Literature DB >> 7570660

Quantitative structure-activity relationships and ecological risk assessment: an overview of predictive aquatic toxicology research.

S P Bradbury1.   

Abstract

In the field of aquatic toxicology, quantitative structure-activity relationships (QSARs) have developed as scientifically credible tools for predicting the toxicity of chemicals when little or no empirical data are available. A fundamental understanding of toxicological principles has been considered an important component to the acceptance and application of QSAR approaches as biologically relevant in ecological risk assessments. As a consequence, there has been an evolution of QSAR development and application from that of a chemical-class perspective to one that is more consistent with assumptions regarding modes of toxic action. In this review, techniques to assess modes of toxic action from chemical structure are discussed, with consideration that toxicodynamic knowledge bases must be clearly defined with regard to exposure regimes, biological models/endpoints and compounds that adequately span the diversity of chemicals anticipated for future applications. With such knowledge bases, classification systems, including rule-based expert systems, have been established for use in predictive aquatic toxicology applications. The establishment of QSAR techniques that are based on an understanding of toxic mechanisms is needed to provide a link to physiologically based toxicokinetic and toxicodynamic models, which can provide the means to extrapolate adverse effects across species and exposure regimes.

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Year:  1995        PMID: 7570660     DOI: 10.1016/0378-4274(95)03374-t

Source DB:  PubMed          Journal:  Toxicol Lett        ISSN: 0378-4274            Impact factor:   4.372


  11 in total

1.  Quantile regression model for a diverse set of chemicals: application to acute toxicity for green algae.

Authors:  Jonathan Villain; Sylvain Lozano; Marie-Pierre Halm-Lemeille; Gilles Durrieu; Ronan Bureau
Journal:  J Mol Model       Date:  2014-11-29       Impact factor: 1.810

2.  QSPR modeling of detonation parameters and sensitivity of some energetic materials: DFT vs. PM3 calculations.

Authors:  Jianying Zhang; Gangling Chen; Xuedong Gong
Journal:  J Mol Model       Date:  2017-05-22       Impact factor: 1.810

3.  Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms.

Authors:  Guillaume Fayet; Patricia Rotureau; Laurent Joubert; Carlo Adamo
Journal:  J Mol Model       Date:  2010-12-21       Impact factor: 1.810

Review 4.  Recent advances in fragment-based QSAR and multi-dimensional QSAR methods.

Authors:  Kyaw Zeyar Myint; Xiang-Qun Xie
Journal:  Int J Mol Sci       Date:  2010-10-08       Impact factor: 5.923

5.  High-throughput respirometric assay identifies predictive toxicophore of mitochondrial injury.

Authors:  Lauren P Wills; Gyda C Beeson; Richard E Trager; Christopher C Lindsey; Craig C Beeson; Yuri K Peterson; Rick G Schnellmann
Journal:  Toxicol Appl Pharmacol       Date:  2013-06-26       Impact factor: 4.219

6.  A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity.

Authors:  Tjalling Jager; Sebastiaan A L M Kooijman
Journal:  Ecotoxicology       Date:  2008-10-19       Impact factor: 2.823

7.  QSPR modeling of thermal stability of nitroaromatic compounds: DFT vs. AM1 calculated descriptors.

Authors:  Guillaume Fayet; Patricia Rotureau; Laurent Joubert; Carlo Adamo
Journal:  J Mol Model       Date:  2010-01-05       Impact factor: 1.810

Review 8.  Reviewing ligand-based rational drug design: the search for an ATP synthase inhibitor.

Authors:  Chia-Hsien Lee; Hsuan-Cheng Huang; Hsueh-Fen Juan
Journal:  Int J Mol Sci       Date:  2011-08-17       Impact factor: 5.923

9.  Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species.

Authors:  W Tong; R Perkins; R Strelitz; E R Collantes; S Keenan; W J Welsh; W S Branham; D M Sheehan
Journal:  Environ Health Perspect       Date:  1997-10       Impact factor: 9.031

10.  A Mechanism-based QSTR Model for Acute to Chronic Toxicity Extrapolation: A Case Study of Antibiotics on Luminous Bacteria.

Authors:  Dali Wang; Yue Gu; Min Zheng; Wei Zhang; Zhifen Lin; Ying Liu
Journal:  Sci Rep       Date:  2017-07-20       Impact factor: 4.379

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