Multiple Computer‐Automated structure evaluation program study of aquatic toxicity 1: Guppy

Klopman, Gilles; Saiakhov, Roustem; Rosenkranz, Herbert S.; Hermens, Joop L. M.

doi:10.1002/etc.5620181116

Cited by 29 publications

(7 citation statements)

References 37 publications

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“…To devise a mathematical means for identifying compounds with strong in vitro / in vivo correlation, we extended concepts that have been previously employed in calculating the “baseline regression” that correlated the aquatic toxicity of (some) chemicals with the logarithm of the n -octanol/water partition coefficient (log P ) (Klopman et al 1999, 2000; Mayer and Reichenberg 2006). Here, we have developed a novel approach, termed “moving M-regression,” to identify a subset of compounds with strong IC 50 versus LD 50 correlation.…”

Section: Resultsmentioning

confidence: 99%

A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents

Zhu

Richard

et al. 2009

Environ Health Perspect

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Background Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public–private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. Objective A wealth of available biological data requires new computational approaches to link chemical structure, in vitro data, and potential adverse health effects. Methods and results A database containing experimental cytotoxicity values for in vitro half-maximal inhibitory concentration (IC 50 ) and in vivo rodent median lethal dose (LD 50 ) for more than 300 chemicals was compiled by Zentralstelle zur Erfassung und Bewertung von Ersatz- und Ergaenzungsmethoden zum Tierversuch (ZEBET; National Center for Documentation and Evaluation of Alternative Methods to Animal Experiments). The application of conventional quantitative structure–activity relationship (QSAR) modeling approaches to predict mouse or rat acute LD 50 values from chemical descriptors of ZEBET compounds yielded no statistically significant models. The analysis of these data showed no significant correlation between IC 50 and LD 50 . However, a linear IC 50 versus LD 50 correlation could be established for a fraction of compounds. To capitalize on this observation, we developed a novel two-step modeling approach as follows. First, all chemicals are partitioned into two groups based on the relationship between IC 50 and LD 50 values: One group comprises compounds with linear IC 50 versus LD 50 relationships, and another group comprises the remaining compounds. Second, we built conventional binary classification QSAR models to predict the group affiliation based on chemical descriptors only. Third, we developed k -nearest neighbor continuous QSAR models for each subclass to predict LD 50 values from chemical descriptors. All models were extensively validated using special protocols. Conclusions The novelty of this modeling approach is that it uses the relationships between in vivo and in vitro data only to inform the initial construction of the hierarchical two-step QSAR models. Models resulting from this approach employ chemical descriptors only for external prediction of acute rodent toxicity.

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Section: Resultsmentioning

confidence: 99%

A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents

Zhu

Richard

et al. 2009

Environ Health Perspect

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“…Much useful information is available for fish such as the guppy and fathead minnow (examples include the Utrecht Guppy [49] and EPA Duluth [50] databases, respectively). This has enabled the development of a variety of expert systems that can model fish toxicity.…”

Section: Acute Environmental Toxicitymentioning

confidence: 99%

Integrated Decision-tree Testing Strategies for Environmental Toxicity with Respect to the Requirements of the EU REACH Legislation

et al. 2006

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Liverpool John Moores University and FRAME recently conducted a research project sponsored by Defra on the status of alternatives to animal testing with regard to the European Union REACH (Registration, Evaluation and Authorisation of Chemicals) system for safety testing and risk assessment of chemicals. The project covered all the main toxicity endpoints associated with the REACH system. This paper focuses on the prospects for using alternative methods (both in vitro and in silico) for environmental (aquatic) toxicity testing. The manuscript reviews tests based on fish cells and cell lines, fish embryos, lower organisms, and the many expert systems and QSARs for aquatic toxicity testing. Ways in which reduction and refinement measures can be used are also discussed, including the Upper Threshold Concentration — Step Down (UTC) approach, which has recently been retrospectively validated by ECVAM and subsequently endorsed by the ECVAM Scientific Advisory Committee (ESAC). It is hoped that the application of this approach could reduce the number of fish used in acute toxicity studies by around 65–70%. Decision-tree style integrated testing strategies are also proposed for acute aquatic toxicity and chronic toxicity (including bioaccumulation), followed by a number of recommendations for the future facilitation of aquatic toxicity testing with respect to environmental risk assessment.

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“…Chemicals that show activities in excess of the relationship between log P and toxicity are then subjected to CASE/MULTI-CASE analysis. Thus, some chemicals which exhibit toxicity in aquatic species (guppies (35).…”

Section: Sar Model Characterisationmentioning

confidence: 99%

Structural Basis of the Toxicity of Chemicals in Cultured Human HeLa Cells

Zhu

Rosenkranz

2000

Alternatives to Laboratory Animals

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A coherent structure-activity relationship (SAR) model was derived from data based on the toxicity of chemicals in cultured human HeLa cells. The ability to construct such a model indicates that toxicity is a function of a finite number of mechanisms. A comparison of the HeLa SAR model with models that describe other toxicological phenomena demonstrated significant mechanistic similarities with systemic toxicity in rodents and ocular irritation in rabbits. Overall, the present analyses support the hypothesis that the inclusion of a battery of cell toxicity assays together with toxicokinetic models will result in a more predictive model of systemic toxicity in humans.

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Multiple Computer‐Automated structure evaluation program study of aquatic toxicity 1: Guppy

Cited by 29 publications

References 37 publications

A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents

A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents

Integrated Decision-tree Testing Strategies for Environmental Toxicity with Respect to the Requirements of the EU REACH Legislation

Structural Basis of the Toxicity of Chemicals in Cultured Human HeLa Cells

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