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Articles

Predicting algal growth inhibition toxicity: three-step strategy using structural and physicochemical properties

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Pages 343-362 | Received 17 Feb 2016, Accepted 31 Mar 2016, Published online: 12 May 2016

References

  • United Nations, United Nations Conference on Sustainable Development in 2012: The Future We Want A/RES/66/288 (Chemicals and Waste, Item No. 213), New York, 2012, p. 41. Available at http://www.un.org/ga/search/view_doc.asp?symbol=A/RES/66/288&Lang=E.
  • Division for Sustainable Development Department of Economic and Social Affairs United Nations, Transforming our world: The 2030 Agenda for Sustainable Development (Sustainable Consumption and Production, Goal 12.4), New York, 2015. Available at https://sustainabledevelopment.un.org/index.php?page=view&type=2002&nr=324&menu=35.
  • Ministry of the Environment Government of Japan, Basic Concepts of the Risk Assessment of Priority Assessment Chemical Substances under the Japanese Chemical Substances Control Act (Draft). Available at http://www.env.go.jp/en/chemi/chemicals/chemical_substances_control_act.pdf.
  • Organisation for Economic Co-operation and Development, OECD Guidelines for Testing of Chemicals. Test no. 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test, OECD, Paris, 2006.
  • Organisation for Economic Co-operation and Development, OECD Guidelines for Testing of Chemicals. Test no. 202: Daphnia sp. Acute Immobilisation Test, OECD, Paris, 2004.
  • Organisation for Economic Co-operation and Development, OECD Guidelines for Testing of Chemicals. Test no. 203: Fish Acute Toxicity Test, OECD, Paris, 1992.
  • S.J. Enoch, M.T.D. Cronin, T.W. Schultz, and J.C. Madden, An evaluation of global QSAR models for the prediction of the toxicity of phenols to Tetrahymena pyriformis, Chemosphere 71 (2008), pp. 1225–1232.
  • Ministry of the Environment in Japan, Results of eco-toxicity tests data conducted by Ministry of the Environment in Japan, 2015. Available at http://www.env.go.jp/chemi/sesaku/02e.pdf.
  • A. Furuhama, K. Hasunuma, and Y. Aoki, Interspecies quantitative structure-activity-activity relationships (QSAARs) for prediction of acute aquatic toxicity of aromatic amines and phenols, SAR QSAR Environ. Res. 26 (2015), pp. 301–323.
  • A. Furuhama, K. Hasunuma, and Y. Aoki, Interspecies quantitative structure–activity relationships (QSARs) for eco-toxicity screening of chemicals: The role of physicochemical properties, SAR QSAR Environ. Res. 26 (2015), pp. 809–830; Corrigendum, SAR QSAR Environ. Res. 27 (2016), pp. 245–247.
  • H.J.M. Verhaar, C.J. van Leeuwen, and J.L.M. Hermens, Classifying environmental pollutants. 1: Structure-activity relationships for prediction of aquatic toxicity, Chemosphere 25 (1992), pp. 471–491.
  • H.J.M. Verhaar, J. Solbe, J. Speksnijder, C.J. van Leeuwen, and J.L.M. Hermens, Classifying environmental pollutants: Part 3, External validation of the classification system, Chemosphere 40 (2000), pp. 875–883.
  • S.J. Enoch, M. Hewitt, M.T.D. Cronin, S. Azam, and J.C. Madden, Classification of chemicals according to mechanism of aquatic toxicity: An evaluation of the implementation of the Verhaar scheme in Toxtree, Chemosphere 73 (2008), pp. 243–248.
  • Organisation for Economic Co-operation and Development, OECD Environment health and safety publications series on testing and assessment No. 194, Guidance on grouping of chemicals, 2nd edition, OECD, Paris, 2014.
  • Daylight Chemical Information Systems Inc., Daylight Theory Manual, 4. SMARTSR – A Language for Describing Molecular Patterns. Available at http://www.daylight.com/dayhtml/doc/theory/theory.smarts.html.
  • B.C.P. Council, The Pesticide Manual: A World Compendium, British Crop Protection Council, Alton, UK, 2012.
  • B.C.P. Council, More on the Pesticide Manual: View Supplementary Entries, British Crop Protection Council, UK, 2015. Available at http://www.bcpc.org/page_Supplementary-Entries_102.html.
  • US EPA, Pyridine, ACToR (Aggregated Computational Toxicology Resource). Available at http://actor.epa.gov/actor/GenericChemical?casrn=110-86-1.
  • G. Patlewicz, N. Jeliazkova, R.J. Safford, A.P. Worth, and B. Aleksiev, An evaluation of the implementation of the Cramer classification scheme in the Toxtree software, SAR QSAR Environ. Res. 19 (2008), pp. 495–524.
  • JRC Computational Toxicology, Toxtree; software available at http://toxtree.sourceforge.net.
  • C.J. van Leeuwen, P.T.J. van der Zandt, T. Aldenberg, H.J.M. Verhaar, and J.L.M. Hermens, Application of QSARs, extrapolation and equilibrium partitioning in aquatic effects assessment.1. Narcotic industrial pollutants, Environ. Toxicol. Chem. 11 (1992), pp. 267–282.
  • R.L. Lipnick, K.R. Watson, and A.K. Strausz, A QSAR study of the acute toxicity of some industrial organic chemicals to goldfish, Narcosis, electrophile and proelectrophile mechanisms, Xenobiotica 17 (1987), pp. 1011–1025.
  • V. Aruoja, M. Moosus, A. Kahru, M. Sihtmaee, and U. Maran, Measurement of baseline toxicity and QSAR analysis of 50 non-polar and 58 polar narcotic chemicals for the alga Pseudokirchneriella subcapitata, Chemosphere 96 (2014), pp. 23–32.
  • A.R. Katritzky, V.S. Lobanov, and M. Karelson, Codessa reference manual 2.0, Gainesville, FL, 1994.
  • ACD/LogD, version 2014, Advanced Chemistry Development, Inc., Toronto, ON, Canada. 24. Available at http://www.acdlabs.com/products/percepta/predictors/logd/.
  • M.J.S. Dewar, E.G. Zoebisch, E.F. Healy, and J.J.P. Stewart, Development and use of quantum mechanical molecular models. 76. AM1: A new general purpose quantum mechanical molecular model, J. Am. Chem. Soc. 107 (1985), pp. 3902–3909.
  • J.J.P. Stewart, 1993, MOPAC 7; software available at http://openmopac.net/Downloads/Downloads.html.
  • Molecular Operating Environment (MOE), 2014.0901, Chemical Computing Group Inc., Montreal, 2014.
  • D. Weininger, SMILES, A chemical language and information-system.1. Introduction to methodology and encoding rules, J. Chem. Inf. Comput. Sci. 28 (1988), pp. 31–36.
  • T.A. Halgren, Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94, J. Comput. Chem. 17 (1996), pp. 490–519.
  • T.A. Halgren, MMFF VI. MMFF94s option for energy minimization studies, J. Comput. Chem. 20 (1999), pp. 720–729.
  • US EPA, KOWWINTM program: Estimates the log octanol-water partition coefficient, log KOW, of chemicals using an atom/fragment contribution method, 2010. Available in the EPI SUITETM at https://www.epa.gov/tsca-screening-tools/epi-suitetm-estimation-program-interface.
  • W.M. Meylan and P.H. Howard, Atom/fragment contribution method for estimating octanol-water partition coefficients, J. Pharmaceut. Sci. 84 (1995), pp. 83–92.
  • US EPA, ECOTOXicology knowledgebase (ECOTOX). Available at http://cfpub.epa.gov/ecotox/.
  • Danish EPA, Immobilization Test of Selected Organic Amines with the Crustacean Daphnia magna, Copenhagen, 51p, 1999.
  • R.L. Lipnick, Base-line toxicity predicted by quantitative structure-activity relationships as a probe for molecular mechanism of toxicity, in Probing Bioactive Mechanisms, P. Magee, J.H. Block, and D.R. Henry, eds., American Chemical Society, Washington D. C., 1989, pp. 366–389.
  • P.C. Von der Ohe, R. Kühne, R.U. Ebert, R. Altenburger, M. Liess, and G. Schüürmann, Structural alerts – A new classification model to discriminate excess toxicity from narcotic effect levels of organic compounds in the acute daphnid assay, Chem. Res. Toxicol. 18 (2005), pp. 536–555.
  • V. Aruoja, M. Sihtmäe, H.-C. Dubourguier, and A. Kahru, Toxicity of 58 substituted anilines and phenols to algae Pseudokirchneriella subcapitata and bacteria Vibrio fischeri: Comparison with published data and QSARs, Chemosphere 84 (2011), pp. 1310–1320.
  • US EPA, Carbon tetrachloride, ACToR (Aggregated Computational Toxicology Resource). Available at http://actor.epa.gov/actor/GenericChemical?casrn=56-23-5.
  • C.M. Ellison, J.C. Madden, M.T.D. Cronin, and S.J. Enoch, Investigation of the Verhaar scheme for predicting acute aquatic toxicity: Improving predictions obtained from Toxtree ver. 2.6, Chemosphere 139 (2015), pp. 146–154.
  • H. Akaike, New look at the statistical-model identification, IEEE Trans. Automat. Contr. Ac19 (1974), pp. 716–723.
  • A.O. Aptula and D.W. Roberts, Mechanistic applicability domains for nonanimal-based prediction of toxicological end points: General principles and application to reactive toxicity, Chem. Res. Toxicol. 19 (2006), pp. 1097–1105.
  • T.W. Schultz, K. Rogers, and A.O. Aptula, Read-across to rank skin sensitization potential: Subcategories for the Michael acceptor domain, Contact Dermatitis 60 (2009), pp. 21–31.
  • A.O. Aptula, G. Patlewicz, and D.W. Roberts, Skin sensitization: Reaction mechanistic applicability domains for structure-activity relationships, Chem. Res. Toxicol. 18 (2005), pp. 1420–1426.
  • G. Patlewicz, A.O. Aptula, D.W. Roberts, and E. Uriarte, A minireview of available skin sensitization (Q)SARs/expert systems, QSAR Comb. Sci. 27 (2008), pp. 60–76.
  • A.P. Bearden and T.W. Schultz, Comparison of Tetrahymena and Pimephales toxicity based on mechanism of action, SAR QSAR Environ. Res. 9 (1998), pp. 127–153.
  • T.W. Schultz, T.I. Netzeva, D.W. Roberts, and M.T.D. Cronin, Structure-toxicity relationships for the effects to Tetrahymena pyriformis of aliphatic, carbonyl-containing, alpha, beta-unsaturated chemicals, Chem. Res. Toxicol. 18 (2005), pp. 330–341.
  • T.W. Schultz, R.E. Carlson, M.T.D. Cronin, J.L.M. Hermens, R. Johnson, P.J. O’Brien, D.W. Roberts, A. Siraki, K.B. Wallace, and G.D. Veith, A conceptual framework for predicting the toxicity of reactive chemicals: Modeling soft electrophilicity, SAR QSAR Environ. Res. 17 (2006), pp. 413–428.
  • F. Bajot, M.T.D. Cronin, D.W. Roberts, and T.W. Schultz, Reactivity and aquatic toxicity of aromatic compounds transformable to quinone-type Michael acceptors, SAR QSAR Environ. Res. 22 (2011), pp. 51–65.
  • US EPA, Ecological Structure Activity Relationships (ECOSAR) Predictive Model. Available at http://www.epa.gov/tsca-screening-tools/ecological-structure-activity-relationships-ecosar-predictive-model.
  • Organisation for Economic Co-operation and Development, OECD Environment health and safety publications series on testing and assessment No. 215, Report of the workshop on a framework for the development and use of integrated approaches to testing and assessment, OECD, Paris, 2015.

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