In-silico screening of high production volume chemicals for mutagenicity using the MCASE QSAR expert system

Computational screening is suggested as a way to set priorities for further testing of high production volume (HPV) chemicals for mutagenicity and other toxic endpoints. Results are presented for batch screening of 2484 HPV chemicals to predict their mutagenicity in Salmonella typhimurium (Ames test). The chemicals were tested against 15 databases for Salmonella strains TA100, TA1535, TA1537, TA97 and TA98, both with metabolic activation (using rat liver and hamster liver S9 mix test) and without metabolic activation. Of the 2484 chemicals, 1868 are predicted to be completely nonmutagenic in all of the 15 data modules and 39 chemicals were found to contain structural fragments outside the knowledge of the expert system and therefore suggested for further evaluation. The remaining 616 chemicals were found to contain different biophores (structural alerts) believed to be linked to mutagenicity. The chemicals were ranked indescending order according to their predicted mutagenic potential and the first 100 chemicals with highest mutagenicity scores are presented. The screening result offers hope that rapid and inexpensive computational methods can aid in prioritizing the testing of HPV chemicals, save time and animals and help to avoid needless expense.     

Metabolic activation of chemicals: in-silico simulation†

The role of metabolism in prioritising chemicals according to their potential adverse health effects is extremely important given the fact that innocuous parents can be transformed into toxic metabolites. Our recent efforts in simulating metabolic activation of chemicals are reviewed in this work. The application of metabolic simulators to predict biodegradation (microbial degradation pathways), bioaccumulation (fish liver metabolism), skin sensitisation (skin metabolism), mutagenicity (rat liver S-9 metabolism) are discussed. The ability of OASIS approach to predict metabolism (toxicokinetics) and toxicity (toxicodynamics) of chemicals resulting from their metabolic activation in a single modelling platform is an important advantage of the method. It allows prioritisation of chemicals due to predicted toxicity of their metabolites.

     

Mutagenicity of silver nanoparticles synthesized with curcumin (Cur-AgNPs)

IntroductionSilver nanoparticles (AgNPs) are of particular interest for their antibacterial properties and are produced by the action of reducing agents on silver ions. Curcumin from Curcuma longa (Zingiberaceae) has been used as a precursor for obtaining biogenic AgNPs, to act as a potential drug.ObjectivesThis study aimed to evaluate the toxicity of AgNPs synthesized with curcumin (Cur-AgNPs 0.081 mg/mL, ~130 nm) through the Salmonella/microsome (Ames test), one of the first required assays for evaluating toxicity.MethodsThe study design was experimental and in vitro. After defining the preliminary toxicity, the mutagenicity was assessed in a concentration range of 0.0010–0.0081 mg/plate Cur-AgNPs using histidine negative (His−) Salmonella Typhimurium strains TA97a, TA98, TA100, and TA102, with (+S9) and without metabolic activation (−S9), in triplicate. Assays were monitored by positive and negative controls. The results were statistically analyzed by Salanal software with p < 0.05 values considered significant.ResultsThe data obtained in the absence of metabolic activation showed that Cur-AgNPs is not mutagenic, but when exposed to the presence of S9, Cur-AgNPs became mutagenic to TA98 and TA100 strains, showing the significance of metabolizer enzymes to activate Cur-AgNPs on these bacteria, which recovered their abilities in synthesizing histidine (His+).ConclusionCur-AgNPs is mutagenic in the presence (+S9), but not in the absence (−S9) of metabolic activation, being able to act as indirect mutagens potentially to organisms that share the same genotype vulnerabilities found in TA98 and TA100 strains to cause a frameshift and base-pair substitution mutations, respectively.     

Comparison of CoMFA Models for Salmonella Typhimurium TA98, TA100+TA98+S9 and TA100+S9 Mutagenicity of Nitroaromatics

Abstract

Comparative Molecular Field Analysis (CoMFA) was applied to a comprehensive data set of heterogeneous nitroaromatics tested in Salmonella typhimurium TA98 and TA100 with and without S9 microsomal activation. The four CoMFA models developed agree with postulated mechanisms of mutagenicity, and explain over 70% of the corresponding mutagenic variance. The standard deviation coefficient contours common in the four models included high electronic density regions equivalent to C4-C5 in the pyrene ring, and an electron deficient site equivalent to C6. These areas are associated with high mutagenicity. Electron deficient areas may be related with the nitroreductive bioactivation of nitroaromatics. Electron rich sites may be involved with oxidative mechanisms analogous to the bioactivation pathway of polycyclic aromatic hydrocarbons. The contribution of steric factors to mutagenicity follows the order TA98 + S9 > TA98 > TA100 + S9 > TA100. The models indicated that increasing bulk perpendicular to the aromatic plane would decrease mutagenicity, but increasing the aromatic ring system along a region corresponding to C6-C7 in 1-nitropyrene would increase mutagenicity.     

Mutagenicity of flavonoids assayed by bacterial reverse mutation (Ames) test

The mutagenicity of ten flavonoids was assayed by the Ames test, in Salmonella typhimurium strains TA98, TA100 and TA102, with the aim of establishing hydroxylation pattern-mutagenicity relationship profiles. The compounds assessed were: quercetin, kaempferol, luteolin, fisetin, chrysin, galangin, flavone, 3-hydroxyflavone, 5-hydroxyflavone and 7-hydroxyflavone. In the Ames assay, quercetin acted directly and its mutagenicity increased with metabolic activation. In the presence of S9 mix, kaempferol and galangin were mutagenic in the TA98 strain and kaempferol showed signs of mutagenicity in the other strains. The absence of hydroxyl groups, as in flavone, only signs of mutagenicity were shown in strain TA102, after metabolization and, among monohydroxylated flavones (3-hydroxyflavone, 5-hydroxyflavone and 7-hydroxyflavone), the presence of hydroxyl groups only resulted in minor changes. Luteolin and fisetin also showed signs of mutagenicity in strain TA102. Finally, chrysin, which has only two hydroxy groups, at the 5-OH and 7-OH positions, also did not induce mutagenic activity in any of the bacterial strains used, under either activation condition. All the flavonoids were tested at concentrations varying from 2.6 to 30.7 nmol/plate for galangin and 12.1 to 225.0 nmol/plate for other flavonoids. In light of the above, it is necessary to clarify the conditions and the mechanisms that mediate the biological effects of flavonoids before treating them as therapeutical agents, since some compounds can be biotransformed into more genotoxic products; as is the case for galangin, kaempferol and quercetin.     

Metabolic activation of chemicals: in-silico simulation

The role of metabolism in prioritising chemicals according to their potential adverse health effects is extremely important given the fact that innocuous parents can be transformed into toxic metabolites. Our recent efforts in simulating metabolic activation of chemicals are reviewed in this work. The application of metabolic simulators to predict biodegradation (microbial degradation pathways), bioaccumulation (fish liver metabolism), skin sensitisation (skin metabolism), mutagenicity (rat liver S-9 metabolism) are discussed. The ability of OASIS approach to predict metabolism (toxicokinetics) and toxicity (toxicodynamics) of chemicals resulting from their metabolic activation in a single modelling platform is an important advantage of the method. It allows prioritisation of chemicals due to predicted toxicity of their metabolites.     

A Novel Method for Mutagenicity Test of Carcinogen by using a Series Piezoelectric Quartz Crystal Bactrial Growth Sensor

ABSTRACT

A new method for mutagenicity testing of carcinogens is proposed in this paper. Mutagenic activity is examined through monitoring of the growth situation of Salmonella typhimurium TA98 strain with a series piezoelectric quartz crystal (SPQC) sensor. This method needs no immobilization and preincubation of microorganism, and is simple and rapid. It can be applied to detect mutagen directly. When it was used to study the mutagenicity of dimethyl sulfate, the test time was 4 h at 37°C. There was a good linear relationship between frequency shift and the dose of mutagen in the range 2.5-20 μg/mL and the regression equation was ∠F = 53.82 + 3.81C. Some experimental conditions are also discussed in detail.     

In silico exploratory study using structure–activity relationship models and metabolic information for prediction of mutagenicity based on the Ames test and rodent micronucleus assay

The mutagenic potential of chemicals is a cause of growing concern, due to the possible impact on human health. In this paper we have developed a knowledge-based approach, combining information from structure–activity relationship (SAR) and metabolic triggers generated from the metabolic fate of chemicals in biological systems for prediction of mutagenicity in vitro based on the Ames test and in vivo based on the rodent micronucleus assay. In the first part of the work, a model was developed, which comprises newly generated SAR rules and a set of metabolic triggers. These SAR rules and metabolic triggers were further externally validated to predict mutagenicity in vitro, with metabolic triggers being used only to predict mutagenicity of chemicals, which were predicted unknown, by SARpy. Hence, this model has a higher accuracy than the SAR model, with an accuracy of 89% for the training set and 75% for the external validation set. Subsequently, the results of the second part of this work enlist a set of metabolic triggers for prediction of mutagenicity in vivo, based on the rodent micronucleus assay. Finally, the results of the third part enlist a list of metabolic triggers to find similarities and differences in the mutagenic response of chemicals in vitro and in vivo.     

An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

Recent legislation mandates the US Environmental Protection Agency (EPA) to develop a screening and testing program for potential endocrine disrupting chemicals (EDCs), of which xenoestrogens figure prominently. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need for priority setting before this strategy can be effectively implemented. Here we report an integrated computational approach to priority setting using estrogen receptor (ER) binding as an example. This approach rationally integrates different predictive computational models into a "Four-Phase" scheme so that it can effectively identify potential estrogenic EDCs based on their predicted ER relative binding affinity (RBA). The system has been validated using an in-house ER binding assay dataset for 232 chemicals that was designed to have both broad structural diversity and a wide range of binding affinities. When applied to 58,000 chemicals identified by Walker et al. as candidates for endocrine disruption screening, some 9100 chemicals were predicted to bind to ER. Of these, only 3600 were expected to bind to ER at RBA values up to 100,000-fold less than that of 17 g -estradiol. The method ruled out 83% of the chemicals as non-binders with a very low rate of false negatives. We believe that the same integrated scheme will be equally applicable to endpoints of other endocrine disrupting mechanisms, e.g. androgen receptor binding.     

Synthesis and biological evaluation of novel fused indolo [3, 2-c] [1,8] naphthyridine derivatives as potential antibacterial agents

Nine novel fused indolo [1,8] naphthyridine derivatives were synthesized using the Povarov reaction, in a one-pot system, and were fully characterized by spectroscopic techniques such as FT-IR, NMR, TOF-MS, and elemental analysis. Furthermore, their antibacterial activities against six bacterial strains were assessed. The results of the bioassay demonstrated that compounds 4a, 4c, and 4i showed good inhibitory effect with a MIC value ranging from 0.04687 to 0.09375?µM against Bacillus cereus and Staphylococcus aureus. The toxicity of 4a–i, evaluated through mutagenicity test against Salmonella typhimurium TA 98 and TA100 strains, revealed that there was no significant increase in the number of revertant colonies in comparison with the control, sodium azide.     

Antioxidant and antimutagenic polyisoprenylated benzophenones and xanthones from Rheedia acuminata

Dichloromethane extract of the stem bark of Rheedia acuminata yielded three benzophenones with antioxidant activity, the new one named acuminophenone A (1), guttiferone K (2) and isoxanthochymol (3), along with the known xanthones formoxanthone C (4) and macluraxanthone (5). The structures were established through interpretation of their spectroscopic data, the stereochemistry of compounds (1) and (2) were resolved by experimental and computational experiments and their antioxidant activities were measured using the DPPH, ABTS and TEAC assays. The antioxidant results showed that metabolites 1, 4 and 5 had a better antioxidant activity than the reference compound quercetin. In addition, we evaluate the mutagenicity and antimutagenicity of the CH2Cl2 extract as well as of the free radical scavenger compounds 1, 4 and 5 by the AMES Salmonella/microsomal test. No mutagenicity was found in the CH2Cl2 extract using Salmonella typhimurium strains TA98, TA100, TA102, TA1537 and TA1538, with or without S9 metabolic activation. The pure compounds neither showed mutagenicity in TA 102 strain and the most important result was the strong reduction of mutagenic effect induced by hydrogen peroxide in S. typhimurium TA102, with or without S9, showed by the compounds 1 (more than 93%) and 4 (more than 88%) at 0.02 microg/plate.     

A strategy for ranking environmentally occurring chemicals. Part VI. QSARs for the mutagenic effects of halogenated aliphatics.

A strategy for the systematic analysis and priority ranking of environmental chemicals has been applied to a class of 58 halogenated aliphatic hydrocarbons. A training set of ten compounds representing this class, was selected by statistical design. The training set compounds were then subjected to biological testing in the Salmonella typhimurium reverse mutation assay (Ames test). The measured biological data, recorded as dose-response curves, were analyzed to determine the mutagenic potency (slope of the initial portion) and the mutagen dose (MD 50) required to increase the number of revertants above the background by 50%. For each compound, four mutagenic potency estimates and four MD 50 values were determined, all originating from the tester strains TA 100 and TA 1535 with and without metabolic activation. The obtained responses were analyzed with multivariate techniques to give QSAR models relating the mutagenic potency data to the physico-chemical properties of the compounds. Finally, the derived QSARs were used to predict the mutagenic potencies and the MD 50S for the non-tested compounds in the class.     

A Plausible Mechanism for the Mutagenic Activity (Salmonella typhimurium TA100) of MX Compounds: A Formation of CG-CG+-CG Radical Cation by One-electron Reduction

Abstract

Combining our previous QSAR work with recent high-level quantum mechanical calculations, a plausible mechanism for the mutagenic activity of halogenated furanones (so called MX compounds) in Salmonella typhimurium TA100 tester strain is proposed. The mechanism involves one-electron reduction as a key step and it seems reasonable to suggest that the mutagenicity of these direct-acting compounds may be a purely thermodynamic phenomenon, rather than the result of site-specific binding or adduct formation. Overall, the proposed model is consistent with the most experimental findings.     

Knowledge-Based Expert Systems for Toxicity and Metabolism Prediction: DEREK,StAR and METEOR

Abstract

It has long been recognised that the ability to predict the metabolic fate of a chemical substance and the potential toxicity of either the parent compound or its metabolites are important in novel drug design. The popularity of using computer models as an aid in this area has grown considerably in recent years.

LHASA Limited has been developing knowledge-based expert systems for toxicity and metabolism prediction in collaboration with industry and regulatory authorities. These systems, DEREK, StAR and METEOR, use rules to describe the relationship between chemical structure and either toxicity in the case of DEREK and StAR, or metabolic fate in the case of METEOR.

The rule refinement process for DEREK often involves assessing the predictions for a novel set of compounds and comparing them to their biological assay results as a measure of the system's performance. For example, 266 non-congeneric chemicals from the National Toxicology Program database have been processed through the DEREK mutagenicity knowledge base and the predictions compared to their Salmonella typhimurium mutagenicity data. Initially, 81 of 114 mutagens (71%) and 117 of 152 non-mutagens (77%) were correctly identified. Following further knowledge base development, the number of correctly identified mutagens has increased to 96 (84%). Further work on improving the predictive capabilities of DEREK, StAR and METEOR is in progress.     

Synthesis and properties of novel bifunctional nitrosamines with omega-chloroalkyl groups

Novel N-nitroso-N-(acetoxymethyl)-omega-chloroalkylamines were synthesized and their chemical and biological properties were evaluated. The nitrosamines were expected to decompose through omega-chloroalkyldiazohydroxides in aqueous solution, and then to alkylate various cellular macromolecules. N-Nitroso-N-(acetoxymethyl)-2-chloroethylamine rapidly decomposed in aqueous solution, and the reaction rate was apparently independent of the pH of the solution. On the other hand, the rate of decomposition of chloropropyl and chlorobutyl homologs was pH-dependent, and increased in alkaline solution. When mutagenicity was assayed in Salmonella typhimurium TA1535 and TA92 for preliminary evaluation, all three compounds were directly mutagenic. The mutagenicity in Salmonella typhimurium TA1535, which can detect base-pair change mutation, clearly showed that these compounds induced DNA alkylation in vivo. The increase of alkyl chain length in chloroalkyl compounds increased the mutagenic activity, and the activities were stronger than those of the corresponding simple alpha-acetoxy nitrosamines lacking a chloro group, N-nitroso-N-(acetoxymethyl)alkylamines. Furthermore, the positive result in TA92 suggested that chlorinated nitrosamines cross-linked DNA like antitumor chloroethylnitrosoureas and that they are expected to be new lead compounds for antitumor agents.     

U.S. EPA Regulatory Perspectives on the Use of QSAR for New and Existing Chemical Evaluations

Abstract

As testing is not required, ecotoxicity or fate data are available for ≈ 5% of the approximately 2,300 new chemicals/year (26,000 + total) submitted to the US-EPA. The EPA's Office of Pollution Prevention and Toxics (OPPT) regulatory program was forced to develop and rely upon QSARs to estimate the ecotoxicity and fate of most of the new chemicals evaluated for hazard and risk assessment. QSAR methods routinely result in ecotoxicity estimations of acute and chronic toxicity to fish, aquatic invertebrates, and algae, and in fate estimations of physical/chemical properties, degradation, and bioconcentration. The EPA's Toxic Substances Control Act (TSCA) Inventory of existing chemicals currently lists over 72,000 chemicals. Most existing chemicals also appear to have little or no ecotoxicity or fate data available and the OPPT new chemical QSAR methods now provide predictions and cross-checks of test data for the regulation of existing chemicals. Examples include the Toxics Release Inventory (TRI), the Design for the Environment (DfE), and the OECD/SIDS/HPV Programs. QSAR screening of the TSCA Inventory has prioritized thousands of existing chemicals for possible regulatory testing of: 1) persistent bioaccumulative chemicals, and 2) the high ecotoxicity of specific discrete organic chemicals.     

Integrated biological–chemical approach for the isolation and selection of polyaromatic mutagens in surface waters

Many environmental mutagens, including polyaromatic compounds are present in surface waters, often in complex mixtures and at low concentrations. The present study provides and applies a novel, integrated approach to isolate polyaromatic mutagens in river water using a sample from the River Elbe. The sample was taken downstream of industrial discharges using blue rayon (BR) as a passive sampler that selectively adsorbs polyaromatic compounds and was subjected to effect-directed fractionation in order to characterise the compounds causing the detected effect(s). The procedure relies on three complementary fractionation steps, the Ames fluctuation assay with strains TA98, YG1024 and YG1041 with and without S9 activation and analytical screening. Several mutagenic fractions were isolated by combining mutagenicity testing with fractionation. The enhanced mutagenicity in the nitroreductase and/or O-acetyltransferase overexpressing strains YG1024 and YG1041 strains suggested amino- and/or nitro-compounds causing mutagenicity in several fractions. Analytical screening of mutagenic fractions with LC-HRMS/MS provided a list of molecular formulas typically containing one to ten nitrogen and at least two oxygen atoms supporting the presence of amino and nitro-compounds in the mutagenic fractions.

Formation of a direct mutagen, diazo-N-nitrosoetilefrin, by interaction of etilefrin with nitrite

Reaction of an antihypotensive drug, etilefrin [alpha-[(ethylamino)methyl]-m-hydroxybenzyl alcohol], with nitrite under mildly acidic conditions produced N-nitrosoetilefrin [alpha-[(N-nitrosoethylamino)methyl]-m-hydroxybenzyl alcohol] (a mixture of syn and anti forms) (Iab) and diazo-N-nitrosoetilefrin [1-(4-diazo-3-oxo-1,5-cyclohexadienyl-2-(N-nitrosoethylamino )ethanol] (a mixture of syn and anti forms) (IIab). Treatment of etilefrin with an equivalent amount of nitrite at pH 3 and 37 degrees C for 4 h gave Iab (yield, 30%) and IIab (yield, 5%). Treatment of etilefrin with 4 eq of nitrite under the same conditions gave Iab (23%) and IIab (53%). Compounds Iab and IIab were each composed of two isomers due to the configuration of the N-nitroso group. While compound Iab was not mutagenic, compound IIab showed mutagenicity to Salmonella typhimurium TA98 and TA100 strains without metabolic activation. Specific mutagenic activity of IIab was 300 his+ revertant colonies for both TA98 and TA100 strains with a dose of 0.1 mumol. Addition of a microsomal activation system little affected the activity. It is noteworthy that this orally administered drug can produce a direct-acting mutagen by reaction with nitrite, which is present in the digestive tract.     

Modelling mutagenicity using properties calculated by computational chemistry

The recent advances in combinatorial chemistry and high throughput screening technologies have led to an explosion in the numbers of possible therapeutic candidates being produced at the early stages of drug discovery. This rapid increase in the number of chemicals to be classified results in a greater need for alternative methods for the prediction of toxicity. Most QSAR models for mutagenicity have been constructed for congeneric series. The prediction requirements of the pharmaceutical industry, however, cover quite diverse chemical structures. This paper reports a study of mutagenicity data for a diverse set of 90 compounds. Good discriminant models have been built for this data set using properties calculated by the techniques of computational chemistry. Jack-knifed (leave one out) predictions for these models are of the order of 85%.     

Searching for an enhanced predictive tool for mutagenicity

The Multiple Computer Automated Structure Evaluation (MCASE) program was used to evaluate the mutagenic potential of organic compounds. The experimental Ames test mutagenic activities for 2513 chemicals were collected from various literature sources. All chemicals have experimental results in one or more Salmonella tester strains. A general mutagenicity data set and fifteen individual Salmonella test strain data sets were compiled. Analysis of the learning sets by the MCASE program resulted in the derivation of good correlations between chemical structure and mutagenic activity. Significant improvement was obtained as more data was added to the learning databases when compared with the results of our previous reports. Several biophores were identified as being responsible for the mutagenic activity of the majority of active chemicals in each individual mutagenicity module. It was shown that the multiple-database mutagenicity model showed a clear advantage over normally used single-database models. The expertise produced by this analysis can be used to predict the mutagenic potential of new compounds.