentrations in coffee. It was concluded that chlorogenic acid, caffeic acid, glyoxal and methylglyoxal cannot contribute alone to the mutagenicity of coffee in the Ara test, since their minimal mutagenic concentrations were much higher than their respective levels in the coffee samples assayed. By contrast, 40-60% of the mutagenic activity in coffee and also in tea could be attributed to their H2O2 contents. Catalase abolished more than 95% of the mutagenic activity of coffee, as detected by the Ara test. A similar sensitivity to catalase has been reported by other authors in relation to the coffee mutagenicity identified by the Salmonella His test. Nevertheless, the results presented in this paper suggest that the Ara forward and the His reverse mutation tests are sensitive to the mutagenicity of different constituents in coffee solutions. We propose that the His test, sensitive at high coffee doses, mainly recognizes the mutagenicity of methylglyoxal, whilst the Ara test, sensitive at low coffee doses, mainly detects the mutagenic activity of hydrogen peroxide. The data reported also suggest that the direct-acting mutagenicity(ies) detected by the Ara test in tea solutions is (are) based on similar, if not identical, mechanisms.     

In silico assessment of chemical mutagenesis in comparison with results of Salmonella microsome assay on 909 chemicals

Genotoxicity is one of the important endpoints for risk assessment of environmental chemicals. Many short-term assays to evaluate genotoxicity have been developed and some of them are being used routinely. Although these assays can generally be completed within a short period, their throughput is not sufficient to assess the huge number of chemicals, which exist in our living environment without information on their safety. We have evaluated three commercially available in silico systems, i.e., DEREK, MultiCASE, and ADMEWorks, to assess chemical genotoxicity. We applied these systems to the 703 chemicals that had been evaluated by the Salmonella/microsome assay from CGX database published by Kirkland et al. [1]. We also applied these systems to the 206 existing chemicals in Japan that were recently evaluated using the Salmonella/microsome assay under GLP compliance (ECJ database). Sensitivity (the proportion of the positive in Salmonella/microsome assay correctly identified by the in silico system), specificity (the proportion of the negative in Salmonella/microsome assay correctly identified) and concordance (the proportion of correct identifications of the positive and the negative in Salmonella/microsome assay) were increased when we combined the three in silico systems to make a final decision in mutagenicity, and accordingly we concluded that in silico evaluation could be optimized by combining the evaluations from different systems. We also investigated whether there was any correlation between the Salmonella/microsome assay result and the molecular weight of the chemicals: high molecular weight (>3000) chemicals tended to give negative results. We propose a decision tree to assess chemical genotoxicity using a combination of the three in silico systems after pre-selection according to their molecular weight.     

Thalidomide and metabolites: indications of the absence of 'genotoxic' carcinogenic potentials

Because of the reintroduction into human therapeutics of thalidomide, a recognized developmental toxicant in humans, there has been concern about its potential for inducing other health effects as well. The present study is concerned with the possible mutagenicity and carcinogenicity of this chemical. Using the expert system, META, a series of putative metabolites of thalidomide was generated. In addition to the known or hypothesized metabolites of thalidomide (N=12), a number of additional putative metabolites (N=131) were identified by META. The structures of these chemicals were subjected to structure-activity analyses using predictive CASE/MULTICASE models of developmental toxicity, rodent carcinogenicity and mutagenicity in Salmonella. While thalidomide and some of its putative metabolites were predicted to be developmental toxicants, none of them were predicted to be rodent carcinogens. Putative metabolites containing the hydroxamic acid or hydroxylamine moieties were predicted to be mutagens. None of the 'known' metabolites of thalidomide contained these reactive moieties. Whether such intermediates are indeed generated or whether they are generated and are either unstable in the presence of oxygen or react rapidly with nucleophiles is unknown.