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Please be aware that this old REACH registration data factsheet is no longer maintained; it remains frozen as of 19th May 2023.

The new ECHA CHEM database has been released by ECHA, and it now contains all REACH registration data. There are more details on the transition of ECHA's published data to ECHA CHEM here.

Diss Factsheets

Toxicological information

Genetic toxicity: in vivo

Currently viewing:

Administrative data

Endpoint:
genetic toxicity in vivo
Remarks:
Type of genotoxicity: other: in silico prediction
Type of information:
(Q)SAR
Adequacy of study:
key study
Study period:
2013
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
Year:
2013

Materials and methods

Test guideline
Qualifier:
no guideline available
Principles of method if other than guideline:
QSAR approach: Different tools were used, when possible, in order to apply a consensus approach and thus enhance the reliability of the predictions. In fact, a single in silico prediction model may provide acceptable results. However, by definition all models are simulation of reality, and therefore they will never be completely accurate; sometimes a single model will not work. When multiple models and multiple approaches are combined in a single consensus score, more accurate predictions can be achieved.
If two prediction methods that use data and different approaches are consistent, the reliability of prediction is better. The errors of a model/approach should be different from another, and therefore compensate.

Several computational tools are nowadays available for applying in silico approaches. Among them, for QSAR predictions the following was selected and used for the endpoint:
Leadscope Model Applier (Leadscope, Inc.) (version 1.4.6-2) is a chemoinformatic platform that provides QSAR for the prediction of potential toxicity and adverse human clinical effects of pharmaceuticals, cosmetics, food ingredients and other chemicals. The Models are constructed by FDA scientists based on both proprietary and non-proprietary data. Predictions are provided together with several parameters which can be used to assess the prediction in terms of applicability domain. The robustness of the prediction can be further evaluated by examining compounds similar to the target from the training set.
GLP compliance:
no

Test material

Constituent 1
Chemical structure
Reference substance name:
Methyl 3-α,7-α-diacetoxy-12-α-hydroxy-5-β-cholan-24-oate
EC Number:
223-151-6
EC Name:
Methyl 3-α,7-α-diacetoxy-12-α-hydroxy-5-β-cholan-24-oate
Cas Number:
3749-87-9
Molecular formula:
C29H46O7
IUPAC Name:
methyl 3-α,7-α-diacetoxy-12-α-hydroxy-5-β-cholan-24-oate

Results and discussion

Any other information on results incl. tables

Name

Leadscope

Prediction

call

Leadscope

Positive

Prediction probability

Prediction reliability parameters

Model Fragment

Count

30% Sim. Training Neighbors Count

Reliability

assessment

methyl 3-α,7-α-diacetoxy-12-α-hydroxy-5-β-cholan-24-oate

NEGATIVE

0.09

7

1

RELIABLE

Applicant's summary and conclusion

Conclusions:
Interpretation of results (migrated information): negative
The methyl 3-α,7-α-diacetoxy-12-α-hydroxy-5-β-cholan-24-oate was predicted negative.