Partial Order Ranking for the aqueous toxicity of aromatic mixtures

We apply a predictive method based on Partial Order Ranking that employs a single molecular descriptor in the model and that is simple enough to perform calculations by hand. A comparison of this procedure with results obtained from the least squares technique is carried out, using aqueous toxicity values elicited by 67 compounds and their aromatic mixtures, and the octanol/water partition coefficient as structural descriptor. Both techniques verify that, by means of a previous classification of the compounds in polar and non-polar groups, it is possible to predict the joint toxicological effect.

[1]  R. García-Domenech,et al.  General topological patterns of known drugs. , 2001, Journal of molecular graphics & modelling.

[2]  S. Murray,et al.  Joint acute toxicity of esfenvalerate and diazinon to larval fathead minnows (Pimephales promelas) , 2003, Environmental toxicology and chemistry.

[3]  Mark T D Cronin,et al.  Structure-toxicity relationships for aliphatic chemicals evaluated with Tetrahymena pyriformis. , 2002, Chemical research in toxicology.

[4]  S. Smith,et al.  Evaluation of the toxicity and quantitative structure - activity Relationships (QSAR) of chlorophenols to the copepodid stage of a marine copepod (Tisbe battagliai) and two species of benthic flatfish, the flounder (Platichthys flesus) and sole (Solea solea) , 1994 .

[5]  T. Lovekamp-Swan,et al.  Mechanisms of phthalate ester toxicity in the female reproductive system. , 2002, Environmental health perspectives.

[6]  Backhaus,et al.  The single substance and mixture toxicity of quinolones to the bioluminescent bacterium Vibrio fischeri. , 2000, Aquatic toxicology.

[7]  C. Hansch.  Quantitative approach to biochemical structure-activity relationships , 1969 .

[8]  Ovanes Mekenyan,et al.  Quantum‐chemical Descriptors for Estimating the Acute Toxicity of Electrophiles to the Fathed minnow (Pimephales promelas): An Analysis Based on Molecular Mechanisms , 1996 .

[9]  A. Morreale,et al.  Superimposition-based protocol as a tool for determining bioactive conformations. II. Application to the GABA(A) receptor. , 2001, Journal of molecular graphics & modelling.

[10]  J. Hermens,et al.  Surrogate parameter for the baseline toxicity content of contaminated water: simulating the bioconcentration of mixtures of pollutants and counting molecules. , 1995, Environmental science & technology.

[11]  T Wayne Schultz,et al.  Regression comparisons of Tetrahymena pyriformis and Poecilia reticulata toxicity. , 2002, Chemosphere.

[12]  C. Russom,et al.  Predicting modes of toxic action from chemical structure: Acute toxicity in the fathead minnow (Pimephales promelas) , 1997 .

[13]  M. Crane,et al.  Forecasting the environmental fate and effects of chemicals , 2001 .

[14]  T W Schultz,et al.  Structure-toxicity relationships for selected halogenated aliphatic chemicals. , 1999, Environmental toxicology and pharmacology.

[15]  T. Backhaus,et al.  Predictability of the toxicity of a multiple mixture of dissimilarly acting chemicals to Vibrio fischeri , 2000 .

[16]  Alexander Golbraikh,et al.  Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection , 2002, J. Comput. Aided Mol. Des..

[17]  Monika Nendza,et al.  Discriminating Toxicant Classes by Mode of Action: 2. Physico‐Chemical Descriptors , 2000 .

[18]  A. Grollman,et al.  Genotoxic mechanism for the major acrolein-derived deoxyguanosine adduct in human cells. , 2002, Chemical research in toxicology.

[19]  L. Carlsen,et al.  Partial order ranking-based QSAr's: estimation of solubilities and octanol-water partitioning. , 2001, Chemosphere.

[20]  John D. Walker,et al.  Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances. , 2003, Environmental health perspectives.

[21]  J. Shorter,et al.  Correlation Analysis in Chemistry: Recent Advances , 2012 .

[22]  T. Backhaus,et al.  Predictability of the toxicity of multiple chemical mixtures to Vibrio fischeri: Mixtures composed of similarly acting chemicals , 2000 .

[23]  K. Killham,et al.  Biosensing the acute toxicity of metal interactions: Are they additive, synergistic, or antagonistic? , 2000 .

[24]  Hava T. Siegelmann,et al.  Support Vector Clustering , 2002, J. Mach. Learn. Res..

[25]  R L Lipnick,et al.  A QSAR study of the toxicity of amines to the fathead minnow. , 1991, The Science of the total environment.

[26]  Douglas M. Hawkins,et al.  Assessing Model Fit by Cross-Validation , 2003, J. Chem. Inf. Comput. Sci..

[27]  S. Bradbury,et al.  Quantitative structure-activity relationships and ecological risk assessment: an overview of predictive aquatic toxicology research. , 1995, Toxicology letters.

[28]  N. B. Chapman,et al.  Correlation Analysis in Chemistry , 1978 .

[29]  Joop L. M. Hermens,et al.  The acute toxicity of aldehydes to the guppy , 1988 .

[30]  T. Wayne Schultz,et al.  Structure‐activity relationships for Pimephales and Tetrahymena: A mechanism of action approach , 1997 .

[31]  Keith R Solomon,et al.  New technique for estimating thresholds of toxicity in ecological risk assessment. , 2002, Environmental science & technology.

[32]  P Gramatica,et al.  QSAR and chemometric approaches for setting water quality objectives for dangerous chemicals. , 2001, Ecotoxicology and environmental safety.

[33]  John D. Walker,et al.  Quantitative structure‐activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments , 2003, Environmental toxicology and chemistry.