5,5'-diisopropyl-2,2'-dimethylbiphenyl-4,4'-diyl dihypoiodite

Skin sensitisation

Administrative data

Endpoint:

skin sensitisation, other

Remarks:

in silico

Type of information:

experimental study

Adequacy of study:

key study

Study period:

6 February 2018

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
DEREK NEXUS - skin sensitisation

2. MODEL (incl. version number)
DEREK NEXUS version 6.0.1

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
C1=C(C(=CC(=C1C2=CC(=(C=C2C)OI)C(C)C)C)OI)C(C)C

- Molecular Mass: 549.9866

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
DEREK NEXUS predictive performance against a combined human dataset had an accuracy of 77 %.

DEREK NEXUS is a knowledge-based system that contains 90 alerts for skin sensitisation based on the presence of molecular substructures. LHASA has inserted validation comments for the skin sensitisation alerts.
The level of likelihood of a structure being sensitizing to skin is expressed in terms of:
Certain = There is proof that the proposition is true.
Probable = There is at least one strong argument that the proposition is true and there are no arguments against it.
Plausible = The weight of evidence supports the proposition.
Equivocal = There is an equal weight of evidence for and against the proposition.
The default of DEREK NEXUS for the level of likelihood, mentioning all alerts which are evaluated as being equivocal or greater was used in this assessment.
If a substance is predicted to be no skin sensitiser, DEREK NEXUS contains an expert-derived functionality to provide negative predictions for skin sensitization. This functionality further evaluates those compounds which do not fire any skin sensitisation alerts in DEREK NEXUS. The query compound is compared to a Lhasa reference set of Ames test or skin sensitisation data, producing the following outcomes:
- In compounds where all features in the molecule are found in accurately classified compounds from the reference set, a negative prediction is displayed: inactive.
- For those query compounds where features in the molecule are found in non-alerting skin sensitisers in the Lhasa reference set, the prediction remains negative and the misclassified features are highlighted to enable the negative prediction to be verified by expert assessment.
- In cases where features in the molecule are not found in the Lhasa reference set, the prediction remains negative and the unclassified features are highlighted to enable the negative prediction to be verified by expert assessment.
If a substance is predicted to be a skin sensitiser, its potency is predicted by DEREK NEXUS by calculating an EC3 value based on experimental data from the closest structurally-related substances (at least 3 substances should be present) using the following equation:
EC3Q = MWQ /(Σ ωNN / Σ TNN)
MW = molecular weight
T = Tanimoto similarity score
ω = weighting factor = (MWNN/EC3) x TNN
Q = query compound
NN = nearest neighbour
The EC3 is the estimated concentration needed to produce a stimulation index of 3.

5. APPLICABILITY DOMAIN
i. descriptor domain: if a substance activates an alert describing a structure activity relationship for skin sensitisation it can be considered to be within the applicablility domain. The aplicability of potency predictions may be judged, and modified, by the user based on the displayed data for nearest neighbours. If a compound dose not activate an alert or reasoning rule then Derek makes a negative prediction. The applicability of a negative prediction to the query compounds can be determined by an expert, if required, by investigating the presence (or absence) of misclassified and/or unclassified features.
ii. structural fragment domain: for skin sensitisation, which features multiple alerts believed to cover most of the mechanisms and chemical classes responsible for activity, “no alerts fired” may be extrapolated to a negative prediction. However, the substructure I-O could also not be found in the Lhasa skin sensitisation negative prediction dataset. Therefore, this prediction should be considered with caution.
iii. mechanism domain: as the prediction is “no alerts fired” none of the mechanisms for skin sensitisation is predicted to be applicable to this structure.
iv. metabolic domain: not relevant.

6. ADEQUACY OF THE RESULT
- The uncertainty of the prediction
The structure did not match any structural alerts or examples for skin sensitisation in DEREK, and the substructure I-O could not be found in the Lhasa skin sensitisation negative prediction dataset. Therefore, this prediction should be considered with caution.

The present prediction may be used for preparing the REACH Registration Dossier on the substance for submission to ECHA, as required by Regulation (EC) 1907/2006 and related amendments. The result is adequate to be used in a weight-of-evidence approach together with in chemico/in vitro studies to complete the endpoint skin sensitisation.

Data source

Reference

Reference Type:

study report

Title:

Unnamed

Year:

2018

Report date:

2018

Materials and methods

Test guideline

Qualifier:

no guideline followed

Principles of method if other than guideline:

The potential for skin sensitisation of the test material was predicted with the in silico model DEREK NEXUS. In this assessment version 6.0.1 of DEREK NEXUS was used.

GLP compliance:

no

Remarks:

calculation method

Type of study:

other: calculation method using the in silico model DEREK NEXUS

Justification for non-LLNA method:

DEREK NEXUS is a knowledge-based system that contains 90 alerts for skin sensitisation based on the presence of molecular substructures. It has been found to provide valuable in silico predictions on skin sensitisation.

Test material

Test material information

Constituent 1

Reference substance name:

5,5'-diisopropyl-2,2'-dimethylbiphenyl-4,4'-diyl dihypoiodite

EC Number:

209-007-5

EC Name:

5,5'-diisopropyl-2,2'-dimethylbiphenyl-4,4'-diyl dihypoiodite

Cas Number:

552-22-7

Molecular formula:

C20H24I2O2

IUPAC Name:

4-[4-(iodooxy)-2-methyl-5-(propan-2-yl)phenyl]-5-methyl-2-(propan-2-yl)phenyl hypoiodite

Specific details on test material used for the study:

- Molecular weight: 549.9866
- SMILES: C1=C(C(=CC(=C1C2=CC(=C(C=C2C)OI)C(C)C)C)OI)C(C)C

Results and discussion

In vitro / in chemico

Results

Key result

Remarks on result:

other: The test material is predicted to be not sensitising to the skin

Any other information on results incl. tables

DEREK NEXUS version 6.0.1 did not match the query structure with any structural alerts or examples for skin sensitisation. However, the query structure also contains features that were not found in the Lhasa skin sensitisation negative prediction dataset (unclassified). The test material is predicted to be not sensitising to the skin, but this prediction should be considered with care.

Applicant's summary and conclusion

Interpretation of results:

other: Not sensitising according to EU criteria

Conclusions:

DEREK NEXUS version 6.0.1 did not match the query structure with any structural alerts or examples for skin sensitisation. However, the query structure also contains features that were not found in the Lhasa skin sensitisation negative prediction dataset (unclassified). The test material is predicted to be not sensitising to the skin, but this prediction should be considered with care.

Executive summary:

The potential for skin sensitisation of the test material was predicted with the in silico model DEREK NEXUS. In this assessment version 6.0.1 of DEREK NEXUS was used.

DEREK NEXUS version 6.0.1 did not match the query structure with any structural alerts or examples for skin sensitisation. However, the query structure also contains features that were not found in the Lhasa skin sensitisation negative prediction dataset (unclassified). The test material is predicted to be not sensitising to the skin, but this prediction should be considered with care.