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Partition coefficient

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Endpoint:
partition coefficient
Data waiving:
study technically not feasible
Justification for data waiving:
the study does not need to be conducted because the substance has a high surface activity
other:
Justification for type of information:
Annex VII of Regulation (EC) 1907/2006, relating to Partition coefficient n-octanol/water states “If the test cannot be performed (e.g. the substance decomposes, has a high surface activity, reacts violently during the performance of the test or does not dissolve in water or in octanol, or it is not possible to obtain a sufficiently pure substance), a calculated value for log P as well as details of the calculation method shall be provided.” The result of the surface tension study (cross referenced) confirms the substance to be highly surface active and so a calculated value for partition coefficient is provided accordingly.
Reason / purpose:
data waiving: supporting information
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: EPI Suite™ KOWWIN™
2. Model: KOWWIN v1.68
3. SMILES: Unreacted nonylphenol CCCCCCCCCc1ccc(O)cc1, mono-reacted nonyl phenol CCCCCCCCCc1ccc(O)c(CN(C)CC(=O)(O[Na]))c1, direacted nonylphenol CCCCCCCCCc1cc(CN(C)CC(=O)(O[Na]))c(O)c(CN(C)CC(=O)(O[Na]))c1, unreacted sodium sarcosinate CNCC(=O)(O[Na]).
4. Scientific validity: Individual estimation programs and/or their underlying predictive methods and equations have been described in numerous journal articles in peer-reviewed technical journals. In addition, EPI Suite™ has undergone detailed review by a panel of EPA’s independent Science Advisory Board (SAB).
5. Applicability domain: The intended application domain is organic chemicals. Inorganic and organometallic chemicals are generally outside the domain.
6. Adequacy of the result: The intended application domain is organic chemicals. Inorganic and organometallic chemicals are generally outside the domain.
Principles of method if other than guideline:
EPI Suite™ KOWWIN™ v1.68
Specific details on test material used for the study:
Not applicable for in silico study
Key result
Type:
log Pow
Partition coefficient:
-0.2
Remarks on result:
not measured/tested
Remarks:
pH and temperature value is not specified by the QSAR model
Conclusions:
The partition coefficient (log Pow) of the test item was estimated to be -0.2.
Executive summary:

The partition coefficient was estimated using the (Q)SAR model KOWWIN v1.68. Organic components of this substance fall into the applicability domain of this model, but not the molecules featuring ionic functional groups. The partition coefficient was calculated for individual components of the substance, and estimated to be -0.2 for this substance using a weighted average, based on the composition of the components of this substance.

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: ALOGPS
2. MODEL (incl. version number): v2.1
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL: Unreacted nonylphenol CCCCCCCCCc1ccc(O)cc1; mono-reacted nonyl phenol CCCCCCCCCc1ccc(O)c(CN(C)CC(=O)(O[Na]))c1; direacted nonylphenol CCCCCCCCCc1cc(CN(C)CC(=O)(O[Na]))c(O)c(CN(C)CC(=O)(O[Na]))c1; unreacted sodium sarcosinate CNCC(=O)(O[Na])
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL: ALOGPs was developed with 12908 molecules from the PHYSPROP database using 75 E-state indicies. 64 neural networks were trained using 50% of molecules selected by chance from the whole set. The logP prediction accuracy is root mean squared error rms=0.35 and standard mean error s=0.26.
5. APPLICABILITY DOMAIN: ALOGPs was developed with 12908 molecules from the PHYSPROP database using 75 E-state indicies. 64 neural networks were trained using 50% of molecules selected by chance from the whole set. The logP prediction accuracy is root mean squared error rms=0.35 and standard mean error s=0.26.
6. ADEQUACY OF THE RESULT: ALOGPs was developed with 12908 molecules from the PHYSPROP database using 75 E-state indicies. 64 neural networks were trained using 50% of molecules selected by chance from the whole set. The logP prediction accuracy is root mean squared error rms=0.35 and standard mean error s=0.26.
Principles of method if other than guideline:
ALOGPS v2.1
Specific details on test material used for the study:
Not applicable for in silico study
Key result
Type:
log Pow
Partition coefficient:
4.145
Remarks on result:
not measured/tested
Remarks:
pH and temperature value is not specified by the QSAR model
Conclusions:
The partition coefficient (log Pow) of the test item was estimated to be 4.1451.
Executive summary:

The partition coefficient was estimated using the (Q)SAR model ALOGPS 2.1. The partition coefficient was calculated for individual components of the substance, and estimated to be 4.1451 for this substance using a weighted average, based on the composition of the components of this substance.

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: Molinspiration

2. MODEL (incl. version number): miLogP2.2

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL: Unreacted nonylphenol CCCCCCCCCc1ccc(O)cc1; mono-reacted nonyl phenol CCCCCCCCCc1ccc(O)c(CN(C)CC(=O)(O[Na]))c1; direacted nonylphenol CCCCCCCCCc1cc(CN(C)CC(=O)(O[Na]))c(O)c(CN(C)CC(=O)(O[Na]))c1; unreacted sodium sarcosinate CNCC(=O)(O[Na])

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL: Method for logP prediction developed at Molinspiration (miLogP2.2 - November 2005) is based on group contributions. These have been obtained by fitting calculated logP with experimental logP for a training set more than twelve thousand, mostly drug-like molecules. In this way hydrophobicity values for 35 small simple "basic" fragments have been obtained, as well as values for 185 larger fragments, characterizing intramolecular hydrogen bonding contribution to logP and charge interactions. Molinspiration methodology for logP calculation is very robust and is able to process practically all organic and most organometallic molecules. For 50.5% of molecules logP is predicted with error < 0.25, for 80.2% with error < 0.5 and for 96.5% with error < 1.0. Only for 3.5% of structures logP is predicted with error > 1.0.

5. APPLICABILITY DOMAIN: Method for logP prediction developed at Molinspiration (miLogP2.2 - November 2005) is based on group contributions. These have been obtained by fitting calculated logP with experimental logP for a training set more than twelve thousand, mostly drug-like molecules. In this way hydrophobicity values for 35 small simple "basic" fragments have been obtained, as well as values for 185 larger fragments, characterizing intramolecular hydrogen bonding contribution to logP and charge interactions. Molinspiration methodology for logP calculation is very robust and is able to process practically all organic and most organometallic molecules. For 50.5% of molecules logP is predicted with error < 0.25, for 80.2% with error < 0.5 and for 96.5% with error < 1.0. Only for 3.5% of structures logP is predicted with error > 1.0.

6. ADEQUACY OF THE RESULT: Method for logP prediction developed at Molinspiration (miLogP2.2 - November 2005) is based on group contributions. These have been obtained by fitting calculated logP with experimental logP for a training set more than twelve thousand, mostly drug-like molecules. In this way hydrophobicity values for 35 small simple "basic" fragments have been obtained, as well as values for 185 larger fragments, characterizing intramolecular hydrogen bonding contribution to logP and charge interactions. Molinspiration methodology for logP calculation is very robust and is able to process practically all organic and most organometallic molecules. For 50.5% of molecules logP is predicted with error < 0.25, for 80.2% with error < 0.5 and for 96.5% with error < 1.0. Only for 3.5% of structures logP is predicted with error > 1.0.



Principles of method if other than guideline:
Molinspiration miLogP2.2
Specific details on test material used for the study:
Not applicable for in silico study
Key result
Type:
log Pow
Partition coefficient:
2.094
Remarks on result:
not measured/tested
Remarks:
pH and temperature value is not specified by the QSAR model
Conclusions:
The partition coefficient was estimated using the (Q)SAR model Molinspiration miLogP2.2. The partition coefficient was calculated for individual components of the substance, and estimated to be 2.0937 for this substance using a weighted average, based on the composition of the components of this substance.
Executive summary:

The partition coefficient was estimated using the (Q)SAR model Molinspiration miLogP2.2. The partition coefficient was calculated for individual components of the substance, and estimated to be 2.0937 for this substance using a weighted average, based on the composition of the components of this substance.

Description of key information

Component

Log Pow

KOWWIN v1.68 (EPI Suite)

ALOGPS 2.1 (mean)*

Molinspiration

Unreacted nonylphenol

5.99

5.70

5.85

Mono-reacted nonylphenol

1.19

4.64

2.58

Di-reacted nonylphenol

-1.84

3.69

1.50

Unreacted sodium sarcosinate

-4.73

-1.26

-3.37

Weighted average

-0.2000

4.1451

2.0937

OVERALL MEAN VALUE

2.0129

 

(Q)SAR models were used to determine Partition coefficient n-octanol/water values, which do not report pH and temperature.

Key value for chemical safety assessment

Log Kow (Log Pow):
2.013

Additional information