Registration Dossier

Administrative data

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
weight of evidence
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:

- EPIsuite/KOWWIN


2. MODEL (incl. version number)

EPISuite/KOWWIN version 1.68

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

O=C(N\C(=C/CCCCCl)C(=O)O)[C@H]1CC1(C)C

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL

This above mentioned tool was selected according to the OECD Guidance Documents on the Validation of (Q)SAR models:

- Document on the validation of (Quantitative) Structure Activity Relationship models. OECD Series on testing and Assessment N° 69. ENV/JM/MONO(2007)2.
- EnochSJ, Madden JC, Cronin MT (2008) Identification of mechanism of toxic action for skin sensitisation using a SMARTS pattern based approach, SAR QSAR Environ Res. 19(5-6):555-78

5. APPLICABILITY DOMAIN

- EPISuite/KOWWIN : Atom/Fragment Contribution

6. ADEQUACY OF THE RESULT

- EPISuite /KOWWIN: moderate reliable


From the evaluation of the result of this software, the target compound was predicted to have a Log Kow = 3.20 and the final prediction was assessed as Moderate Reliable.








Data source

Reference
Reference Type:
other: in silico prediction
Title:
Unnamed
Year:
2017
Report Date:
2017

Materials and methods

Test guideline
Qualifier:
according to
Guideline:
other: OECD series on testing assassment n° 69
Version / remarks:
ENV/JM/MONO(2007)2
Deviations:
not specified

Test material

Reference
Name:
Unnamed
Type:
Constituent

Study design

Analytical method:
other: (Q)SAR in silico prediction

Results and discussion

Partition coefficient
Type:
log Pow
Partition coefficient:
ca. 3.2
Remarks on result:
other: moderate reliable

Any other information on results incl. tables

This study was designed to generate estiamted "in silico" data.

The table below shows the result obstained.

 Endpoint  Prediction call  Reliability Assessment
 octanol-water partition coefficient  Log Kow = 3.20  moderate reliable

Applicant's summary and conclusion

Executive summary:

For the target , KOWWIN predicted a Log Kow value of 3.20. Based on the overall good prediction accuracy of KOWWIN estimation methodology ancd the fact that the target was included in the molecular weight range of the training set (MW equal to 273.76), the KOWWIN prediction was assessed as moderate reliable.