2,2'-dihydroxy-4,4'-dimethoxybenzophenone

Density

Administrative data

Endpoint:

density, other

Remarks:

prediction of density in g/cm³

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

2018-05-29

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
T.E.S.T. (Toxicity Estimation Software Tool) version 4.2

2. MODEL (incl. version number)
Hierarchical method
The toxicity for a given query compound is estimated using the weighted average of the predictions from several different models. The different models are obtained by using Ward’s method to divide the training set into a series of structurally similar clusters. A genetic algorithm based technique is used to generate models for each cluster. The models are generated prior to runtime.

FDA method
The prediction for each test chemical is made using a new model that is fit to the chemicals that are most similar to the test compound. Each model is generated at runtime.

Single model method
Predictions are made using a multilinear regression model that is fit to the training set (using molecular descriptors as independent variables) using a genetic algorithm based approach. The regression model is generated prior to runtime.

Group contribution method
Predictions are made using a multilinear regression model that is fit to the training set (using molecular fragment counts as independent variables). The regression model is generated prior to runtime.

Nearest neighbor method
The predicted toxicity is estimated by taking an average of the 3 chemicals in the training set that are most similar to the test chemical.

Consensus method
The predicted toxicity is estimated by taking an average of the predicted toxicities from the above QSAR methods (provided the predictions are within the respective applicability domains). A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster.

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
CAS number: 131-54-4

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
please refer to the attached QMRF report

5. APPLICABILITY DOMAIN
The substance falls within the applicability domains (structural fragment and descriptor domain) of the applied models as specified in the corresponding QMRF.

Data source

Reference

Reference Type:

other: QSAR

Title:

Prediction of density with T.E.S.T. (Toxicity Estimation Software Tool) version 4.2

Author:

Todd Martin, Paul Harten, Raghuraman Venkatapathy, and Douglas Young, US EPA

Year:

2012

Bibliographic source:

A Program to Estimate Toxicity from Molecular Structure

Materials and methods

Test guideline

Guideline:

other: ECHA Guidance R.6

Principles of method if other than guideline:

- Software tool(s) used including version: Toxicity Estimation Software Tool (T.E.S.T.) v4.2
- Model(s) used: Consensus method, see field 'Justification for non-standard information',
- Model description: see field 'Justification for non-standard information' and 'Attached justification'
- Justification of QSAR prediction: see field 'Justification for type of information' and 'Attached justification'

GLP compliance:

no

Remarks:

not applicable for QSAR predictions

Test material

Test material information

Constituent 1

Reference substance name:

2,2'-dihydroxy-4,4'-dimethoxybenzophenone

EC Number:

205-027-3

EC Name:

2,2'-dihydroxy-4,4'-dimethoxybenzophenone

Cas Number:

131-54-4

Molecular formula:

C15H14O5

IUPAC Name:

2-(2-hydroxy-4-methoxybenzoyl)-5-methoxyphenol

Results and discussion

Density

Density 1

Key result

Type:

density

Density:

1.38 g/cm³

Remarks on result:

other: Consensus method

Density 2

Type:

density

Density:

1.36 g/cm³

Remarks on result:

other: group contribution method

Density 3

Type:

density

Density:

1.36 g/cm³

Remarks on result:

other: Hierarchical clustering

Density 4

Type:

density

Density:

1.43 g/cm³

Remarks on result:

other: nearest neighour

Any other information on results incl. tables

The density was predicted with T.E.S.T v4.2 using a combination of different QSAR models (Consensus method).

Applicant's summary and conclusion

Conclusions:

The density was predicted to be 1.38 g/cm3.

Executive summary:

The density was predicted with T.E.S.T v4.2 using a combination of different QSAR models (Consensus method). The density was predicted to be 1.38 g/cm³.