Investigation and Modeling of the Solubility of Anthracene in Organic Phases

Investigation of the solubility of anthracene can yield potential models to give insights into solvent–solute systems of polyaromaric hydrocarbons (PAHs). This is important in petroleum industries and also fluorescence studies of polyaromatics in organic phases. A five parametric linear QSPR model, based structural/theoretical descriptors of solvents, and a five parametric LSER model using empirical scales, are developed to predict the Ostwald solubility coefficient of anthracene in various organic solvents. Both QSPR and LSER models obtained good prediction quality with covering 84 and 88% of data variance, respectively. The validation process of these models was done using cross validation, y-randomization and external test set. The applicability domain of the proposed model was also calculated using both a Williams plot and the standardization approach. The first model shows the role of some structural features combined with mass, charge and electronegativity of solvents in prediction of anthracene’s Ostwald solubility coefficient in organic phases. In addition, the second, alternative model based on empirical scales reveals the contributions of solvent polarity, polarizability, dielectric constant and acidity parameter to the solubility of anthracene.

[1]  Supratik Kar,et al.  On a simple approach for determining applicability domain of QSAR models , 2015 .

[2]  W. Acree,et al.  Solubility of Pyrene in Organic Nonelectrolyte Solvents. Comparison of Observed Versus Predicted Values Based Upon Mobile Order Theory , 1994 .

[3]  S. Yousefinejad,et al.  On the Solubility of Ferrocene in Nonaqueous Solvents , 2016 .

[4]  Mati Karelson,et al.  The classification of solvents by combining classical QSPR methodology with principal component analysis. , 2005, The journal of physical chemistry. A.

[5]  S. Yousefinejad,et al.  New relationship models for solvent–pyrene solubility based on molecular structure and empirical properties , 2016 .

[6]  M. L. Crossley,et al.  Color and Constitution. , 1924 .

[7]  Scott D. Kahn,et al.  Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships , 2005, Alternatives to laboratory animals : ATLA.

[8]  R. Taft,et al.  AN EXAMINATION OF LINEAR SOLVATION ENERGY RELATIONSHIPS , 2007 .

[9]  Igor V. Tetko,et al.  Neural network studies, 1. Comparison of overfitting and overtraining , 1995, J. Chem. Inf. Comput. Sci..

[10]  J. Stadelhofer,et al.  Anthracene — production and uses , 1988 .

[11]  Consonni,et al.  Chemometrics in QSAR , 2009 .

[12]  W. Acree,et al.  Thermochemical investigations of associated solutions. Part 14.—Calculation of anthracene–butyl acetate association parameters from measured solubility data , 1991 .

[13]  Bahram Hemmateenejad,et al.  A chemometrics approach to predict the dispersibility of graphene in various liquid phases using theoretical descriptors and solvent empirical parameters , 2014 .

[14]  T. Abe Improvements of the Empirical π* Solvent Polarity Scale , 1990 .

[15]  F. Abbasitabar,et al.  New LSER Model Based on Solvent Empirical Parameters for the Prediction and Description of the Solubility of Buckminsterfullerene in Various Solvents , 2013, Journal of Solution Chemistry.

[16]  P. Ruelle,et al.  Prediction of carbazole solubility and its dependence upon the solvent nature , 1994 .

[17]  W. Acree,et al.  Solubility of Xanthene in Organic Nonelectrolyte Solvents: Comparison of Observed Versus Predicted Values Based Upon Mobile Order Theory , 2002 .

[18]  Yonghong Hu,et al.  Thermodynamic Models for Determination of the Solubility of Dibenzothiophene in Different Solvents at Temperatures from (278.15 to 328.15) K , 2014 .

[19]  R. Taft,et al.  Linear solvation energy relationships. Part 1. Solvent polarity–polarizability effects on infrared spectra , 1979 .

[20]  A. N. Díaz,et al.  Analytical applications of 1,10-anthraquinones: A review. , 1991, Talanta.

[21]  Gerta Rücker,et al.  y-Randomization and Its Variants in QSPR/QSAR , 2007, J. Chem. Inf. Model..

[22]  James G. Surles,et al.  Model-Dependent Variance Inflation Factor Cutoff Values , 2002 .

[23]  Michael H. Abraham,et al.  Linear solvation energy relations , 1985 .

[24]  R. Pincock Effects of Nonpolar Solvents on an Ionic Reaction. The Ionic Decomposition of tert-Butylperoxy Formate , 1964 .

[25]  J. Means,et al.  Sorption of polynuclear aromatic hydrocarbons by sediments and soils. , 1980, Environmental science & technology.

[26]  W. E. Acree,et al.  Solubility of Anthracene in Organic Nonelectrolyte Solvents. Comparison of Observed Versus Predicted Values Based Upon Mobile Order Theory , 1999 .

[27]  Paola Gramatica,et al.  On the development and validation of QSAR models. , 2013, Methods in molecular biology.

[28]  S. Yousefinejad,et al.  Structure–electrochemistry relationship in non-aqueous solutions: Predicting the reduction potential of anthraquinones derivatives in some organic solvents , 2015 .

[29]  Polina V. Oliferenko,et al.  A General Treatment of Solubility. 1. The QSPR Correlation of Solvation Free Energies of Single Solutes in Series of Solvents , 2003, J. Chem. Inf. Comput. Sci..

[30]  K. Roy,et al.  Further exploring rm2 metrics for validation of QSPR models , 2011 .

[31]  Roberto Todeschini,et al.  Molecular descriptors for chemoinformatics , 2009 .

[32]  Shuangcheng Ma,et al.  Anti-angiogenic effects of rhubarb and its anthraquinone derivatives. , 2009, Journal of ethnopharmacology.

[33]  Kunal Roy,et al.  Some case studies on application of “rm2” metrics for judging quality of quantitative structure–activity relationship predictions: Emphasis on scaling of response data , 2013, J. Comput. Chem..

[34]  Manuela Pavan,et al.  DRAGON SOFTWARE: AN EASY APPROACH TO MOLECULAR DESCRIPTOR CALCULATIONS , 2006 .

[35]  J. Dearden The History and Development of Quantitative Structure-Activity Relationships (QSARs) , 2016 .

[36]  R. A. McGill,et al.  Determination of olive oil–gas and hexadecane–gas partition coefficients, and calculation of the corresponding olive oil–water and hexadecane–water partition coefficients , 1987 .

[37]  S. Yousefinejad,et al.  Linear solvent structure-polymer solubility and solvation energy relationships to study conductive polymer/carbon nanotube composite solutions , 2015 .

[38]  S. Tucker,et al.  Thermochemical investigations of hydrogen-bonded solutions: development of a predictive equation for the solubility of anthracene in binary hydrocarbon , 1994 .

[39]  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..

[40]  R. Todeschini,et al.  Molecular Descriptors for Chemoinformatics: Volume I: Alphabetical Listing / Volume II: Appendices, References , 2009 .

[41]  Polina V. Oliferenko,et al.  A General Treatment of Solubility. 2. QSPR Prediction of Free Energies of Solvation of Specified Solutes in Ranges of Solvents , 2003, J. Chem. Inf. Comput. Sci..

[42]  Humayun Kabir,et al.  Comparative Studies on Some Metrics for External Validation of QSPR Models , 2012, J. Chem. Inf. Model..

[43]  K. Roy,et al.  Be aware of error measures. Further studies on validation of predictive QSAR models , 2016 .

[44]  L. Brooker,et al.  Color and Constitution. XIII.1 Merocyanines as Solvent Property Indicators2 , 1965 .

[45]  Osama A. Al-Rashed,et al.  Solubility of pyrene in simple and mixed solvent systems , 2009 .

[46]  Paola Gramatica,et al.  External Evaluation of QSAR Models, in Addition to Cross‐Validation: Verification of Predictive Capability on Totally New Chemicals , 2014, Molecular informatics.

[47]  William E. Acree,et al.  Solubility predictions for crystalline nonelectrolyte solutes dissolved in organic solvents based upon the Abraham general solvation model , 2001 .

[48]  J. McCargar,et al.  Thermochemical investigations of associated solutions: 4. Calculation of carbazole-dibutyl ether association constants from measured solubility in binary solvent mixtures. , 1987, Journal of pharmaceutical sciences.

[49]  W. Fawcett Acidity and basicity scales for polar solvents , 1993 .

[50]  S. Yousefinejad,et al.  Chemometrics tools in QSAR/QSPR studies: A historical perspective , 2015 .

[51]  Jean-François Gal,et al.  Linear Solvation Energy Relationships. Part 32. , 1986 .

[52]  W. Acree Polycyclic Aromatic Hydrocarbons: Binary Non-Aqueous Systems Part 1: Solutes A-E , 1995 .

[53]  S. Tucker,et al.  Solubility of Anthracene in Binary p-xylene + Alkane and Benzene + Alkane Solvent Mixtures , 1989 .

[54]  Gregg D. Wilensky,et al.  Neural Network Studies , 1993 .

[55]  P. Gemperline Practical Guide To Chemometrics , 2006 .