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EC number: 234-207-4 | CAS number: 10595-80-9
- Life Cycle description
- Uses advised against
- Endpoint summary
- Appearance / physical state / colour
- Melting point / freezing point
- Boiling point
- Density
- Particle size distribution (Granulometry)
- Vapour pressure
- Partition coefficient
- Water solubility
- Solubility in organic solvents / fat solubility
- Surface tension
- Flash point
- Auto flammability
- Flammability
- Explosiveness
- Oxidising properties
- Oxidation reduction potential
- Stability in organic solvents and identity of relevant degradation products
- Storage stability and reactivity towards container material
- Stability: thermal, sunlight, metals
- pH
- Dissociation constant
- Viscosity
- Additional physico-chemical information
- Additional physico-chemical properties of nanomaterials
- Nanomaterial agglomeration / aggregation
- Nanomaterial crystalline phase
- Nanomaterial crystallite and grain size
- Nanomaterial aspect ratio / shape
- Nanomaterial specific surface area
- Nanomaterial Zeta potential
- Nanomaterial surface chemistry
- Nanomaterial dustiness
- Nanomaterial porosity
- Nanomaterial pour density
- Nanomaterial photocatalytic activity
- Nanomaterial radical formation potential
- Nanomaterial catalytic activity
- Endpoint summary
- Stability
- Biodegradation
- Bioaccumulation
- Transport and distribution
- Environmental data
- Additional information on environmental fate and behaviour
- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
- Long-term toxicity to fish
- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
- Toxicity to aquatic plants other than algae
- Toxicity to microorganisms
- Endocrine disrupter testing in aquatic vertebrates – in vivo
- Toxicity to other aquatic organisms
- Sediment toxicity
- Terrestrial toxicity
- Biological effects monitoring
- Biotransformation and kinetics
- Additional ecotoxological information
- Toxicological Summary
- Toxicokinetics, metabolism and distribution
- Acute Toxicity
- Irritation / corrosion
- Sensitisation
- Repeated dose toxicity
- Genetic toxicity
- Carcinogenicity
- Toxicity to reproduction
- Specific investigations
- Exposure related observations in humans
- Toxic effects on livestock and pets
- Additional toxicological data
Genetic toxicity: in vitro
Administrative data
- Endpoint:
- in vitro gene mutation study in bacteria
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with adequate and reliable documentation / justification
- Justification for type of information:
- 1. SOFTWARE: Vega Application (version 1.1.4)
2. MODEL (incl. version number): CAESAR Mutagenicity model (version 2.1.13)
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL:
Structural formula: C6H10O5S
a. SMILES: O=C(OCCS(=O)(=O)O)C(=C)C
b. InChI: InChI=1S/C6H10O5S/c1-5(2)6(7)11-3-4-12(8,9)10/h1,3-4H2,2H3,(H,8,9,10)
c. Other structural representation: mol file used and included in the test material information.
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: Mutagenicity - microbial in vitro Salmonella
- Unambiguous algorithm: Integrated model arranged cascading two models, a trained Support Vector Machine (SVM) classifier, and an additional model for false negatives (FNs) removal based on Structural Alerts (SAs) matching (please see attached QMRF for further details)
- Defined domain of applicability: The applicability domain of predictions was assessed using an Applicability Domain Index (ADI) that has values from 0 (not reliable) to 1 (fully reliable). The ADI is calculated by grouping several other indices, each one taking into account a particular issue of the applicability domain, i.e. similar molecules with known experimental value, accuracy of prediction for similar molecules, concordance for similar molecules, model descriptors range check and Atom Centered Fragments (ACF) similarity check. In more details: ADI > 0.9 (target compound is into model AD), ADI < 0.7 (target compound is out model AD), 0.7 < ADI < 0.9 (target compound could be out of model AD and further analysis is needed).
- Appropriate measures of goodness-of-fit and robustness and predictivity: please see attached QMRF.
- Mechanistic interpretation: The model includes SAs to identify toxic compounds, according to the mechanistic basis described by the Benigni-Bossa rules. In addition a stochastic model is included, to provide basis also for negative results.
5. APPLICABILITY DOMAIN
The ADI value calculated for 2-SEM is equal to 0.89, meaning that the target compound could be out of the applicability domain of the model. The global ADI was based on: Similarity index = 0.79 (not optimal), Accuracy index = 1 (good), Concordance index = 1 (good), Descriptors range check = True (good), ACF index = 1 (good).
- Descriptor domain: descriptors for the target compound have values inside the descriptor range of the compounds of the training set.
- Structural fragment domain: all atom centered fragments of the target compound have been found in the compounds of the training set.
- Mechanism domain: no structural alerts related to mutagenicity or suspect mutagenicity (Benigni/Bossa structural alerts) have been found in the target compound.
Overall, it was concluded that the target 2-SEM is included in the applicability domain of the model.
- Similarity with analogues in the training set: A similarity index equal to 0.79 was derived, meaning that moderately similar compounds are included in the training set. The three most similar compounds from the training set exhibited moderate similarity with respect to the target 2-SEM (similarity indices in the range 0.78-0.81), negative experimental values, and good prediction accuracy. Please see attached QPRF for structural analogues and further details.
6. ADEQUACY OF THE RESULT
The target 2-SEM was predicted negative for bacterial in vitro mutagenicity (Ames test) and the prediction was assessed as moderately reliable. This QSAR prediction indicates that 2-SEM does not have the potential to induce gene mutation and could be used to assess the mutagenic potential of the substance (e.g., to support the conclusion for no classification for germ cell mutagenicity).
This negative bacterial in vitro mutagenicity QSAR prediction was assessed as adequate for regulatory purposes.
Data source
Reference
- Reference Type:
- other: Software
- Title:
- CAESAR Mutagenicity model (version 2.1.13) implemented in Vega Application (version 1.1.4)
- Author:
- [1] Thomas Ferrari Department of Electronics and Information (DEI), Politecnico di Milano
[2] Alberto Manganaro Istituto di Ricerche Farmacologiche "Mario Negri" - Year:
- 2 010
- Bibliographic source:
- Ferrari T, Gini G (2010) An open source multistep model to predict mutagenicity from statistical analysis and relevant structural alerts. Chemistry Central Journal , 4(Suppl 1):S2.
Materials and methods
Test guideline
- Qualifier:
- according to guideline
- Guideline:
- other: REACH Guidance on QSARs R.6 (2008)
- Principles of method if other than guideline:
- - Software tool used including version: Vega Application (version 1.1.4)
- Model(s) used: CAESAR Mutagenicity model (version 2.1.13)
- Model description: see field 'Justification for type of information' and 'Attached justification'
- Justification of QSAR prediction: see field 'Justification for type of information' and 'Attached justification' - Type of assay:
- bacterial reverse mutation assay
Test material
- Reference substance name:
- Sulphoethyl methacrylate
- EC Number:
- 234-207-4
- EC Name:
- Sulphoethyl methacrylate
- Cas Number:
- 10595-80-9
- Molecular formula:
- C6H10O5S
- IUPAC Name:
- sulphoethyl methacrylate
Constituent 1
- Specific details on test material used for the study:
- SMILES: O=C(OCCS(=O)(=O)O)C(=C)C
InChI=1S/C6H10O5S/c1-5(2)6(7)11-3-4-12(8,9)10/h1,3-4H2,2H3,(H,8,9,10)
Results and discussion
Test results
- Key result
- Species / strain:
- other: S. typhimurium
- Genotoxicity:
- negative
- Additional information on results:
- Limited uncertainty was associated with the negative prediction generated for the target 2-SEM since:
- the target compound is moderately represented in the training set (i.e., moderately similar compounds found in the training set, target descriptors inside the descriptor range of training set, all structural fragments of the target found in the training set);
- training set analogues have experimental values in agreement with the predicted value for the target, i.e. negative Ames test results;
- prediction accuracy for training set analogues was good.
Overall, the negative bacterial in vitro mutagenicity QSAR prediction was assessed as reliable with a moderate level of confidence. - Remarks on result:
- no mutagenic potential (based on QSAR/QSPR prediction)
Applicant's summary and conclusion
- Conclusions:
- The target 2-SEM is predicted negative for bacterial in vitro mutagenicity (Ames test). The prediction is assessed as moderately reliable and adequate for regulatory purposes.
- Executive summary:
This study was designed to generate in silico (non-testing) genotoxicity data as bacterial in vitro mutagenicity for 2-sulfoethyl methacrylate (2-SEM). A reliability score of 2 was assigned, since results were derived from a valid (Q)SAR model, and falling into its applicability domain, with adequate and reliable documentation/justification.
The CAESAR Mutagenicity model (version 2.1.13) implemented in Vega Application (version 1.1.4) was employed. Vega/CAESAR model provides a qualitative prediction of mutagenicity on Salmonella typhimurium (Ames test).
Vega/Caesar mutagenicity model predicted the target 2-SEM as negative for Salmonella in vitro mutagenicity. The target compound was moderately represented in the training set (i.e., moderately similar compounds found in the training set, target descriptors inside the descriptor range of the training set, all structural fragments of the target found in the training set). The three most similar analogues showed consistent experimental values (i.e., negative Ames test results), and good prediction accuracy. Based on these considerations, the negative prediction was assessed as moderately reliable, and adequate for regulatory purposes.
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