Registration Dossier

Administrative data

Endpoint:
partition coefficient
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
Remarks:
Values for individual constituents of this natural complex substance (NCS) were calculated using a validated QSAR. All constituents fall within the applicability domain of the QSAR.
Justification for type of information:
SEE ATTACHED QMRF AND QPRF REPORT

1. SOFTWARE

2. MODEL (incl. version number)

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
[Explain how the model fulfils the OECD principles for (Q)SAR model validation. Consider attaching the QMRF or providing a link]
- Defined endpoint:
- Unambiguous algorithm:
- Defined domain of applicability:
- Appropriate measures of goodness-of-fit and robustness and predictivity:
- Mechanistic interpretation:

5. APPLICABILITY DOMAIN
[Explain how the substance falls within the applicability domain of the model]
- Descriptor domain:
- Structural and mechanistic domains:
- Similarity with analogues in the training set:
- Other considerations (as appropriate):

6. ADEQUACY OF THE RESULT
[Explain how the prediction fits the purpose of classification and labelling and/or risk assessment]

Data source

Reference
Reference Type:
other: QSAR model
Title:
KOWWIN v1.67a
Author:
U.S. Environmental Protection Agency
Year:
2008
Bibliographic source:
US EPA. [2008]. Estimation Programs Interface Suite™ for Microsoft® Windows, v 4.00. United States Environmental Protection Agency, Washington, DC, USA

Materials and methods

Test guideline
Qualifier:
according to
Guideline:
other: REACH Guidance on QSARs R.6
Deviations:
not applicable
Principles of method if other than guideline:
The partition coefficient of a NCS has little meaning. In all cases, the log Kow can be based on the range of Kow from the calculated or measured values of the individual constituents. Calculated and measured data on the constituents are obtained from Kowwin v1.67. The relevance and reliability of the used QSAR for these constituents is shown in the attached QMRF and QPRF.
GLP compliance:
no
Type of method:
other: Calculation by estimation
Partition coefficient type:
octanol-water

Test material

Reference
Name:
Unnamed
Type:
Constituent
Type:
Constituent
Test material form:
other: not applicable for in silico study
Details on test material:
not applicable for in silico study

Results and discussion

Partition coefficient
Key result
Type:
log Pow
Partition coefficient:
>= 4.57 - <= 6.45
Remarks on result:
other: temperature and pH not relevant (QSARs)
Details on results:
87% of the NCS has a log Kow > 4.0.

Any other information on results incl. tables

Constituent CAS Estimated log Kow MW
Bulnesol 22451-73-6 4.90 222.37
Guaiol 489-86-1 5.24 222.37
Eudesmol isomers α-Eudesmol 473-16-5,
β-Eudesmol 473-15-4,
γ-Eudesmol 1209-71-8,
10-epi-γ-Eudesmol 15051-81-7
5.28* 222.37
Bulnesene isomers α-Bulnesene 3691-11-0
β-Bulnesene 3772-93-8
6.45** 204.36
Guaioxide 20149-50-2 4.57 222.37
Elemol 8024-27-9 5.54 222.37

* The value for gamma-Eudesmol is used as it represents the worst case (highest predicted Kow value)

** The value for beta-Bulnesene is used as it represents the worst case (highest predicted Kow value)

Kowwin v1.67a model details

Reference to the type of model used

KOWWIN uses a "fragment constant" methodology to predict log P. In a "fragment constant" method, a structure is divided into fragments (atom or larger functional groups) and coefficient values of each fragment or group are summed together to yield the log P estimate. KOWWIN’s methodology is known as an Atom/Fragment Contribution (AFC) method.

 

Description of the applicability domain

The applicability domain is based on the maximum number of instances of that a fragment can be used in a chemical and molecular weight. The minimum and maximum values for molecular weight are the following:

 

Training Set Molecular Weights:

Minimum MW: 18.02

Maximum MW: 719.92

Average MW: 199.98

 

Validation Molecular Weights:

Minimum MW: 27.03

Maximum MW: 991.15

Average MW: 258.98

Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that log P estimates are less accurate for compounds outside the MW range of the training set compounds, and/or that have more instances of a given fragment than the maximum for all training set compounds. It is also possible that a compound may have a functional group(s) or other structural features not represented in the training set, and for which no fragment coefficient was developed. These points should be taken into consideration when interpreting model results.

 

Description and results of any possible structural analogues of the substance to assess reliability of the prediction

External validation with a dataset containing 10946 substances resulted in a correlation coefficient (r2) of 0.943, a standard deviation of 0.479 and an absolute deviation of 0.358.

Predictivity assessment of the external validation set:

Validation Set Estimation Error:

within <= 0.20 - 39.6%

within <= 0.40 - 66.0%

within <= 0.50 - 75.6%

within <= 0.60 - 82.5%

within <= 0.80 - 91.6%

within <= 1.00 - 95.6%

within <= 1.20 - 97.7%

within <= 1.50 - 99.1%

Uncertainty of the prediction

All constituents for which estimations were made fall within the applicability domain of the model.

Mechanistic domain

KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds. KOWWIN requires only a chemical structure to estimate a log P. The octanol-water partition coefficient is a physical property used extensively to describe a chemical's lipophilic or hydrophobic properties. It is the ratio of a chemical's concentration in the octanol-phase to its concentration in the aqueous phase of a two phase system at equilibrium. Since measured values range from less than 10^-4 to greater than 10^8 (at least 12 orders of magnitude), the logarithm (log P) is commonly used to characterize its value.

KOWWIN uses a "fragment constant" methodology to predict log P. In a "fragment constant" method, a structure is divided into fragments (atom or larger functional groups) and coefficient values of each fragment or group are summed together to yield the log P estimate. KOWWIN’s™s methodology is known as an Atom/Fragment Contribution (AFC) method. Coefficients for individual fragments and groups were derived by multiple regression of 2447 reliably measured log P values.

As all regular and common fragments are included in this method, and the constituents for which this method was applied do not contain exotic fragments, there are no limits to the mechanistic domain.

Applicant's summary and conclusion

Conclusions:
The log Kow range of the constituents of Guaiacwood oil is 4.57 - 6.45.
Executive summary:

As Guaiacwood oil is a naturally complex substance consisting of multiple constituents, a partition coefficient value for this NCS has little meaning. Therefore, in line with the NCS protocol, partition coefficients for the individual known constituents were calculated using the KOWWIN v1.67 QSAR by US-EPA.

The log Kow range for Guaiacwood oil constituents was found to be 4.57 - 6.45. The fraction of log Kow > 4.0 was 87.5%.