2-methylhydroquinone

Basic toxicokinetics

Administrative data

Endpoint:

basic toxicokinetics, other

Remarks:

blood-brain barrier penetration

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

Data source

Reference

Reference Type:

study report

Title:

Unnamed

Year:

2017

Report date:

2017

Materials and methods

Objective of study:

distribution

Test guideline

Qualifier:

equivalent or similar to guideline

Guideline:

OECD Guideline 417 (Toxicokinetics)

GLP compliance:

no

Test material

Test material information

Constituent 1

Reference substance name:

2-methylhydroquinone

EC Number:

202-443-7

EC Name:

2-methylhydroquinone

Cas Number:

95-71-6

Molecular formula:

C7H8O2

IUPAC Name:

2-methylbenzene-1,4-diol

Test material form:

solid: particulate/powder

Radiolabelling:

other: not applicable

Test animals

Species:

rat

Results and discussion

Preliminary studies:

Applicability domain (OECD principle 3)
a. Domains:
i. descriptor domain
All descriptor values for methylhydroquinone fall in the applicability domain (training set value ±30%).
ii. structural fragment domain
Methylhydroquinone is structurally relatively similar to the model compounds. The training set contains compounds of similar size to the studied molecule.
iii. mechanism domain
Methylhydroquinone is considered to be in the same mechanistic domain as the molecules in the training set as it is structurally similar to the model compounds.
iv. metabolic domain, if relevant
Methylhydroquinone e is considered to be in the same metabolic domain as themolecules in the training set of the model due to the structural similarity (i.e. CAS-No. 59-92-7, CAS-No. 50-78-2).

Considerations on structural analogues:
The structural analogues are relatively similar to the studied compound, and are considered to be within the same mechanistic domain. The descriptor values of the
analogues are close to those of the studied compound. The analogues are evaluated correctly within the model. The following aspects have been considered for the selection and analysis of structural analogues:
Presence and number of common functional groups;
Presence and relevance of non-common functional groups;
Similarity of the ‘core structure’ apart from the (non-)common functional groups;
Potential differences due to reactivity;
Potential differences due to steric hindrance;
Presence of structural alerts;
Position of the double bonds;
Presence of stereoisomers.

Toxicokinetic / pharmacokinetic studies

Transfer into organs

Transfer type:

blood/brain barrier

Observation:

slight transfer

Remarks:

logP(BB) = 0.07

Metabolite characterisation studies

Metabolites identified:

no

Any other information on results incl. tables

The uncertainty of the prediction (OECD principle 4)

The training set is assembled from different sources, but the previous successful modelling (ref 1,2) supports the consistency of the present model. While the blood-brain barrier penetration is in principle relatively simple to measure, in rats for instance, it requires the sacrifice of the rat, therefore, reliable and large data-series are not common. Due to the complexity of the mechanism, the modelling has been relatively limited. While the size of the dataset is moderate, the endpoint values are very well distributed (roughly equal positive and negative logP values), the statistical quality (RMS, correlation coefficients etc.) of the model supports reliable predictions within the margins of the experimental error. The similarity of the analogues to the studied molecule supports prediction consistency. All similar compounds have been evaluated correctly within the model, also adding to consistency.

Considering the dataset, model statistical quality and prediction reliability, a reliability score (Klimisch score) “2” could be assigned to the present prediction.

The prediction reliability in terms of classification is estimated as 78 %.

Applicant's summary and conclusion

Conclusions:

Based on a QSAR calculation, methylhydroquinone is able to penetrate the Blood-brain barrier.

Executive summary:

Based on a QSAR calculation, methylhydroquinone is able to penetrate the Blood-brain barrier.