Substance-tailored testing strategies in toxicology: an in silico methodology based on QSAR modeling of toxicological thresholds and Monte Carlo simulations of toxicological testing.

The design of toxicological testing strategies aimed at identifying the toxic effects of chemicals without (or with a minimal) recourse to animal experimentation is an important issue for toxicological regulations and for industrial decision-making. This article describes an original approach which enables the design of substance-tailored testing strategies with a specified performance in terms of false-positive and false-negative rates. The outcome of toxicological testing is simulated in a different way than previously published articles on the topic. Indeed, toxicological outcomes are simulated not only as a function of the performance of toxicological tests but also as a function of the physico-chemical properties of chemicals. The required inputs for our approach are QSAR predictions for the LOAELs of the toxicological effect of interest and statistical distributions describing the relationship existing between in vivo LOAEL values and results from in vitro tests. Our methodology is able to correctly predict the performance of testing strategies designed to analyze the teratogenic effects of two chemicals: di(2-ethylhexyl)phthalate and Indomethacin. The proposed decision-support methodology can be adapted to any toxicological context as long as a statistical comparison between in vitro and in vivo results is possible and QSAR models for the toxicological effect of interest can be developed.

Results of a round-robin exercise on read-across.

A round-robin exercise was conducted within the CALEIDOS LIFE project. The participants were invited to assess the hazard posed by a substance, applying in silico methods and read-across approaches. The exercise was based on three endpoints: mutagenicity, bioconcentration factor and fish acute toxicity. Nine chemicals were assigned for each endpoint and the participants were invited to complete a specific questionnaire communicating their conclusions. The interesting aspect of this exercise is the justification behind the answers more than the final prediction in itself. Which tools were used? How did the approach selected affect the final answer?

The individual tyrosines of proteins: their spectra may or may not differ from those in water or other solvents.

The overall derivative spectrum of a protein is the sum of the individual derivative spectra just as the overall ultraviolet spectrum of a protein is the sum of its component parts. The RNase and DNA binding protein Sso7d has two tyrosines and one tryptophan. We used two mutant forms of the protein to show that the individual aromatics contribute derivative spectra that can be explained on the basis of their environments. We used mutant forms of iso-1-cytochrome c to estimate the contributions of the single tryptophan and three of the five tyrosines to the overall derivative spectrum. The tryptophan spectrum is not exceptional. The comparable tyrosine spectra are more complex. The derivative spectrum of individual tyrosines does not correspond to that expected on the basis of concentration. This is a reflection of two factors: (1) the extent to which mutations are sensed distally through the introduction and compression of packing defects; and (2) the extent to which electronic transitions of tyrosine are influenced by nearby atoms. This influence could take the form of tyrosine residing in an area where the dielectric coefficient is not uniform; it could also result from tyrosine bumping into neighboring atoms with lower frequency than it does in solution.

Expression of a synthetic gene encoding P2 ribonuclease from the extreme thermoacidophilic archaebacterium Sulfolobus solfataricus in mesophylic hosts.

This work reports the molecular cloning and expression of a synthetic gene encoding P2, a 7-kDa ribonuclease (RNase) previously isolated in our laboratory from the archaebacterium Sulfolobus solfataricus [Fusi et al., Eur. J. Biochem. 211 (1993) 305-310]. The P2-encoding synthetic gene was expressed in E. coli and in Saccharomyces cerevisiae. The recombinant (re-) protein was produced to approx. 1.5% of the total protein content in S. cerevisiae using the galactose-inducible GAL1 promoter and to 3% (tac/lac tandem promoters) or 6.5% (T7 promoter) in E. coli as judged by immunological and biochemical criteria. E. coli-produced P2 was purified to electrophoretic homogeneity through a one-step procedure, i.e., DEAE-Sephacel chromatography at pH 9.3. S. cerevisiae-produced P2 additionally required filtration through a Centricon-10 microconcentrator to obtain the same purity. The re-P2 was found to be indistinguishable from the Su. solfataricus enzyme on the basis of heat stability, pH optimum and RNA digestion pattern. Furthermore, monodimensional nuclear magnetic resonance showed that the E. coli- and Su. solfataricus-produced enzymes were structurally identical, the only exceptions being that Lys4 and Lys6 were not methylated in the re-enzyme, thus showing that lysine methylation does not play a role in P2 thermostabilization.

Perspectives for integrating human and environmental risk assessment and synergies with socio-economic analysis.

For more than a decade, the integration of human and environmental risk assessment (RA) has become an attractive vision. At the same time, existing European regulations of chemical substances such as REACH (EC Regulation No. 1907/2006), the Plant Protection Products Regulation (EC regulation 1107/2009) and Biocide Regulation (EC Regulation 528/2012) continue to ask for sector-specific RAs, each of which have their individual information requirements regarding exposure and hazard data, and also use different methodologies for the ultimate risk quantification. In response to this difference between the vision for integration and the current scientific and regulatory practice, the present paper outlines five medium-term opportunities for integrating human and environmental RA, followed by detailed discussions of the associated major components and their state of the art. Current hazard assessment approaches are analyzed in terms of data availability and quality, and covering non-test tools, the integrated testing strategy (ITS) approach, the adverse outcome pathway (AOP) concept, methods for assessing uncertainty, and the issue of explicitly treating mixture toxicity. With respect to exposure, opportunities for integrating exposure assessment are discussed, taking into account the uncertainty, standardization and validation of exposure modeling as well as the availability of exposure data. A further focus is on ways to complement RA by a socio-economic assessment (SEA) in order to better inform about risk management options. In this way, the present analysis, developed as part of the EU FP7 project HEROIC, may contribute to paving the way for integrating, where useful and possible, human and environmental RA in a manner suitable for its coupling with SEA.

Evaluation of the OECD (Q)SAR Application Toolbox for the profiling of estrogen receptor binding affinities.

The determination of binding affinities for the estrogen receptor (ER) is used extensively to assess potential hazards to human health and the environment arising from chemicals that can interfere with natural hormone homeostasis. Given the great number of chemicals to which humans and wildlife are exposed, (quantitative) structure-activity relationship (Q)SAR models for the characterization of ER disruptors represent a fast and cost-efficient alternative to experimental testing. In this toxicological context, the freely available Organisation for Economic Co-operation and Development (OECD) (Q)SAR Application Toolbox provides a profiler for the categorical profiling of chemicals according to their ER binding propensities. The aim of this study was to evaluate the predictive performances of this profiler. To achieve such a purpose, prediction results with the ER-profiler were compared with experimental binding affinities relative to two large datasets of chemicals (rat and human). The resulting Cooper statistics indicated that the binding affinities of the majority of chemicals included in the retained datasets could be correctly predicted.

Structural alerts for estimating the carcinogenicity of pesticides and biocides.

More than 20 years ago, Ashby and Tennant showed the interest of structural alerts for the prediction of the carcinogenicity of chemicals. These structural alerts are functional groups or structural features of various sizes that are linked to the level of carcinogenicity of chemicals. Since this pioneering work it has been possible to refine the alerts over time, as more experimental results have become available and additional mechanistic insights have been gained. To date, one of the most advanced lists of structural alerts for evaluating the carcinogenic potential of chemicals is the list proposed by Benigni and Bossa and that is implemented as a rule-based system in Toxtree and in the OECD QSAR Application Toolbox. In order to gain insight into the applicability of this system to the detection of potential carcinogens we screened about 200 pesticides and biocides showing a high structural diversity. Prediction results were compared with experimental data retrieved from an extensive bibliographical review. The prediction correctness was only equal to 60.14%. Attempts were made to analyse the sources of mispredictions.

Androgen receptor binding affinity: a QSAR evaluation.

The multiparameter formulation of the COmmon REactivity PAttern (COREPA) approach has been used to describe the structural requirements for eliciting rat androgen receptor (AR) binding affinity, accounting for molecular flexibility. Chemical affinity for AR binding was related to the distances between nucleophilic sites and structural features describing electronic and hydrophobic interactions between the receptor and ligands. Categorical models were derived for each binding affinity range in terms of specific distances, local (maximal donor delocalizability associated with the oxygen atom of the A ring), global nucleophilicity (partial positive surface areas and energy of the highest occupied molecular orbital) and hydrophobicity (log Kow) of the molecules. An integral screening tool for predicting binding affinity to AR was constructed as a battery of models, each associated with different activity bins. The quality of the screening battery of models was assessed using a high value (0.9) of the Pearson contingency coefficient. The predictability of the model was assessed by testing the model performance on external validation sets. A recently developed technique for selection of potential androgenically active chemicals was used to test the performance of the model in its applicability domain. Some of the selected chemicals were tested for AR transcriptional activation. The experimental results confirmed the theoretical predictions.

Evaluation of the OECD (Q)SAR Application Toolbox and Toxtree for predicting and profiling the carcinogenic potential of chemicals.

The OECD (Q)SAR Application Toolbox and Toxtree are software tools used in regulatory toxicology to fill gaps in (eco)toxicity data. They include different SAR and QSAR models for estimating (eco)toxicological endpoints. Among them, the Benigni/Bossa rule-based system is proposed to characterize the carcinogenic potential of chemicals. Our study evaluates the predictive performance that can be expected from the OECD (Q)SAR Toolbox and Toxtree when analysing chemicals by means of the structural alerts coded within the Benigni/Bossa rule-based system for carcinogenicity and the associated QSAR model (QSAR8). These evaluations have been carried out thanks to a large collection of chemicals retrieved from original publications and public databases. Overall, our findings confirm the performance of the system of structural alerts while suggesting that the sensitivity of QSAR8, as implemented in the two tools, is lower than what was previously reported. They also indicate that attention has to be paid when interpreting the output of the two tools because of possible malfunctions involving the coding of two-dimensional structures. A set of possible modulating factors for the structural alert identifying polycyclic aromatic hydrocarbons is also proposed together with candidates for putative new structural alerts not included in the tested tools.

Evaluation of the OECD QSAR Application Toolbox and Toxtree for estimating the mutagenicity of chemicals. Part 1. Aromatic amines.

The Ames Salmonella typhimurium mutagenicity assay is a short-term bacterial reverse mutation test that was designed to detect mutagens. For several decades, it has been used in research laboratories and by regulatory agencies throughout the world for the detection and characterization of potential mutagens among natural products and man-made chemicals. Faced with the ever-growing number of chemicals available on the market, congeneric and non-congeneric (Q)SAR models have been designed from Ames test results obtained on specific S. typhimurium strains such as TA 100 or TA 98. Such models have great potential for a quick and cheap identification and classification of large numbers of potential chemical mutagens. The OECD QSAR Application Toolbox and Toxtree, which were developed for facilitating the practical use of (Q)SAR approaches in regulatory contexts, include two mechanistic SAR models for predicting the mutagenicity of aromatic amines and α-ß unsaturated aliphatic aldehydes. The aim of this study was to estimate the interest and limitations of the former model. The model was first re-computed to check its transparency and to verify its statistical validity. Then, it was tested on about 150 chemicals not previously used for the design of the model but belonging to its domain of application. A critical analysis of the results was performed and proposals were made for increasing the model performances.

Evaluation of the OECD QSAR Application Toolbox and Toxtree for estimating the mutagenicity of chemicals. Part 2. α-ß unsaturated aliphatic aldehydes.

The OECD QSAR Application Toolbox versions 1.1.01 and 1.1.02 and Toxtree version 1.60, which were developed for facilitating the practical use of (Q)SAR approaches by regulators, include a mechanistic SAR model for predicting the mutagenicity of α-ß unsaturated aliphatic aldehydes. The aim of this study was to estimate the interest and limitations of this model. First, the model was re-computed to check its transparency and to verify its statistical validity. Then, the model implemented in the two software tools was tested on 34 chemicals not previously used for its design and for which experimental mutagenic activity data were available in the literature. A critical analysis of the results was performed and the practical interest of the model was discussed.

Production of engineered human pancreatic ribonucleases, solving expression and purification problems, and enhancing thermostability.

Human pancreatic ribonuclease, the homolog of bovine pancreatic ribonuclease, has a significant therapeutic potential. Its study has been hindered by the difficulty of obtaining the enzyme in a pure and homogeneous form, either from human source or using heterologous expression. Engineering of different variants of human pancreatic ribonuclease has allowed us to study and overcome some problems encountered during its heterologous production in an Escherichia coli system and its purification from inclusion bodies. The 5'-end region of the mRNA that encodes the enzyme is critical for obtaining high expression levels. The results also suggest the importance of the proline 50 residue in the recovery yields of human pancreatic ribonuclease. All the variants produced are pure and homogeneous. Their homogeneity has been demonstrated by cation-exchange and reversed-phase chromatography and by mass spectrometry analysis. Moreover, enhancement of human pancreatic ribonuclease thermal stability is observed when residues R4, K6, Q9, D16, and S17 are changed to the corresponding residues of bovine seminal ribonuclease.

The role of phenylalanine 31 in maintaining the conformational stability of ribonuclease P2 from Sulfolobus solfataricus under extreme conditions of temperature and pressure.

Ribonuclease P2 from the thermophilic archaebacterium Sulfolobus solfataricus is a small protein (7 kDa) with a known three-dimensional structure. Inspection of the structure and molecular dynamics simulation reveal that three aromatic residues (Phe5, Phe31, and Tyr33) from the hydrophobic core have a strong van der Waals interaction energy. We studied the thermodynamics of the heat, cold, and pressure-induced protein conformational changes of the wild type and of the F31A and F31Y mutants by analyzing the protein UV absorbance in the fourth derivative mode. The wild-type protein was extremely stable under all conditions of temperature and pressure. Heat and cold denaturation of both mutants, as well as denaturation by pressure of the F31A mutant, led to significant blue shifts of the derivative spectrum, indicating increased solvent exposure of Tyr33. For the F31Y mutant, high pressure (400 MPa) protected the protein against thermal denaturation. This study, probing the properties of the hydrophobic aromatic core, complements a thermal unfolding study which probes the overall structural changes [Knapp, S., Karshikoff, A., Berndt, K. D., Christova, P., Atanasov, B., & Ladenstein, R. (1996) J. Mol. Biol. 264,1132-1144]. The differences observed in response to extremes of temperature, pressure, and pH may be rationalized by an unfolding mechanism involving larger parts of the peripheral protein while the integrity of the hydrophobic core is maintained.