JRC QSAR Model Database models and data

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This collection contains QSAR models listed in the JRC QSAR Model Database that have a sufficient amount of raw data in original scientific article or in the submitted QMRF to establish a QDB archive.

Disclaimer:

The QSARs listed in the JRC QSAR Model Database collection at QsarDB were not developed by the JRC, which makes no claims about their validity, reproducibility and applicability. Please contact the original developers in case of questions.

Explanation of implementation:

The QSARs listed in JRC QSAR Model Database collection at QsarDB were reproduced from research articles or QSAR Model Reporting Format (QMRF) PDF documents or accompanying XLS, XML and SDF source files by the members of QsarDB Team at University of Tartu (Estonia). This means that these models were submitted to the JRC with a sufficient amount of supporting data and the model authors followed best practices of QSAR model reporting. If a model submitted to the JRC QSAR Model Database is not listed in this collection, please contact the QsarDB Team for guidance and assistance (qsardb [at] chem.ut.ee) with a view to implementing the model here.

Reference for JRC QSAR Model Database:

European Commission, Joint Research Centre (2020): JRC QSAR Model Database. European Commission, Joint Research Centre (JRC) [Dataset] PID: https://data.jrc.ec.europa.eu/dataset/e4ef8d13-d743-4524-a6eb-80e18b58cba4

Reference for JRC QSAR Model Database models collection at QsarDB Repository:

JRC QSAR Model Database models collection at QsarDB Repository, 2012-2020, HDL: http://hdl.handle.net/10967/109

Recent Submissions

Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for acute toxicity to Daphnia magna. Q13-31-0060. 2010.

Published: Geven Piir (2020-04-21)

Abstract: This QSAR model corresponds to the QMRF Q13-31-0060 "QSAR for acute toxicity to Daphnia magna" from the JRC QSAR Model Database

EcoTox Regression QMRF
Tulp, I.; Tamm, T.; Dobchev, D.; Martin, D.; Karelson, G.; Jänes, J.; Tämm, K.; Härk, E.; Savchenko, D.; Kreegipuu, A.; Karelson, M. QSAR for the soil adsorption coefficient Koc. Q13-26-0009. 2009.

Published: Geven Piir (2020-04-20)

Abstract: This QSAR model corresponds to the QMRF Q13-26-0009 "QSAR for the soil adsorption coefficient Koc" from the JRC QSAR Model Database

EnvironFate Regression QMRF
Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for human serum albumin binding. Q13-59-0008. Molcode Ltd., 2009.

Published: Geven Piir (2020-04-20)

Abstract: This QSAR model corresponds to the QMRF Q13-59-0008 "QSAR for human serum albumin binding" from the JRC QSAR Model Database

Toxicokinetics Regression QMRF
Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for acute oral toxicity of benzene derivatives - Acute Toxic Class Method. Q13-42-0029. Molcode Ltd., 2009.

Published: Geven Piir (2020-04-17)

Abstract: This QSAR model corresponds to the QMRF Q13-42-0029 "QSAR for acute oral toxicity of benzene derivatives - Acute Toxic Class Method" from the JRC QSAR Model Database

HumanHealth Regression QMRF
Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for rat chronic LOAEL. Q13-414-0035. Molcode Ltd., 2010.

Published: Geven Piir (2020-04-17)

Abstract: This QSAR model corresponds to the QMRF Q13-414-0035 "QSAR for rat chronic LOAEL" from the JRC QSAR Model Database

HumanHealth Regression QMRF
Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for relative binding affinity to estrogen receptor. Q13-418a-0021. Molcode Ltd., 2009.

Published: Geven Piir (2020-04-17)

Abstract: This QSAR model corresponds to the QMRF Q13-418a-0021 "QSAR for relative binding affinity to estrogen receptor" from the JRC QSAR Model Database

HumanHealth Regression QMRF
Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for abiotic degradation in air. Q13-22a-0034. Molcode Ltd., 2010.

Published: Geven Piir (2020-04-17)

Abstract: This QSAR model corresponds to the QMRF Q13-22a-0034 "QSAR for abiotic degradation in air" from the JRC QSAR Model Database

EnvironFate Regression QMRF
Tulp, I.; Tamm, T.; Karelson, G.; Dobchev, D.; Martin, D.; Tämm, K.; Savchenko, D.; Jänes, J.; Härk, E.; Kreegipuu, A.; Karelson, M. QSAR for algae toxicity of benzene derivatives. Q13-32-0028. Molcode Ltd., 2009.

Published: Geven Piir (2020-04-17)

Abstract: This QSAR model corresponds to the QMRF Q13-32-0028 "QSAR for algae toxicity of benzene derivatives" from the JRC QSAR Model Database

EcoTox Regression QMRF
Bajot, F.; Cronin, M. Polar narcosis QSAR for fathead minnow acute toxicity. Q17-33-0032. Liverpool John Moores University, 2009.

Published: Geven Piir (2020-03-13)

Abstract: All compounds are considered to act by polar narcosis. This is well established for non-reactive compounds. Acute lethality is brought about by accumulation in cellular membranes causing their disruption and ultimately death of the organism. The ability of the compound to accumulate in a cellular membrane is thought to be related to its intrinsic hydrophobicity. ...

EcoTox Regression QMRF
Bajot, F.; Cronin, M. Non polar narcosis QSAR for fathead minnow acute toxicity. Q17-33-0030. Liverpool John Moores University, 2009.

Published: Geven Piir (2020-03-12)

Abstract: All compounds are considered to act by non-polar narcosis. This is well established for non-reactive compounds. Acute lethality is brought about by accumulation in cellular membranes causing their disruption and ultimately death of the organism. The ability of the compound to accumulate in a cellular membrane is thought to be related to its intrinsic ...

EcoTox Regression QMRF
Pavan, M.; Worth, A.; Netzeva, T. Preliminary analysis of an aquatic toxicity dataset and assessment of QSAR models for narcosis. EUR 21749 EN. European Commission, Joint Research Centre, 2005.

Published: Geven Piir (2020-03-10)

Abstract: The purpose of the analyses presented in this report was to contribute to an evaluation of the possibility of using QSAR predictions for regulatory purposes. To this end QSAR predictions were compared with SIDS test data. Furthermore, the models were also assessed according to the extent to which they meet OECD principles for QSAR validation (OECD ENV/JM/Mon ...

EcoTox Regression QMRF
Claeys, L.; Iaccino, F.; Janssen, C. R.; Van Sprang, P.; Verdonck, F. Development and validation of a quantitative structure-activity relationship for chronic narcosis to fish. Environ. Toxicol. Chem. 2013, 32, 2217–2225.

Published: Geven Piir (2020-03-06)

Abstract: Abstract Vertebrate testing under the European Union's regulation on Registration, Evaluation, Authorisation and Restriction of Chemical substances (REACH) is discouraged, and the use of alternative nontesting approaches such as quantitative structure?activity relationships (QSARs) is encouraged. However, robust QSARs predicting chronic ecotoxicity of organic ...

EcoTox Regression QMRF
Pérez-Garrido, A.; Helguera, A. M.; López, G. C.; Cordeiro, M. N. D. S.; Escudero, A. G. A topological substructural molecular design approach for predicting mutagenesis end-points of α, β-unsaturated carbonyl compounds. Toxicology 2010, 268, 64–77.

Published: Geven Piir (2020-03-03)

Abstract: Chemically reactive, α, β-unsaturated carbonyl compounds are common environmental pollutants able to produce a wide range of adverse effects, including, e.g. mutagenicity. This toxic property can often be related to chemical structure, in particular to specific molecular substructures or fragments (alerts), which can then be used in specialized software or ...

HumanHealth Regression QMRF
Benigni, R.; Conti, L.; Crebelli, R.; Rodomonte, A.; Vari’, M. R. Simple and α,β-unsaturated aldehydes: Correct prediction of genotoxic activity through structure-activity relationship models. Environ. Mol. Mutagen. 2005, 46, 268–280.

Published: Geven Piir (2020-02-28)

Abstract: Aldehydes are widespread environmental and industrial compounds, able to stimulate a range of adverse health effects (e.g., general toxicity, allergenic reactions, mutagenicity, and carcinogenicity). We have previously presented quantitative structure–activity relationships (QSARs) for the genotoxicity of simple and α,β‐unsaturated aliphatic aldehydes. In this ...

HumanHealth Regression QMRF
Pérez-Garrido, A.; González, M. P.; Escudero, A. G. Halogenated derivatives QSAR model using spectral moments to predict haloacetic acids (HAA) mutagenicity. Bioorg. Med. Chem. 2008, 16, 5720–5732.

Published: Geven Piir (2020-02-18)

Abstract: The risk of the presence of haloacetic acids in drinking water as chlorination by-products and the shortage of experimental mutagenicity data for most of them requires a research work. This paper describes a QSAR model to predict direct mutagenicity for these chemicals. The model, able to describe more than 90% of the variance in the experimental activity, was ...

HumanHealth Regression QMRF
Roy, P. P.; Kovarich, S.; Gramatica, P. QSAR model reproducibility and applicability: A case study of rate constants of hydroxyl radical reaction models applied to polybrominated diphenyl ethers and (benzo-)triazoles. Journal of Computational Chemistry 2011, 32, 2386–2396.

Published: Iiris Kahn (2016-09-05)

Abstract: The crucial importance of the three central OECD principles for quantitative structure-activity relationship (QSAR) model validation is highlighted in a case study of tropospheric degradation of volatile organic compounds (VOCs) by OH, applied to two CADASTER chemical classes (PBDEs and (benzo-)triazoles). The application of any QSAR model to chemicals without ...

EnvironFate Regression QMRF
Gramatica, P.; Chirico, N.; Papa, E.; Cassani, S.; Kovarich, S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. Journal of Computational Chemistry 2013, 34, 2121–2132.

Published: Iiris Kahn (2016-08-22)

Abstract: QSARINS (QSAR-INSUBRIA) is a new software for the development and validation of multiple linear regression Quantitative Structure-Activity Relationship (QSAR) models by Ordinary Least Squares method and Genetic Algorithm for variable selection. This program is mainly focused on the external validation of QSAR models. Various tools for explorative analysis of ...

Regression QMRF
Gramatica, P.; Cassani, S.; Chirico, N. QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS. J. Comput. Chem. 2014, 35, 1036–1044.

Published: Geven Piir (2016-02-26)

Abstract: A database of environmentally hazardous chemicals, collected and modeled by QSAR by the Insubria group, is included in the updated version of QSARINS, software recently proposed for the development and validation of QSAR models by the genetic algorithm-ordinary least squares method. In this version, a module, named QSARINS-Chem, includes several datasets of ...

PhysChem EnvironFate EcoTox HumanHealth Regression QMRF
Austin, T.J.; Eadsforth, C.V. Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. SAR QSAR Environ. Res. 2014, 25, 147–160.

Published: Iiris Kahn (2015-03-31)

Abstract: To comply with the REACH (Registration, Evaluation, Authorisation and restriction of Chemicals) regulations, the generation of chronic fish toxicity data is required for chemicals produced or imported within or into the EU in quantities greater than 100 tonnes per year. This comes at a great cost to industry and consumers alike and requires the sacrifice of ...

EcoTox Regression QMRF
Franke, R.; Gruska, A.; Giuliani, A.; Benigni, R. Prediction of rodent carcinogenicity of aromatic amines: a quantitative structure-activity relationships model. Carcinogenesis 2001, 22, 1561–1571.

Published: Alfonso T. Garcia-Sosa (2015-03-23)

Abstract: The aromatic amines are widely used industrial chemicals and can be found in tobacco smoke as well as in products generated during cooking. In a previous study, we established quantitative structure–activity relationship (QSAR) models linking the carcinogenic potency of non- heterocyclic carcinogenic aromatic amines to a series of molecular determinants. ...

HumanHealth Regression QMRF

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JRC QSAR Model Database models and data

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