Literature DB >> 19005789

Polar narcosis: Designing a suitable training set for QSAR studies.

E U Ramos1, W H Vaes, H J Verhaar, J L Hermens.   

Abstract

Substituted phenols, anilines, pyridines and mononitrobenzenes can be classified as polar narcotics. These chemicals differ from non-polar narcotic compounds not only in their toxic potency (normalized by log K(ow)), but also in their Fish Acute Toxicity Syndrome profiles, together suggesting a different mode of action. For 97 polar narcotics, which are not ionized under physiological conditions, 11 physico-chemical and quantum-chemical descriptors were calculated. Using principal component analysis, 91% of the total variance in this descriptor space could be explained by three principal components which were subsequently used as factors in a statistical design. Eleven compounds were selected based on a two-level full factorial design including three compounds near the center of the chemical domain (a 2(3)+3 design). QSARs were developed for both the design set and the whole set of 63 polar narcotics for which guppy and/or fathead minnow data were available in the literature. Both QSARs, based on partial least squares regression (3 latent variables), resulted in good models (R(2)=0.96 and Q(2)=0.82; R(2)=0.86 and Q(2)=0.83 respectively) and provided similar pseudo-regression coefficients. In addition, the model based on the design chemicals was able to predict the toxicity of the 63 compounds (R(2) =0.85). Models show that acute fish toxicity is determined by hydrophobicity, HOMO-LUMO energy gap and hydrogen-bond acceptor capacity.

Entities:  

Year:  1997        PMID: 19005789     DOI: 10.1007/BF02986285

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  8 in total

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Journal:  Ecotoxicol Environ Saf       Date:  1986-10       Impact factor: 6.291

2.  Molecular connectivity of phenols and their toxicity to fish.

Authors:  L H Hall; L B Kier
Journal:  Bull Environ Contam Toxicol       Date:  1984-03       Impact factor: 2.151

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Authors:  H Kŏnemann; A Musch
Journal:  Toxicology       Date:  1981       Impact factor: 4.221

4.  Acute toxicity of priority pollutants to water flea (Daphnia magna).

Authors:  G A LeBlanc
Journal:  Bull Environ Contam Toxicol       Date:  1980-05       Impact factor: 2.151

5.  Relation between physicochemical properties of phenols and their toxicity and accumulation in fish.

Authors:  J Saarikoski; M Viluksela
Journal:  Ecotoxicol Environ Saf       Date:  1982-12       Impact factor: 6.291

6.  Application of QSARs in risk management of existing chemicals.

Authors:  H J Verhaar; C J van Leeuwen; J Bol; J L Hermens
Journal:  SAR QSAR Environ Res       Date:  1994       Impact factor: 3.000

7.  Quantitative structure-activity relationships and mixture toxicity studies of chloro- and alkylanilines at an acute lethal toxicity level to the guppy (Poecilia reticulata).

Authors:  J Hermens; P Leeuwangh; A Musch
Journal:  Ecotoxicol Environ Saf       Date:  1984-08       Impact factor: 6.291

8.  Rules for distinguishing toxicants that cause type I and type II narcosis syndromes.

Authors:  G D Veith; S J Broderius
Journal:  Environ Health Perspect       Date:  1990-07       Impact factor: 9.031

  8 in total
  4 in total

1.  Megavariate analysis of environmental QSAR data. Part I--a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD).

Authors:  Lennart Eriksson; Patrik L Andersson; Erik Johansson; Mats Tysklind
Journal:  Mol Divers       Date:  2006-06-13       Impact factor: 2.943

2.  Predicting concentrations of organic chemicals in fish by using toxicokinetic models.

Authors:  Julita Stadnicka; Kristin Schirmer; Roman Ashauer
Journal:  Environ Sci Technol       Date:  2012-02-28       Impact factor: 9.028

3.  Measured and modeled toxicokinetics in cultured fish cells and application to in vitro-in vivo toxicity extrapolation.

Authors:  Julita Stadnicka-Michalak; Katrin Tanneberger; Kristin Schirmer; Roman Ashauer
Journal:  PLoS One       Date:  2014-03-19       Impact factor: 3.240

4.  Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics.

Authors:  Izabella Surowiec; Erik Johansson; Frida Torell; Helena Idborg; Iva Gunnarsson; Elisabet Svenungsson; Per-Johan Jakobsson; Johan Trygg
Journal:  Metabolomics       Date:  2017-08-24       Impact factor: 4.290

  4 in total

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