ToxML,a data exchange standard with content controlled vocabulary used to build better (Q)SAR models

Development of accurate quantitative structure–activity relationship (QSAR) models requires the availability of high quality validated data. International regulations such as REACH in Europe will now accept (Q)SAR-based evaluations for risk assessment. The number of toxicity datasets available for those wishing to share knowledge, or to use for data mining and modelling, is continually expanding. The challenge is the current use of a multitude of different data formats. The issues of comparing or combining disparate data apply both to public and proprietary sources. The ToxML project addresses the need for a common data exchange standard that allows the representation and communication of these data in a well-structured electronic format. It is an open standard based on Extensible Markup Language (XML). Supporting information for overall toxicity endpoint data can be included within ToxML files. This makes it possible to assess the quality and detail of the data used in a model. The data file model allows the aggregation of experimental data to the compound level in the detail needed to support (Q)SAR work. The standard is published on a website together with tools to view, edit and download it.     

Qsar Models for Predicting the Acute Toxicity of Selected Organic Chemicals with Diverse Structures to Aquatic Non-Vertebrates and Humans

Abstract

The linear and non-linear relationships of acute toxicity (as determined on five aquatic non-vertebrates and humans) to molecular structure have been investigated on 38 structurally-diverse chemicals. The compounds selected are the organic chemicals from the 50 priority chemicals prescribed by the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme. The models used for the evaluations are the best combination of physico-chemical properties that could be obtained so far for each organism, using the partial least squares projection to latent structures (PLS) regression method and backpropagated neural networks (BPN). Non-linear models, whether derived from PLS regression or backpropagated neural networks, appear to be better than linear models for describing the relationship between acute toxicity and molecular structure. BPN models, in turn, outperform non-linear models obtained from PLS regression. The predictive power of BPN models for the crustacean test species are better than the model for humans (based on human lethal concentration). The physico-chemical properties found to be important to predict both human acute toxicity and the toxicity to aquatic non-vertebrates are the n?octanol water partition coefficient (Pow) and heat of formation (HF). Aside from the two former properties, the contribution of parameters that reflect size and electronic properties of the molecule to the model is also high, but the type of physico-chemical properties differs from one model to another. In all of the best BPN models, some of the principal component analysis (PCA) scores of the ¹³C-NMR spectrum, with electron withdrawing/accepting capacity (LUMO, HOMO and IP) are molecular size/volume (VDW or MS1) parameters are relevant. The chemical deviating from the QSAR models include non-pesticides as well as some of the pesticides tested. The latter type of chemical fits in a number of the QSAR models. Outliers for one species may be different from those of other test organisms.     

Experiences with the Application of QSAR in the Routine of the Notification Procedure

Abstract

On behalf of the Umweltbundesamt the Fraunhofer Gesellschaft has developed a software system (SAR-system) comprising more than 90 estimation models for endpoints relevant in environmental risk assessment. These estimation models are based on the approach of quantitative structure-activity relationships (QSAR). All models were checked for their validity and application range. In the last months the Umweltbundesamt started to test the applicability of some models concerning the endpoints fish acute toxicity, daphnia acute toxicity and ready (i.e., ultimate) biodegradability in the daily routine of the notification procedure. For testing these models the corresponding confidential data given in the dossiers of substances notified 1993 in Germany, were used. We were able to make calculations for 36% of the notified substances. For the remaining 64% of the chemicals it was impossible to accomplish SAR estimations due to several reasons, e.g., ionic structure of the compounds. Different results for the applicability of the mentioned endpoints are obtained. The predictions of the fish and Daphnia toxicity are in sufficient agreement with the experimental results, in case of the fish toxicity we receive 58% agreement, for the Daphnia toxicity 56% The corresponding values which were obtained in the US EPA/E.C. Joint Project on the evaluation of (quantitative) structure activity relationships were 82.3% and 70.9% About 300 different models were used for the calculations of these endpoints within the framework of the EPA/EC project. The SAR-system presented here contains 8 models for estimating the fish toxicity and 6 models for the Daphnia toxicity. For the prediction of the biodegradability the results obtained with the SAR-system are rather poor and have to be improved. Meanwhile the SAR-system is commercially available and can be ordered at the Fraunhofer Institute for Environmental Chemistry and Ecotoxicology, Schmallenberg (Germany).     

Physicochemical and Graph Theoretical Descriptors in Developmental Toxicity SAR: A Comparative Study

Abstract

Chemical insults to the developing fetus can lead to growth retardation, malformation, death, and functional deficits. The present study seeks to determine if physicochemical and/or graph theoretical parameters can be used to determine a structure-activity relationship (SAR) for developmental toxicity, and if consistency is observed among the selected features. The biological data utilized consists of a diverse series of compounds evaluated within the Chernoff-Kavlock in vivo mouse assay. Physicochemical parameters calculated correspond to electronic, steric, and transport properties. Graph theoretical parameters calculated include the simple, valence, and kappa indices. Both sets of parameters were independently applied to derive SARs in order to compare the quality of the respective models. Multiple random sampling, without replacement, was utilized to obtain ten training/test partitions. Models were built by linear discriminant analysis, decision trees, and neural networks respectively. Comparisons on identical sets of data were carried out to determine if any of the model building procedures had a significant advantage in terms of predictive performance. Furthermore, comparison of the features selected within and across the model building processes led to the determination of model consistency. Our results indicate that consistent features related to developmental toxicity are observed and that both physicochemical and graph theoretical parameters have equal utility.     

QSAR-based toxicity classification and prediction for single and mixed aromatic compounds

Quantitative structure-activity relationships (QSARs) based on the octanol/water partition coefficient were employed to predict acute toxicities of 36 substituted aromatic compounds and their mixtures. In this study, the model developed by Verhaar et al. was modified and used to calculate octanol/water partition coefficients of chemical mixtures. To validate the model, acute toxicities of these chemicals were measured to Vibrio fischeri in terms of EC⁵⁰. The results indicated that the obtained QSAR models could be used to predict toxicities of samples consisting of these substituted aromatic compounds, individually or in combinations. The obtained equations were proved to be robust enough by using the leave-one-out test method. By classifying these chemicals into two groups, polar and non-polar, the toxicities of chemical mixtures within each group can be predicted accurately from their calculated partition coefficients.     

Chemical characterisation of a new estuarine pollutant (2,4-Dichloro-6-Nitrophenol) and assessment of the acute toxicity of its quinoid form for Artemia salina

It is known that the compound 2,4-dichloro-6-nitrophenol (2,4DC6NP) is formed upon nitration of 2,4-dichlorophenol, which in turn is a transformation intermediate of the herbicide dichlorprop. However, the chemical and spectroscopic characteristics of 2,4DC6NP, as well as its toxicity, are poorly known. This work shows that 2,4DC6NP behaves as a diprotic acid in aqueous solutions, with pK_a values of 3.0?±?0.9 and 4.9?±?0.5. At pH?<?3, 2,4DC6NP would undergo protonation. The absorption spectra suggest that anionic 2,4DC6NP, which prevails at pH?>?5 would have an ortho-quinoid structure that is responsible for the absorption peak centred at 428?nm. Considering that 2,4DC6NP has been detected in the brackish lagoons of the Rhône delta (southern France), where its levels are comparable to those of the parent herbicide, it is necessary to examine the possible effects of 2,4DC6NP on the species living in that environment. For this reason, the acute toxicity of the anionic form of 2,4DC6NP was assessed for the brine shrimp Artemia salina, a zooplankton species that lives both in brackish and in saline aquatic environments. The toxicity test yielded a LC₂₀ value of 8?±?2?mg?L^?1 and a LC₅₀ value of 18.7?±?0.8?mg?L^?1. Such values are safely higher than the maximum detected concentration of 2,4DC6NP in the Rhône delta lagoons. Further studies should be concentrated on the long-term effects of 2,4DC6NP, and in particular on its potential genotoxicity.     

Modeling and analysis of a marine plankton system with nutrient recycling and diffusion

This article describes a nutrient‐phytoplankton‐zooplankton system with nutrient recycling in the presence of toxicity. We have studied the dynamical behavior of the system with delayed nutrient recycling in the first part of the article. Uniform persistent of the system is examined. In the second part of the article, we have incorporated diffusion of the plankton population to the system and dynamical behavior of the system is analyzed with instantaneous nutrient recycling. The condition of the diffusion driven instability is obtained. The conditions for the occurrence of Hopf and Turing bifurcation critical line in a spatial domain are derived. Variation of the system with small periodicity of diffusive coefficient has been studied. Stability condition of the plankton system subject to the periodic diffusion coefficient of the zooplankton is derived. It is observed that nutrient‐phytoplankton‐zooplankton interactions are very complex and situation specific. Moreover, we have obtained different exciting results, ranging from stable situation to cyclic oscillatory behavior may occur under different favorable conditions, which may give some insights for predictive management. © 2014 Wiley Periodicals, Inc. Complexity 21: 229–241, 2015