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EC number: 941-805-5 | CAS number: -
- 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
- Remarks:
- Type of genotoxicity: gene mutation
- Type of information:
- (Q)SAR
- Adequacy of study:
- supporting study
- Reliability:
- 2 (reliable with restrictions)
- Justification for type of information:
- QSAR prediction: migrated from IUCLID 5.6
Data source
Reference
- Reference Type:
- study report
- Title:
- Unnamed
- Report date:
- 2015
Materials and methods
- Principles of method if other than guideline:
- Gene mutation as microbial in vitro Salmonella was estimated by using four predictors: Leadscope, ACD/Percepta, Vega and Toxtree decision rule system.
- GLP compliance:
- no
- Type of assay:
- bacterial reverse mutation assay
Test material
- Reference substance name:
- Reaction mass of (2R)-2-phenyl-2-[(2R)-piperidin-2-yl]acetamide and (2S)-2-phenyl-2-[(2S)-piperidin-2-yl]acetamide
- EC Number:
- 941-805-5
- Molecular formula:
- C13H18N2O
- IUPAC Name:
- Reaction mass of (2R)-2-phenyl-2-[(2R)-piperidin-2-yl]acetamide and (2S)-2-phenyl-2-[(2S)-piperidin-2-yl]acetamide
Constituent 1
Results and discussion
Any other information on results incl. tables
Leadscope | ACD/Percepta | Vega | Toxtree | Consensus prediction |
NEGATIVE Moderate reliable |
NEGATIVE Borderline reliable |
NEGATIVE Borderline reliable |
NEGATIVE Not Reliable |
NEGATIVE Moderate Reliable |
Leadscope Model Applier
LeadscopePredictioncall | LeadscopePositivePrediction probability | Model FeaturesCount | 30% Sim. Training Neighbors Count | Reliabilityassessment |
NEGATIVE | 0.12 | 12 | 4 | MODERATE RELIABLE |
Model Features Count. Parameter used to verify that the target compound, i.e.c-racemate, contains a significant number of features that are present in the prediction model. The structural features used to make the prediction provide information on the reliability of the prediction: a prediction provided by a low number of features means that the model is not able to fully describe the test compound, while a prediction supported by a high number of features reveals that the test compound is well described by the model. Since 12 features were found, it was concluded thatc-racemateis well represented by the model.
30% Similarity Training Neighbours Count. Number of compounds structurally similar to the target, i.e.c-racemate, in the model's training set of compounds. Another way to assess the reliability of the prediction is looking at the analogues, i.e. the compounds structurally similar to the target in the model's training set of compounds. While this information does not take part to the prediction, it provides the user a complementary means to see how similar compounds were predicted and what the experimental values of similar compounds are. Look at analogues is also an initial, less-sophisticated easy way to understand estimate of toxicity. Four structures were identified in the training set as analogues toc-racemate, illustrated in the Table. It has to be noted that the identified analogues have little to moderate similarity with respect to the target (similarity index ranging from 0.32 to 0.58) and inconsistent experimental data, being two negative and two positive. However, since the mostly similar analogue has moderate similarity with respect to the target (similarity = 0.58) and consistent experimental data, being negative, the prediction was considered of moderate reliability.
Methylphenidate Result: negative Similarity: 0.58 |
phenyl-2-ethylmalondiamide, 2- Result: positive Similarity: 0.43 |
naphthyl)acetamide, 2-(1- Result: positive Similarity: 0.35 |
Atenolol Result: negative Similarity: 0.32 |
ACD/Percepta genotoxicity prediction
ACD/Percepta genotoxicity prediction is illustrated in Table 11. The prediction is provided together with a reliability index, which assesses the degree of confidence of the prediction. The reliability index (RI)takes into account the similarity of the target with the training set compounds and the consistency of experimental values for similar compounds. Itranges from0 to 1: if the RI is less than 0.3 the prediction has to be considered not reliable while if RI is more than 0.5 the prediction is considered reliable. ACD/Percepta prediction resulted to be negative, and the prediction is of borderline reliability being the reliability index equal to 0.32.
ACD/Percepta prediction call | ACD/Percepta positive probability | ACD/Percepta RI | Reliability assessment |
NEGATIVE | 0.12 | 0.32 | BORDERLINE |
No hazardous fragment was identified.
Together with the prediction, ACD/Percepta displays up to 5 most structurally similar structures from the training set along with experimental Ames test results for the corresponding compounds. The structural similarity is evaluated by a fragmental approach. The information on the structurally similar compounds in the training set is used to further assess the reliability of the prediction, since it illustrates how the test compound, i.e.c-racemate, is represented in the training set. The five mostly similar compounds from the training set, illustrated in Table 12, exhibit little similarity with respect to the targetc-racemate, only one with similarity greater than 0.5. Despite their little similarity, the five mostly similar training compounds exhibit consistent experimental data, being all of them negative and one inconclusive. Because of the little similarity of the training compounds with respect to the target, the prediction was considered of borderline reliability.
Methylphenidate Result: negative Similarity: 0.52 |
Amphetamine Result: inconclusive Similarity: 0.31 |
Methamphetamine Result: negative Similarity: 0.31 |
Dicyclohexylamine Result: positive Similarity: 0.83 |
2-METHYL-5-NITROBENZOIC ACID Result: negative Similarity: 0.23 |
HexahydroazepineResult: negativeSimilarity: 0.23 |
CAESAR QSAR model for mutagenicity implemented in Vegais an integrated model arranged cascading two models, a trained Support Vector Machine (SVM) classifier, and an additional for false negatives (FNs) removal based on Structural Alerts (SAs) matching. It assesses the reliability of the mutagenicity prediction according to a global applicability domain index, which ranges from 0 (not reliable) to 1 (fully reliable) taking into account many parameters, e.g. descriptor ranges, chemical similarity index, fragments similarity, etc… An ADI value greater than 0.9 means that the predicted substance is into the applicability domain of the model; ADI value lower than 0.7 means that the predicted substance is out of the applicability domain of the model, while an ADI value between 0.7 and 0.9, means that the predicted substance could be out of the Applicability Domain of the model.
Vega Prediction call | Vega prediction reliability | Reliability assessment |
NEGATIVE | AD Index = 0.85 | BORDERLINE RELIABLE |
Vega predicted the targetc-racemateas negative and the prediction is of borderline reliability, being the ADI equal to 0.85, since some similar molecules found in the training set have experimental values that disagree with the predicted value. The six compounds most similar toc-racemateare illustrated in the Table. It can be noted that the identified analogues exhibit good similarity with respect to the target (similarity ranging from 0.82 to 0.92) and five out of the six exhibit negative experimental test results.
The five compounds most similar are:
CAS: 113-45-1 (Training set) Similarity: 0.92 Experimental value: NEGATIVE Predicted value: NEGATIVE |
CAS: 34798-80-6 (Test set) Similarity: 0.85 Experimental value: NEGATIVE Predicted value: NEGATIVE |
CAS: 87625-62-5 (Training set) Similarity: 0.84 Experimental value: POSITIVE Predicted value: POSITIVE |
CAS: 2431-96-1 (Training set) Similarity: 0.84Experimental value: NEGATIVE Predicted value: NEGATIVE |
CAS: 134-72-5 (Training set) Similarity: 0.82 Experimental value: NEGATIVE Predicted value: NEGATIVE |
CAS: 92071-51-7 (Training set) Similarity: 0.82 Experimental value: NEGATIVE Predicted value: NEGATIVE |
Toxtree predicts the positive or negative mutagenicity according to decision rules based on the identification of Structural Alerts (SA) for mutagenicity, i.e. molecular functional groups or substructures known to be linked to the mutagenicity activity of chemicals. As one or more SAs embedded in a molecular structure are recognised, the system flags the potential mutagenicity of the chemical.The reliability of Toxtree mutagenicity prediction was evaluated by theApplicability Domain Index (ADI)implemented in VEGA platform (ADI > 0.9: into the domain; 0.9 > ADI ≥ 0.7: could be out of the domain; ADI < 0.7: out of the domain).Toxtreedid not identify any structural alert in the targetc-racemate, butthe prediction is not reliable being the ADI (global Applicability Domain Index) equal to 0.00.In fact, the following issues were addressed:only moderately similar compounds with known experimental value in the training set have been found; similar compounds found in the training set have experimental values that disagree with the predicted value and the accuracy of prediction for similar compounds found in the training set is not adequate.
The six compounds mostly similar to c-racemate are:
CAS: 125-33-7 (Training set) Similarity: 0.84 Experimental value: POSITIVE Predicted value: NEGATIVE |
CAS: 50 -06 -6 (Training set) Similarity: 0.81 Experimental value: POSITIVE Predicted value: NEGATIVE |
CAS: 54 -80 -8 (Training set) Similarity: 0.81Experimental value: NEGATIVE Predicted value: NEGATIVE |
CAS: 55268-74-1 (Training set) Similarity: 0.79 Experimental value: NEGATIVE Predicted value: NEGATIVE |
CAS: 136-77-6 (Training set) Similarity: 0.78 Experimental value: NEGATIVE Predicted value: NEGATIVE |
CAS: 77191-36-7 (Training set)Similarity: 0.77 Experimental value: NEGATIVE Predicted value: NEGATIVE |
Applicant's summary and conclusion
- Conclusions:
- Interpretation of results (migrated information):
negative Moderate Reliable
Gene mutation of the target c-racemate was estimated by using four predictors: Leadscope, ACD/Percepta, Vega and Toxtree decision rule system. The four predictors were employed in order to apply a consensus approach to enhance the reliability of the prediction. In the consensus assessment only reliable predictions are to be taken into account. Thus, in the case of c-racemate, Toxtree prediction was not taken into account due to the fact that its prediction resulted to be not reliable. The other three predictors, i.e. Leadscope, ACD/Percepta and Vega, were all in agreement providing a negative prediction although with a different level of confidence. Therefore, it was concluded that the target c-racemate is NEGATIVE for microbial in vitro Salmonella, and the prediction is of moderate reliability.
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