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EC number: 251-238-9 | CAS number: 32817-15-5
- 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
Endpoint summary
Administrative data
Key value for chemical safety assessment
Genetic toxicity in vitro
Link to relevant study records
- Endpoint:
- in vitro cytogenicity / micronucleus study
- Remarks:
- Type of genotoxicity: chromosome aberration
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2019
- Reliability:
- 1 (reliable without restriction)
- Justification for type of information:
- The computational simulation was performed based on the read-across approach. The readacross is one of the so-called alternative test methods recommended by REACH, where the predictions are based on the experimental data available for the most similar compounds. The predictions were performed according to the Read-Across Assessment Framework (RAAF), which assumes six different risk assessment scenarios of chemical compounds.
Applied tool:
The OECD QSAR Toolbox, version 4.3
Procedure of analysis:
I. Profiling of the target substance in order to retrieve relevant information related to mechanism of action and observed or simulated metabolites
II. Analogue (source compound) search based on selected criteria:
a. analogue dissociates similarly like the target compound (dissociation simulator)
b. analogue transforms similarly like the target compound (in vivo rat metabolism simulator)
c. analogue transforms similarly like the target compound (rat liver S9 simulator)
d. analogue has similar transformation products as the target compound (metabolism simulators, similarity >50%).
III. Data collection for the analogues (OECD Toolbox database/Genotoxicity pesticides
EFSA).
IV. Toxicity prediction for the target substance
V. Category consistency check in order to assess the quality of the prediction.
Applied scenario:
Scenario 1
Toxicity prediction for the target substance:
3 dissociating products, 3 in vivo rat liver metabolites and 3 rat liver S9 metabolites are produced after accounting for (a)biotic simulation (dissociation, rat in vivo metabolism and rat liver S9 simulator). However, based on the fact that target compound undergoes dissociation reaction it is expected that this will be the one of first reactions to which target is exposed. Thus, the prediction is based on toxicological data of the source compound with exact dissociation products. The target substance is an organometallic compound containing copper (Cu) centres, glycine (Gly) ligands. The metallic centres of the substance are linked by oxygen coordination bonds of the Gly ligands.
The weak bonds between metallic centres and the oxygen atoms in the compound structure will break easily and favour dissociation of the substance into its basic products: (Gly, H2SO4 and Cu(OH)2). Glycine is an amino acid, which is not considered as toxic compound. However, since there were no data available for the CuSO4, the prediction was performed basing on a transformation analogue search assuming at least 50% similarity between dissociation products of source and target substances. FeSO4 analogue has been found as the most similar chemical; therefore, it was used as the source compound.
The chromosome aberration for the source compound was performed according to:
Test guideline: OECD 473
Endpoint: chromosome aberration
Test organism: Mammalian cells
“One to one” read-across approach was used to predict the cytogenicity of target substance expressed by in vitro mammalian chromosome aberration test. - Principles of method if other than guideline:
- In order to meet regulatory needs, reliability of the predicted results should be assessed. In case of classic quantitative structure-activity relationships (QSAR) modelling, this idea can be realised by analysing, whether the predicted value is located within so-called applicability domain. The applicability domain is a theoretical region, defined by the range of toxicity values and structural descriptors for the training compounds, where the predictions may be considered as realistic ones. In a specific case of read-across, the assessment is performed based on the assessment of degree of similarity between the source and target compounds (in %). Moreover, the internal consistency of the group of source compounds (called „category” in OECD Toolbox nomenclature, independently which approach: analogue approach or category approach is
used). The category consistency check could be based on the parameters describing the structural similarity and/or properties as well as mechanistic similarity of the tested compounds.
For example, all members of the category (analogues as well as target substance) need to have the same functional groups and endpoint specific alerts.
In the case of read-across-based prediction of the in vitro cytogenicity of the copper (II) glycine sulphate (VI) dehydrate, the read-across hypothesis considers that source and target compounds have the same transformation products. Based on the Dice measure, the structural similarity between dissociation products of source and target substances (besides glycine) was equal to 50%. FeSO4 analogue has been found as the most similar chemical; therefore, it was used as the source compound.
Besides, the category consistencies, the boundaries of the applicability domain are verified by the critical value of log KOW. In case of Cu(Gly)SO4x2H2O, the log KOW value is not available.
Thus, information that “domain is not defined” is not critical in this situation.
The structural similarity between the source (FeSO4) and the target compound Cu(Gly)SO4x2H2O equals to 42.1% - Species / strain:
- mammalian cell line, other:
- Metabolic activation:
- not specified
- Genotoxicity:
- other:
- Remarks:
- QSAR
- Cytotoxicity / choice of top concentrations:
- cytotoxicity
- Remarks:
- The in vitro mammalian chromosome aberration for the target substance is predicted as positive.
- Additional information on results:
- The in vitro mammalian chromosome aberration for the target substance is predicted as positive.
- Remarks on result:
- ambiguous mutagenic potential (based on QSAR/QSPR prediction)
- Conclusions:
- The in vitro mammalian chromosome aberration for the target substance is predicted as positive.
- Endpoint:
- in vitro gene mutation study in mammalian cells
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2019
- Reliability:
- 1 (reliable without restriction)
- Justification for type of information:
- The computational simulation was performed based on the read-across approach. The readacross is one of the so-called alternative test methods recommended by REACH, where the predictions are based on the experimental data available for the most similar compounds. The predictions were performed according to the Read-Across Assessment Framework (RAAF), which assumes six different risk assessment scenarios of chemical compounds.
Applied tool:
The OECD QSAR Toolbox, version 4.3
Procedure of analysis:
I. Profiling of the target substance in order to retrieve relevant information related to mechanism of action and observed or simulated metabolites
II. Analogue (source compound) search based on selected criteria:
a. analogue dissociates similarly like the target compound (dissociation simulator)
b. analogue transforms similarly like the target compound (in vivo rat metabolism simulator)
c. analogue transforms similarly like the target compound (rat liver S9 simulator)
d. analogue has the same transformation products as the target compound (metabolism simulators).
III. Data collection for the analogues (OECD Toolbox database/ECHA CHEM).
IV. Toxicity prediction for the target substance
V. Category consistency check in order to assess the quality of the prediction
Applied scenario:
Scenario 1
Toxicity prediction for the target substance:
3 dissociating products, 3 in vivo rat liver metabolites and 3 rat liver S9 metabolites are produced after accounting for (a)biotic simulation (dissociation, rat in vivo metabolism and rat liver S9 simulator). However, based on the fact that target compound undergoes dissociation reaction it is expected that this will be the one of first reactions to which target is exposed. Thus, the prediction is based on toxicological data of the source compound with exact dissociation products.
The target substance is an organometallic compound containing copper (Cu) centres, glycine (Gly) ligands. The metallic centres of the substance are linked by oxygen coordination bonds of the Gly ligands.
The weak bonds between metallic centres and the oxygen atoms in the compound structure will break easily and favour dissociation of the substance into its basic products: (Gly, H2SO4 and Cu(OH)2). Glycine is an amino acid, which is not considered as toxic compound. Copper (II) sulphate would have the same dissociation products (H2SO4 and Cu(OH)2). Therefore, the prediction is based on the CuSO4. The gene mutation for the source compound was performed according to:
Test guideline: EU Method B.12 (Mutagenicity - In Vivo Mammalian Erythrocyte
Micronucleus Test)
Endpoint: Gene mutation
Test organism: mammalian cells
The read-across prediction of the gene mutation for the target substance was performed based on the “one to one” approach. - Principles of method if other than guideline:
- In order to meet regulatory needs, reliability of the predicted results should be assessed. In case of classic quantitative structure-activity relationships (QSAR) modelling, this idea can be realised by analysing, whether the predicted value is located within so-called applicability domain. The applicability domain is a theoretical region, defined by the range of toxicity values and structural descriptors for the training compounds, where the predictions may be considered as realistic ones. In a specific case of read-across, the assessment is performed based on the assessment of degree of similarity between the source and target compounds (in %). Moreover, the internal consistency of the group of source compounds (called „category” in OECD Toolbox nomenclature, independently which approach: analogue approach or category approach is used). The category consistency check could be based on the parameters describing the structural similarity and/or properties as well as mechanistic similarity of the tested compounds.
For example, all members of the category (analogues as well as target substance) need to have the same functional groups and endpoint specific alerts.
In the case of read-across-based prediction of the fish acute toxicity of the copper (II) glycine sulphate (VI) dehydrate, the read-across hypothesis considers that source and target compounds have the same transformation products. Based on the Dice measure, the structural similarity between dissociation products of source and target substances (besides glycine) was equal to 100%. Therefore, using experimental data of CuSO4 for predicting biological activity for the target compound was justified.
Besides, the category consistencies, the boundaries of the applicability domain are verified by the critical value of log KOW. In case of Cu(Gly)SO4x2H2O, the log KOW value is not available.
Thus, information that “domain is not defined” is not critical in this situation.The structural similarity between the source (CuSO4) and the target compound u(Gly)SO4x2H2O equals to 52.6% - Species / strain:
- mammalian cell line, other:
- Genotoxicity:
- negative
- Remarks on result:
- no mutagenic potential (based on QSAR/QSPR prediction)
- Conclusions:
- The gene mutation for the target substance is predicted as negative.
- Executive summary:
Cu(OH)2. Due to the glycine is an amino acid which is not considered as toxic compound, the analogues search was performed assuming 100% (“exact match”) structural similarity between dissociation products of source and target substances (besides glycine). The toxicity prediction was performed based on the experimental data included in the OECD QSAR Toolbox. Copper
(II) sulphate would have the same dissociation products (H2SO4 and Cu(OH)2) as well as the experimental data related to its in vivo gene mutation was available. Therefore, the prediction is based only on the CuSO4.
- Endpoint:
- in vitro gene mutation study in bacteria
- Type of information:
- experimental study
- Adequacy of study:
- key study
- Study period:
- 2019
- Reliability:
- 1 (reliable without restriction)
- Qualifier:
- according to guideline
- Guideline:
- OECD Guideline 471 (Bacterial Reverse Mutation Assay)
- GLP compliance:
- yes (incl. QA statement)
- Type of assay:
- bacterial reverse mutation assay
- Species / strain / cell type:
- S. typhimurium TA 1535, TA 1537, TA 98 and TA 100
- Genotoxicity:
- negative
- Remarks on result:
- no mutagenic potential (based on QSAR/QSPR prediction)
- Conclusions:
- Based on the results obtained under the experimental conditions applied, the test item did not induce gene mutations by base pair changes or frameshifts in the genome of the strains used.
In conclusion, the test item COPPER GLYCINATE has no mutagenic activity in the bacterial tester strains under the test conditions used in this study.
Referenceopen allclose all
Endpoint conclusion
- Endpoint conclusion:
- no adverse effect observed (negative)
Additional information
Justification for classification or non-classification
no classified
Information on Registered Substances comes from registration dossiers which have been assigned a registration number. The assignment of a registration number does however not guarantee that the information in the dossier is correct or that the dossier is compliant with Regulation (EC) No 1907/2006 (the REACH Regulation). This information has not been reviewed or verified by the Agency or any other authority. The content is subject to change without prior notice.
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