QSPR-based estimation of the half-lives for polychlorinated biphenyl congeners

References

• WHO, Polychlorinated biphenyls: human health aspects, Concise International Chemical Assessment Document 55, World Health Organization, Geneva, Switzerland, 2003. Available at http://www.who.int/ipcs/publications/cicad/en/cicad55.pdf
   Google Scholar
• UNEP, Stockholm Convention on Persistent Organic Pollutants, United Nations Environment Programme, Geneva, Switzerland, 2001. Available at http://chm.pops.int/Portals/0/Repository/conf/UNEP–POPS–CONF–4–AppendixII.5206ab9e–ca67–42a7–afee–9d90720553c8.pdf
   Google Scholar
• Wania , F and Mackay , D . 1995 . A global distribution model for persistent organic chemicals . Sci. Total Environ. , 160–161 : 211 – 232 .
   Web of Science ®Google Scholar
• van der Oost , R , Beyer , J and Vermeulen , NPE . 2003 . Fish bioaccumulation and biomarkers in environmental risk assessment: A review . Environ. Toxicol. Pharmacol. , 13 : 57 – 149 .
   PubMed Web of Science ®Google Scholar
• Larsson , P and Soedergren , A . 1987 . Transport of polychlorinated biphenyls (PCBs) in freshwater mesocosms from sediment to water and air . Water, Air, Soil Pollut. , 36 : 33 – 46 .
   Web of Science ®Google Scholar
• Ozcelik , B , Uygun , U and Bayram , B . 2011 . “ Seafoods and environmental contaminants ” . In Handbook of Seafood Quality, Safety and Health Applications , Edited by: Alasalvar , C , Shahidi , F , Miyashita , K and Wanasundara , U . Chichester , , UK : Wiley–Blackwell .
   Google Scholar
• CEMN, Development and Application of Models of Chemical Fate in Canada; Modelling Guidance Document No 200501, Canadian Environmental Modelling Network, Trent University, Peterborough, Ontario, 2005. Available at http://www.trentu.ca/academic/aminss/envmodel/CEMNReport200501.pdf
   Google Scholar
• Geyer , H , Rimkus , G , Scheunert , I , Kaune , A , Schramm , KW , Kettrup , A , Zeeman , M , Muir , D , Hansen , L and Mackay , D . 2000 . “ Bioaccumulation and occurrence of endocrine-disrupting chemicals (EDCs), persistent organic pollutants (POPs), and other organic compounds in fish and other organisms including humans ” . In Bioaccumulation – New Aspects and Developments , Edited by: Beek , B . Berlin/Heidelberg : Springer .
   Google Scholar
• Sinkkonen , S and Paasivirta , J . 2000 . Degradation half-life times of PCDDs, PCDFs and PCBs for environmental fate modeling . Chemosphere , 40 : 943 – 949 .
   PubMed Web of Science ®Google Scholar
• Callahan , MA , Slimak , MW , Gabel , NW , May , IP , Fowler , CF , Freed , JR , Jennings , P , Durfee , RL , Whitmore , FC , Maestri , B , Mabey , WR , Holt , BR and Gould , C . Water-related environmental fate of 129 priority pollutants, Environmental Protection Agency (EPA 440/4–79–029a), Washington, DC, US, 1979
   Google Scholar
• Leifer , A , Brink , RH , Thom , GC and Partymiller , KG . 1983 . Environmental transport and transformation of polychlorinated biphenyls , Washington, DC , , US : Environmental Protection Agency, Office of Pesticides and Toxic Substances .
   Google Scholar
• Buckman , AH , Brown , SB , Hoekstra , PF and Fisk , AT . 2004 . Toxicokinetics of three polychlorinated biphenyl technical mixtures in rainbow trout (Oncorhynchus mykiss) . Environ. Toxicol. Chem. , 23 : 1725 – 1736 .
   PubMed Web of Science ®Google Scholar
• Cronin , MTD . 2010 . “ Quantitative structure–activity relationships (qsars)–applications and methodology ” . In Recent Advances in QSAR Studies; Methods and Applications , Edited by: Puzyn , T , Leszczynski , J and Cronin , MTD . 3 – 11 . New York : Springer .
   Google Scholar
• EC, Regulation (EC) No 1907/2006 of the European parliament and of the council of 18 December, OJ L 396, 30 December 2006; Available at http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:396:0001:0849:EN:PDF
   Google Scholar
• Qin , LT , Liu , SS , Liu , HL and Ge , HL . 2008 . A new predictive model for the bioconcentration factors of polychlorinated biphenyls (PCBs) based on the molecular electronegativity distance vector (MEDV) . Chemosphere , 70 : 1577 – 1587 .
   PubMed Web of Science ®Google Scholar
• Sabljic , A , Guesten , H , Hermens , J and Opperhuizen , A . 1993 . Modeling octanol/water partition coefficients by molecular topology: Chlorinated benzenes and biphenyls . Environ. Sci. Technol. , 27 : 1394 – 1402 .
   Web of Science ®Google Scholar
• Zhou , W , Zhai , Z , Wang , Z and Wang , L . 2005 . Estimation of n-octanol/water partition coefficients (Kow) of all PCB congeners by density functional theory . J. Mol. Struct. Theochem , 755 : 137 – 145 .
   Web of Science ®Google Scholar
• Ruiz , P , Faroon , O , Moudgal , CJ , Hansen , H , De Rosa , CT and Mumtaz , M . 2008 . Prediction of the health effects of polychlorinated biphenyls (PCBs) and their metabolites using quantitative structure–activity relationship (QSAR) . Toxicol. Lett. , 181 : 53 – 65 .
   PubMed Web of Science ®Google Scholar
• Arnot , JA , Meylan , W , Tunkel , J , Howard , PH , Mackay , D , Bonnell , M and Boethling , RS . 2009 . A quantitative structure–activity relationship for predicting metabolic biotransformation rates for organic chemicals in fish . Environ. Toxicol. Chem. , 28 : 1168 – 1177 .
   PubMed Web of Science ®Google Scholar
• Fatemi , MH and Baher , E . 2009 . A novel quantitative structure–activity relationship model for prediction of biomagnification factor of some organochlorine pollutants . Mol. Diversity , 13 : 343 – 352 .
   PubMed Web of Science ®Google Scholar
• Wang , L , Liu , XH , Wu , D , Xu , MZ , Sun , T , Cui , BS and Yang , ZF . 2009 . Modelling the depuration rates of polychlorinated biphenyls in Oncorhynchus mykiss with quantum chemical descriptors . SAR QSAR Environ. Res. , 20 : 91 – 101 .
   PubMed Web of Science ®Google Scholar
• Li , X , Fang , L , Huang , J and Yu , G . 2008 . Photolysis of mono- through deca-chlorinated biphenyls by ultraviolet irradiation in n-hexane and quantitative structure–property relationship analysis . J. Environ. Sci. , 20 : 753 – 759 .
   Web of Science ®Google Scholar
• Niu , JF , Yang , ZF , Shen , ZY and Wang , LL . 2006 . QSPRs for the prediction of photodegradation half-life of PCBs in n-hexane . SAR QSAR Environ. Res. , 17 : 173 – 182 .
   PubMed Web of Science ®Google Scholar
• Todeschini , R , Consonni , V , Mauri , A and Pavan , M . 2003 . DRAGON software version 3.0 , TALETE srl, Milan, Italy : Milano Chemometrics and QSAR Research Group . Software available at http://www.disat.unimib.it/chm
   Google Scholar
• Hagan , MT , Demuth , HB and Beale , M . 1996 . Neural Network Design , Boston : PWS .
   Google Scholar
• Daqi , G and Yan , J . 2005 . Classification methodologies of multilayer perceptrons with sigmoid activation functions . Pattern Recognit. , 38 : 1469 – 1482 .
   Web of Science ®Google Scholar
• STATISTICA (data analysis software system), StatSoft. Inc., Tulsa, 2004. Software available at http://www.statsoft.com
   Google Scholar
• Vapnik , VN . 1998 . Statistical Learning Theory , New York , , USA : John Wiley and Sons .
   Google Scholar
• Nord , LI and Jacobsson , SP . 1998 . A novel method for examination of the variable contribution to computational neural network models . Chemom. Intell. Lab. Syst. , 44 : 153 – 160 .
   Web of Science ®Google Scholar
• Roy , K . 2007 . On some aspects of validation of predictive quantitative structure–activity relationship models . Expert Opin. Drug Discovery , 2 : 1567 – 1577 .
   PubMed Web of Science ®Google Scholar
• Rücker , C , Rücker , G and Meringer , M . 2007 . Y-randomization and its variants in QSPR/QSAR . J. Chem. Inf. Model. , 47 : 2345 – 2357 .
   PubMed Web of Science ®Google Scholar
• Todeschini , R and Consonni , V . 2009 . Handbook of Molecular Descriptors for Chemoinformatics , Weinheim : Wiley–VCH Verlag GmbH & Co. KGaA .
   Google Scholar
• Galvez , J , Garcia , R , Salabert , MT and Soler , R . 1994 . Charge Indexes. New Topological Descriptors . J. Chem. Inf. Comput. Sci. , 34 : 520 – 525 .
   Google Scholar
• Broto , P , Moreau , G and Vandycke , C . 1984 . Molecular Structures: Perception, Autocorrelation Descriptor and SAR Studies. Use of the Autocorrelation Descriptors in the QSAR Study of Two Non-Narcotic Analgesic Series . Eur. J. Med. Chem. , 19 : 79 – 84 .
   Web of Science ®Google Scholar