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Ringeissen, S.; Marrot, L.; Note, R.; Labarussiat, A.; Imbert, S.; Todorov, M.; Mekenyan, O.; Meunier, J.-R. Development of a mechanistic SAR model for the detection of phototoxic chemicals and use in an integrated testing strategy. Toxicol. In Vitro 2011, 25, 324–334.

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Ringeissen, S.; Marrot, L.; Note, R.; Labarussiat, A.; Imbert, S.; Todorov, M.; Mekenyan, O.; Meunier, J.-R. Development of a mechanistic SAR model for the detection of phototoxic chemicals and use in an integrated testing strategy. Toxicol. In Vitro 2011, 25, 324–334.

QDB archive DOI: 10.15152/QDB.139   DOWNLOAD

QsarDB content

Property 3T3_NRU_Phototoxicity: Neural red uptake phototoxicity: P - phototoxic, nP - non-phototoxic

Compounds: 53 | Models: 1 | Predictions: 2

Phototoxicity_window: Acute phototoxicity classifier based on HOMO-LUMO energy gap (EGAP)

Decision tree (classification)

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Name Type n Accuracy
Training set training 50 0.840
Test set external validation 3 0.667

Citing

When using this data, please cite the original article and this QDB archive:

  • Ringeissen, S.; Marrot, L.; Note, R.; Labarussiat, A.; Imbert, S.; Todorov, M.; Mekenyan, O.; Meunier, J.-R. Development of a mechanistic SAR model for the detection of phototoxic chemicals and use in an integrated testing strategy. Toxicol. In Vitro 2011, 25, 324–334. http://dx.doi.org/10.1016/j.tiv.2010.09.017

  • Garcia-Sosa, A. T. QDB archive #139. QsarDB repository, 2015. http://dx.doi.org/10.15152/QDB.139

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Title: Ringeissen, S.; Marrot, L.; Note, R.; Labarussiat, A.; Imbert, S.; Todorov, M.; Mekenyan, O.; Meunier, J.-R. Development of a mechanistic SAR model for the detection of phototoxic chemicals and use in an integrated testing strategy. Toxicol. In Vitro 2011, 25, 324–334.
Abstract: Phototoxicity is of increasing concern in dermatology, since modern lifestyle is often associated with exposure to sunlight. The most commonly reported process is via oxidative reactions. Therefore characterizing the ‘‘photo-pro-oxidant” potential of a compound early in its industrial development is of utmost interest, especially for compounds likely to undergo sunlight exposure in skin. Today there is a need for filtering compounds to be tested in the 3T3 neutral red uptake in vitro test for phototoxicity since testing requires resources. A computational model aiming at predicting the mechanisms that imply the generation of reactive oxygen species was developed using a diverse set of 56 chemicals having 3T3 NRU data. An historical mechanistic (Q)SAR model developed for polycyclic aromatic hydrocarbons was used to derive the new mechanistic model: descriptors were selected upfront to describe the modeled phenomenon. The historical parabolic relationships between phototoxicity and the energy gap (EGAP) between energies of the highest occupied molecular orbital and the lowest unoccupied molecular orbital was confirmed. The model predicts chemicals to be ‘‘phototoxic or photodegradable”, or ‘‘non-phototoxic and non-photodegradable”. A four-step testing strategy is proposed to enable the reduction of experimental testing with the in silico model implemented as a first screen.
URI: http://hdl.handle.net/10967/139
http://dx.doi.org/10.15152/QDB.139
Date: 2015-03-17


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