The KOW Controversy

Renner, Rebecca

doi:10.1021/es022457+

Cited by 52 publications

(56 citation statements)

References 3 publications

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“…This equation could be correctly applied for the prediction of new toxicity data only if the descriptor value is homogeneously calculated, but it is well known that, in apparent contradiction to its wide use, log K ow is not a universal descriptor and its value varies, depending on the experimental procedure or the calculation method applied [17,18]. Thus, the predicted data will differ if log K ow used in the equation comes from a different experimental method or different software [18].…”

Section: Principle 2: An Unambiguous Algorithmmentioning

confidence: 99%

Principles of QSAR models validation: internal and external

2007

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The recent REACH Policy of the European Union has led to scientists and regulators to focus their attention on establishing general validation principles for QSAR models in the context of chemical regulation (previously known as the Setubal, nowadays, the OECD principles). This paper gives a brief analysis of some principles: unambiguous algorithm, Applicability Domain (AD), and statistical validation. Some concerns related to QSAR\ud algorithm reproducibility and an example of a fast check of the applicability domain for MLR models are presented. Common myths and misconceptions related to popular techniques for verifying internal predictivity, particularly for MLR models (for instance crossvalidation,\ud bootstrap), are commented on and compared with commonly used statistical techniques for external validation. The differences in the two validating approaches are highlighted, and evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes.\ud (“Validation is one of those words...that is constantly used and seldom defined” as stated by A. R. Feinstein in the book Multivariate Analysis: An Introduction, Yale University Press, New Haven, 1996)

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Section: Principle 2: An Unambiguous Algorithmmentioning

confidence: 99%

Principles of QSAR models validation: internal and external

2007

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“…Chemicals are subject to various partitioning processes within and between these environmental spheres, which influence their expected presence in any of these spheres. The measurement of these partition coefficients is tedious and coefficients reported in the literature often vary over several orders of magnitude for a given compound and partitioning system [7].…”

Section: A General Principle To Predict Partitioning Between Diverse mentioning

confidence: 99%

Developing Methods to Predict Chemical Fate and Effect Endpoints for Use Within REACH

Fenner¹,

Canonic²,

Escher³

et al. 2006

Chimia

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Abstract:With the pending implementation of REACH, both old and new chemicals will have to be registered and chemical safety reports will have to be compiled. Depending on the yearly tonnages produced or imported, (eco-) toxicological and chemical fate data of varying degrees of detail will have to be produced. It has been forecast that these new requirements will result in higher costs for registration and an increased need for animal testing. Some of this additional workload could be avoided by making use of in vitro or in silica prediction methods. At Eawag (Swiss Federal Institute of Aquatic Science and Technology) several research groups are working on the development and validation of quantitative structure-activity relationships (QSARs) and related methods to predict ecotoxicological and fate endpoints, such as reactivities in or partitioning between different environmental media, based on chemical structure or easily measurable physico-chemical properties. When developing such tools, special attention has to be paid to use only descriptors whose mechanistic significance for the modelled endpoint is well understood on a molecular level. In this article four examples of our work in the field of compound fate and effect predictions will be presented: i) the measurement of compound descriptors for use in linear-free-energy relationships to predict partition coefficients between environmental media; ii) the development of free-energy relationships for the prediction of indirect photolysis; iii) the evaluation of existing structure-biodegradability models to predict soil biodegradation half-lives; and iv) the application of mode-of-action-based test batteries to develop quantitative structure-activity relationships to classify chemicals according to their modes of toxic action.

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“…[11][12][13][14][15][16][17][18][19][20][21][22] This hydrophobicity term, usually given as logP ow represents the ability of a substance to enter into cells through the lipid membranes related to both toxicant uptake and baseline toxicity. Among a large number of the QSAR models in the past decades, the octanol-water partition coefficient (P ow ) has been known important as a descriptor to predict the toxicity.…”

Section: Introductionmentioning

confidence: 99%

An Electronic‐structure Informatics Study on the Toxicity of Alkylphenols toTetrahymena pyriformis

Sugimoto

Manggara

Yoshida

et al. 2020

Molecular Informatics

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Alkylphenols (APs) dissolved in water are known to be toxic to animals including humans. In this study, regression models describing the toxicity of the 33 AP molecules were investigated for reproducing and thereby making it possible to predict a quantitative structureactivity relationship (QSAR). For this purpose, we tried to derive regression models for the experimental IGC 50 (growth inhibition concentration at 50 %) to Tetrahymena pyriformis by using various descriptor sets consisting of electronic and shape descriptors. By applying the multiple linear regression (MLR) analysis, it was successful to derive a quantitative regression model for the IGC 50 values. In this analysis, the size parameters of the molecules were found important, suggesting that bulky molecules should be less toxic. We could also obtain, when the size descriptors were excluded, an MLR model indicating that the electron affinity (EA) should be important, which is consistent with the previous QSAR studies. Through the correlation analysis among the descriptors, it was shown that, in the present set of molecules, EA and a size parameter are highly correlated. Since EA was calculated to be negative, indicating that the related process would be energetically unfavourable, it was concluded that the size of the molecules should be a dominant factor determining IGC 50 . This implies that a molecular recognition process would play a critical role in the mode of action for the toxicity.

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The KOW Controversy

Cited by 52 publications

References 3 publications

Principles of QSAR models validation: internal and external

Principles of QSAR models validation: internal and external

Developing Methods to Predict Chemical Fate and Effect Endpoints for Use Within REACH

An Electronic‐structure Informatics Study on the Toxicity of Alkylphenols toTetrahymena pyriformis

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