Application of chemical reaction mechanistic domains to an ecotoxicity QSAR model, the KAshinhou Tool for Ecotoxicity (KATE)

References

• Report of the World Summit on Sustainable Development: Johannesburg, South Africa, 26 August–4 September 2002 (with corrigendum), United Nations, 2003. Available at http://www.johannesburgsummit.org/html/documents/documents.html
   Google Scholar
• Parliament Adopts REACH: New EU Chemicals Legislation and New Chemicals Agency, 2006. Available at: http://www.europarl.europa.eu/sides/getDoc.do?language=EN&type=IM-PRESS&reference=20061213IPR01493
   Google Scholar
• Act on the Evaluation of Chemical Substances and Regulation of their Manufacture, etc. (CSCL), 2010. Available at: http://www.meti.go.jp/policy/chemical_management/english/cscl.html
   Google Scholar
• OECD Quantitative Structure–Activity Relationships [(Q)SARs] Project. Available at: http://www.oecd.org/document/23/0,3343,en_2649_34379_33957015_1_1_1_1,00.htm
   Google Scholar
• T. Netzeva, P. Manuela, and W. Andrew, Review of Data Sources, QSARs and Integrated Testing Strategies for Aquatic Toxicity, European Commission Joint Research Centre, 2007. Available at: http://ecb.jrc.ec.europa.eu/DOCUMENTS/QSAR/EUR_22943_EN.pdf
   Google Scholar
• OECD Environment Health and Safety Publications Series on Testing and Assessment, No. 69, Guidance Document on the Validation of (Quantitative) Structure–Activity Relationships [(Q)SAR] Models, Paris, 2007. Available at http://www.oecd.org/dataoecd/55/35/38130292.pdf
   Google Scholar
• Netzeva , TI , Worth , AP , Aldenberg , T , Benigni , R , Cronin , MTD , Gramatica , P , Jaworska , JS , Kahn , S , Klopman , G , Marchant , CA , Myatt , G , Nikolova-Jeliazkova , N , Patlewicz , GY , Perkins , R , Roberts , DW , Schultz , TW , Stanton , DT , van de Sandt , JJM , Tong , WD , Veith , G and Yang , CH . 2005 . Current status of methods for defining the applicability domain of (quantitative) structure–activity relationships: Report and recommendations of ECVAM Workshop 52, ATLA . Altern. Lab. Anim. , 33 : 155 – 173 .
   PubMed Web of Science ®Google Scholar
• Eriksson , L , Jaworska , J , Worth , AP , Cronin , MTD , McDowell , RM and Gramatica , P . 2003 . Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs . Environ. Health Persp. , 111 : 1361 – 1375 .
   PubMed Web of Science ®Google Scholar
• Jaworska , J , Nikolova-Jeliazkova , N and Aldenberg , T . 2005 . QSAR applicability domain estimation by projection of the training set in descriptor space: A review, ATLA . Altern. Lab. Anim. , 33 : 445 – 459 .
   PubMed Web of Science ®Google Scholar
• Netzeva , TI , Saliner , AG and Worth , AP . 2006 . Comparison of the applicability domain of a quantitative structure–activity relationship for estrogenicity with a large chemical inventory . Environ. Toxicol. Chem. , 25 : 1223 – 1230 .
   PubMed Web of Science ®Google Scholar
• Boethling , RS and Costanza , J . 2010 . Domain of EPI suite biotransformation models . SAR QSAR Environ. Res. , 21 : 415 – 443 .
   PubMed Web of Science ®Google Scholar
• Mekenyan , OG , Dimitrov , SD , Pavlov , TS and Veith , GD . 2004 . A systematic approach to simulating metabolism in computational toxicology: I. The TIMES heuristic modelling framework . Curr. Pharm. Des. , 10 : 1273 – 1293 .
   PubMed Web of Science ®Google Scholar
• Dimitrov , S , Dimitrova , G , Pavlov , T , Dimitrova , N , Patlewicz , G , Niemela , J and Mekenyan , O . 2005 . A stepwise approach for defining the applicability domain of SAR and QSAR models . J. Chem. Inf. Model. , 45 : 839 – 849 .
   PubMed Web of Science ®Google Scholar
• Furuhama , A , Toida , T , Nishikawa , N , Aoki , Y , Yoshioka , Y and Shiraishi , H . 2010 . Development of an ecotoxicity QSAR model for the KAshinhou Tool for Ecotoxicity (KATE) system, March 2009 version . SAR QSAR Environ. Res. , 21 : 403 – 413 .
   PubMed Web of Science ®Google Scholar
• KATE: It should be noted that the prediction results provided by the KATE system do not guarantee satisfactory prediction accuracy. It should be regarded as a tool for obtaining reference figures for the extent of the ecotoxicity impact of a chemical substance. Furthermore, the results may not be used for MoE submissions in compliance with the CSCL, 2009. Available at http://kate.nies.go.jp
   Google Scholar
• Aptula , AO , Patlewicz , G and Roberts , DW . 2005 . Skin sensitization: Reaction mechanistic applicability domains for structure–activity relationships . Chem. Res. Toxicol. , 18 : 1420 – 1426 .
   PubMed Web of Science ®Google Scholar
• Hermens , JLM . 1990 . Electrophiles and acute toxicity to fish . Environ. Health Perspect. , 87 : 219 – 225 .
   PubMed Web of Science ®Google Scholar
• Aptula , AO and Roberts , DW . 2006 . Mechanistic applicability domains for nonanimal-based prediction of toxicological end points: General principles and application to reactive toxicity . Chem. Res. Toxicol. , 19 : 1097 – 1105 .
   PubMed Web of Science ®Google Scholar
• Roberts , DW , Patlewicz , G , Kern , PS , Gerberick , F , Kimber , I , Dearman , RJ , Ryan , CA , Basketter , DA and Aptula , AO . 2007 . Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization . Chem. Res. Toxicol. , 20 : 1019 – 1030 .
   PubMed Web of Science ®Google Scholar
• Dimitrov , SD , Low , LK , Patlewicz , GY , Kern , PS , Dimitrova , GD , Comber , MHI , Phillips , RD , Niemela , J , Bailey , PT and Mekenyan , OG . 2005 . Skin sensitization: Modeling based on skin metabolism simulation and formation of protein conjugates . Int. J. Toxicol. , 24 : 189 – 204 .
   PubMed Web of Science ®Google Scholar
• Jowsey , IR , Basketter , DA , Westmoreland , C and Kimber , I . 2006 . A future approach to measuring relative skin sensitising potency: A proposal . J. Appl. Toxicol. , 26 : 341 – 350 .
   PubMed Web of Science ®Google Scholar
• Grindon , C , Combes , R , Cronin , MTD , Roberts , DW and Garrod , JF . 2007 . An integrated decision-tree testing strategy for skin sensitisation with respect to the requirements of the EU REACH legislation, ATLA . Altern. Lab. Anim. , 35 : 683 – 697 .
   PubMed Web of Science ®Google Scholar
• Patlewicz , G , Aptula , AO , Roberts , DW and Uriarte , E . 2008 . A minireview of available skin sensitization (Q)SARs/expert systems . QSAR Comb. Sci. , 27 : 60 – 76 .
   Google Scholar
• Vandebriel , RJ and van Loveren , H . 2010 . Non-animal sensitization testing: State-of-the-art . Crit. Rev. Toxicol. , 40 : 389 – 404 .
   PubMed Web of Science ®Google Scholar
• Enoch , SJ , Madden , JC and Cronin , MTD . 2008 . Identification of mechanisms of toxic action for skin sensitisation using a SMARTS pattern based approach . SAR QSAR Environ. Res. , 19 : 555 – 578 .
   PubMed Web of Science ®Google Scholar
• Daylight Chemical Information Systems Inc., Daylight Theory Manual: 4. SMARTS® – A Language for Describing Molecular Patterns. Available at http://www.daylight.com/dayhtml/doc/theory/theory.smarts.html
   Google Scholar
• Weininger , D . 1988 . SMILES, A chemical language and information system: 1. Introduction to methodology and encoding rules . J. Chem. Inf. Comp. Sci. , 28 : 31 – 36 .
   Google Scholar
• Yoshioka , Y . 2008 . Know-how in the development of a program for QSAR platform, PAS: Part 1. Extract the component from the SMILES notation (in Japanese) . Jpn. J. Environ. Toxicol. , 11 : 33 – 40 .
   Google Scholar
• Yoshioka , Y . 2009 . Know-how in the development of a program for QSAR platform, PAS: Part 2. Drawing method of chemical structure (in Japanese) . Jpn. J. Environ. Toxicol. , 12 : 107 – 112 .
   Google Scholar
• Yoshioka , Y . 2009 . Know-how in the development of a program for QSAR platform, PAS: Part 3. An extraction method of partial structure (in Japanese) . Jpn. J. Environ. Toxicol. , 12 : 113 – 122 .
   Google Scholar
• Lipnick , RL , Johnson , DE , Gilford , JH , Bickings , CK and Newsome , LD . 1985 . Comparison of fish toxicity screening data for 55 alcohols with the quantitative structure–activity relationship predictions of minimum toxicity for nonreactive nonelectrolyte organic compounds . Environ. Toxicol. Chem. , 4 : 281 – 296 .
   Web of Science ®Google Scholar
• Lipnick , RL . 1989 . Narcosis, electrophile and proelectrophile toxicity mechanisms: Application of SAR and QSAR . Environ. Toxicol. Chem. , 8 : 1 – 12 .
   Web of Science ®Google Scholar
• MoE, Japan ecotoxicity test data, 2009. Available at http://www.env.go.jp/chemi/sesaku/02e.pdf
   Google Scholar
• US EPA fathead minnow database. Available at http://www.epa.gov/med/Prods_Pubs/fathead_minnow.htm
   Google Scholar
• Russom , CL , Bradbury , SP , Broderius , SJ , Hammermeister , DE and Drummond , RA . 1997 . Predicting modes of toxic action from chemical structure: Acute toxicity in the fathead minnow (Pimephales promelas) . Environ. Toxicol. Chem. , 16 : 948 – 967 .
   Web of Science ®Google Scholar
• Netzeva , TI , Pavan , M and Worth , AP . 2008 . Review of (quantitative) structure–activity relationships for acute aquatic toxicity . QSAR Comb. Sci. , 27 : 77 – 90 .
   Google Scholar
• OECD, OECD Environment Monographs No. 58, Report of the OECD workshop on quantitative structure activity relationships (QSARs) in aquatic effects assessment, Paris, 1992. Available at http://www.oecd.org/dataoecd/19/27/35220377.pdf
   Google Scholar
• Verhaar , HJM , van Leeuwen , CJ and Hermens , JLM . 1992 . Classifying environmental pollutants: 1. Structure–activity relationships for prediction of aquatic toxicity . Chemosphere , 25 : 471 – 491 .
   Web of Science ®Google Scholar
• Cronin , MTD and Dearden , JC . 1995 . QSAR in toxicology: 1. Prediction of aquatic toxicity . Quant. Struct.–Act. Rel. , 14 : 1 – 7 .
   Web of Science ®Google Scholar
• Verhaar , HJM , Ramos , EU and Hermens , JLM . 1996 . Classifying environmental pollutants: 2. Separation of class 1 (baseline toxicity) and class 2 ('polar narcosis') type compounds based on chemical descriptors . J. Chemom. , 10 : 149 – 162 .
   Web of Science ®Google Scholar
• Verhaar , HJM , Solbe , J , Speksnijder , J , van Leeuwen , CJ and Hermens , JLM . 2000 . Classifying environmental pollutants: Part 3. External validation of the classification system . Chemosphere , 40 : 875 – 883 .
   PubMed Web of Science ®Google Scholar
• Bradbury , SP , Russom , CL , Ankley , GT , Schultz , TW and Walker , JD . 2003 . Overview of data and conceptual approaches for derivation of quantitative structure–activity relationships for ecotoxicological effects of organic chemicals . Environ. Toxicol. Chem. , 22 : 1789 – 1798 .
   PubMed Web of Science ®Google Scholar
• ECOSAR, 2009. Available at http://www.epa.gov/oppt/newchems/tools/21ecosar.htm
   Google Scholar
• G.D. Veith and S.J. Broderius, Rules for distinguishing toxicants that cause type-I and type-II narcosis syndromes, Environ. Health Perspect. 87 (1990), pp. 207–211
   Google Scholar
• KOWWIN. Available at http://www.epa.gov/opptintr/exposure/pubs/episuite.htm
   Google Scholar
• EPISuite. Available at http://www.epa.gov/oppt/exposure/pubs/episuite.htm
   Google Scholar
• Hulzebos , EM and Posthumus , R . 2003 . (Q)SARs: Gatekeepers against risk on chemicals? . SAR QSAR Environ. Res. , 14 : 285 – 316 .
   PubMed Web of Science ®Google Scholar
• Schultz , TW and Cronin , MTD . 2003 . Essential and desirable characteristics of ecotoxicity quantitative structure–activity relationships . Environ. Toxicol. Chem. , 22 : 599 – 607 .
   PubMed Web of Science ®Google Scholar
• von der Ohe , PC , Kühne , R , Ebert , RU , Altenburger , R , Liess , M and Schüürmann , G . 2005 . 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 : 536 – 555 .
   PubMed Web of Science ®Google Scholar
• Veith , GD , Call , DJ and Brooke , LT . 1983 . Structure toxicity relationships for the fathead minnow, Pimephales promelas: Narcotic industrial chemicals . Can. J. Chem. , 40 : 743 – 748 .
   Web of Science ®Google Scholar
• van Leeuwen , CJ , van der Zandt , PTJ , Aldenberg , T , Verhaar , HJM and Hermens , JLM . 1992 . Application of QSARs, extrapolation and equilibrium partitioning in aquatic effects assessment: 1. Narcotic industrial pollutants . Environ. Toxicol. Chem. , 11 : 267 – 282 .
   Web of Science ®Google Scholar
• Hidaka , S , Shiraishi , H , Ohmayu , Y , Yamasaki , H , Okamoto , K , Kawashita , N , Yasunaga , T and Takagi , T . 2010 . Ecotoxicity prediction using 3D descriptors . J. Comput.-Aided Chem. , 11 : 11 – 18 .
   Google Scholar