Building up a QSAR model for toxicity toward Tetrahymena pyriformis by the Monte Carlo method: A case of benzene derivatives.

Data on toxicity toward Tetrahymena pyriformis is indicator of applicability of a substance in ecologic and pharmaceutical aspects. Quantitative structure-activity relationships (QSARs) between the molecular structure of benzene derivatives and toxicity toward T. pyriformis (expressed as the negative logarithms of the population growth inhibition dose, mmol/L) are established. The available data were randomly distributed three times into the visible training and calibration sets, and invisible validation sets. The statistical characteristics for the validation set are the following: r(2)=0.8179 and s=0.338 (first distribution); r(2)=0.8682 and s=0.341 (second distribution); r(2)=0.8435 and s=0.323 (third distribution). These models are built up using only information on the molecular structure: no data on physicochemical parameters, 3D features of the molecular structure and quantum mechanics descriptors are involved in the modeling process.

[1]  Giuseppina C. Gini,et al.  CORAL: Quantitative structure–activity relationship models for estimating toxicity of organic compounds in rats , 2011, J. Comput. Chem..

[2]  Yue Yu,et al.  In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods. , 2011, Chemosphere.

[3]  A. Kahru,et al.  Toxicity of 58 substituted anilines and phenols to algae Pseudokirchneriella subcapitata and bacteria Vibrio fischeri: comparison with published data and QSARs. , 2011, Chemosphere.

[4]  D. Stuckey,et al.  Toxicity measurement in biological wastewater treatment processes: a review. , 2015, Journal of hazardous materials.

[5]  Jerzy Leszczynski,et al.  CORAL: QSAR modeling of toxicity of organic chemicals towards Daphnia magna , 2012 .

[6]  Judith C. Madden,et al.  In silico toxicology : principles and applications , 2010 .

[7]  David Weininger,et al.  SMILES. 2. Algorithm for generation of unique SMILES notation , 1989, J. Chem. Inf. Comput. Sci..

[8]  Jerzy Leszczynski,et al.  CORAL: Predictions of rate constants of hydroxyl radical reaction using representation of the molecular structure obtained by combination of SMILES and Graph approaches , 2012 .

[9]  F. Burden,et al.  A quantitative structure--activity relationships model for the acute toxicity of substituted benzenes to Tetrahymena pyriformis using Bayesian-regularized neural networks. , 2000, Chemical research in toxicology.

[10]  Tatiana I. Netzeva,et al.  Development and Evaluation of QSARs for Ecotoxic Endpoints: The Benzene Response- Surface Model for Toxicity , 2004 .

[11]  Andrey A Toropov,et al.  Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes. , 2015, Chemosphere.

[12]  E. Benfenati,et al.  Correlation weighting of valence shells in QSAR analysis of toxicity. , 2006, Bioorganic & medicinal chemistry.

[13]  Chang Yu,et al.  Effect of light on toxicity of nanosilver to Tetrahymena pyriformis , 2012, Environmental toxicology and chemistry.

[14]  David Weininger,et al.  SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules , 1988, J. Chem. Inf. Comput. Sci..

[16]  Feng Luan,et al.  Predicting multiple ecotoxicological profiles in agrochemical fungicides: a multi-species chemoinformatic approach. , 2012, Ecotoxicology and environmental safety.

[17]  Humberto González-Díaz,et al.  Entropy model for multiplex drug-target interaction endpoints of drug immunotoxicity. , 2013, Current topics in medicinal chemistry.

[18]  Humberto González-Díaz,et al.  Model for high-throughput screening of drug immunotoxicity--study of the anti-microbial G1 over peritoneal macrophages using flow cytometry. , 2014, European journal of medicinal chemistry.

[19]  Cheng Sun,et al.  Quantitative structure-activity relationships for the inhibition toxicity to root elongation of Cucumis sativus of selected phenols and interspecies correlation with Tetrahymena pyriformis. , 2002, Chemosphere.

[20]  T W Schultz,et al.  Structure-toxicity relationships for benzenes evaluated with Tetrahymena pyriformis. , 1999, Chemical research in toxicology.

[21]  G. Nikolic,et al.  In silico prediction of the β-cyclodextrin complexation based on Monte Carlo method. , 2015, International journal of pharmaceutics.

[22]  Tatiana I Netzeva,et al.  QSARs for the aquatic toxicity of aromatic aldehydes from Tetrahymena data. , 2005, Chemosphere.

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

[24]  Humberto González-Díaz,et al.  ANN multiplexing model of drugs effect on macrophages; theoretical and flow cytometry study on the cytotoxicity of the anti-microbial drug G1 in spleen. , 2012, Bioorganic & medicinal chemistry.

[25]  Jerzy Leszczynski,et al.  Comparison of SMILES and molecular graphs as the representation of the molecular structure for QSAR analysis for mutagenic potential of polyaromatic amines , 2011 .

[26]  M. Hewitt,et al.  Repeatability analysis of the Tetrahymena pyriformis population growth impairment assay , 2011, SAR and QSAR in environmental research.

[27]  M. Abraham,et al.  Toxicity of organic chemicals to Tetrahymena pyriformis: effect of polarity and ionization on toxicity. , 2010, Chemosphere.

[28]  Feng Luan,et al.  In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect. , 2015, Mini reviews in medicinal chemistry.

[29]  Feng Luan,et al.  Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions. , 2014, Environment international.

[30]  Uko Maran,et al.  From data point timelines to a well curated data set, data mining of experimental data and chemical structure data from scientific articles, problems and possible solutions , 2013, Journal of Computer-Aided Molecular Design.

[31]  M. Hewitt,et al.  Assessing Applicability Domains of Toxicological QSARs: Definition, Confidence in Predicted Values, and the Role of Mechanisms of Action , 2007 .

[32]  Jahan B. Ghasemi,et al.  3D-QSAR studies on the toxicity of substituted benzenes to Tetrahymena pyriformis: CoMFA, CoMSIA and VolSurf approaches. , 2014, Ecotoxicology and environmental safety.

[33]  John D. Walker,et al.  Quantitative structure–activity relationships (QSARs) in toxicology: a historical perspective , 2003 .

[34]  Jia He,et al.  Discrimination of excess toxicity from narcotic effect: comparison of toxicity of class-based organic chemicals to Daphnia magna and Tetrahymena pyriformis. , 2013, Chemosphere.

[35]  Luis G Valerio,et al.  In silico toxicology for the pharmaceutical sciences. , 2009, Toxicology and applied pharmacology.

[36]  Jerzy Leszczynski,et al.  QSPR/QSAR analyses by means of the CORAL software: Results, challenges, perspectives , 2015 .

[37]  Andrey A. Toropov,et al.  Prediction of Aquatic Toxicity: Use of Optimization of Correlation Weights of Local Graph Invariants , 2003, J. Chem. Inf. Comput. Sci..

[38]  David Weininger,et al.  SMILES, 3. DEPICT. Graphical depiction of chemical structures , 1990, J. Chem. Inf. Comput. Sci..

[39]  M Cronin Modelling Environmental Fate and Toxicity , 2001, Alternatives to laboratory animals : ATLA.

[40]  E Benfenati,et al.  CORAL: Monte Carlo Method as a Tool for the Prediction of the Bioconcentration Factor of Industrial Pollutants , 2013, Molecular informatics.

[41]  T W Schultz,et al.  Development of quantitative structure-activity relationships for the toxicity of aromatic compounds to Tetrahymena pyriformis: comparative assessment of the methodologies. , 2001, Chemical research in toxicology.

[42]  Xing Yuan,et al.  Classification of toxicity of phenols to Tetrahymena pyriformis and subsequent derivation of QSARs from hydrophobic, ionization and electronic parameters. , 2009, Chemosphere.

[43]  T. W. Schultz,et al.  TETRATOX: TETRAHYMENA PYRIFORMIS POPULATION GROWTH IMPAIRMENT ENDPOINTA SURROGATE FOR FISH LETHALITY , 1997 .

[44]  Anahita Kyani,et al.  Comparative structure-toxicity relationship study of substituted benzenes to Tetrahymena pyriformis using shuffling-adaptive neuro fuzzy inference system and artificial neural networks. , 2008, Chemosphere.

[45]  V. V. Kleandrova,et al.  Computational tool for risk assessment of nanomaterials: novel QSTR-perturbation model for simultaneous prediction of ecotoxicity and cytotoxicity of uncoated and coated nanoparticles under multiple experimental conditions. , 2014, Environmental science & technology.

[46]  A. Niazi,et al.  Prediction of toxicity of nitrobenzenes using ab initio and least squares support vector machines. , 2008, Journal of hazardous materials.