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Partition coefficient

Link to relevant study record(s)

Reference

Reference 1

Endpoint:

partition coefficient

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

24 May 2021

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 v4.11

2. MODEL (incl. version number): KOWWIN v1.68

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL: O=C(OCCCCCCCCCCOC(=O)C(=C)C)C(=C)C

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: logarithm of the n-octanol:water partition coefficient
- Unambiguous algorithm: The predicted value of the log Kow is calculated through the following equation: log Kow =∑f(j)n(j) + c(j)n(j) + 0.229
where f(j) is the coefficient for each atom/fragment), c(j) is the coefficient for each correction factor,
and n(i) is the number of times the atom/fragment (and correction factor) occurs in the test species.
- Defined domain of applicability:
KOWWIN v1.68 predicts log Kow of a given test chemical based on the functional groups which are part of that given test chemical’s structure. The log Kow is calculated as the summation of the atom fragment constants of individual chemical functionalities (fj). The contribution of individual chemical functionality to the overall log Kow is corrected according to a corresponding coefficient correction (cj) for a given atom type or chemical functionality. The summation of these atom fragment constants and associated correction factors is representative of the overall log Kow (i.e. the ratio of n-octanol solubility to water solubility). The predictive capacity of KOWWIN is limited to chemical functionalities which are contained in the reference data set and therefore only test chemicals which fall in that domain are accurately estimated. KOWWIN v1.68 accurately estimates test chemical which contain most commonly occurring aliphatic and aromatic chemical functional groups. Inorganics, or oganometallics, and boron containing species are generally outside the predictive domain of KOWWINv1.68.

Training set parameters (n = 2447):
Molecular weight range: 18.02 D – 719.92 D
Average molecular weight: 199.98
Log Kow range (measured): -4.22 – 8.18
Validation set parameters (n = 10,946):
Molecular weight range: 27.03 D – 991.15 D
Average molecular weight: 258.98
Log Kow range (measured): -5.08 - 11.29

- Appropriate measures of goodness-of-fit and robustness and predictivity:
From the log-log plot of predicted and experimental n-octanol/water partition coefficients (Kow’s) of the training set (2,447 compounds), the correlation coefficient (r2) is 0.982, the standard deviation (sd) is 0.217, and the absolute mean error (me) is 0.159. From the log-log plot of predicted and experimental n-octanol/water partition coefficients (Kow’s) of the validation set (10,946 compounds), the correlation coefficient (r2) is 0.943, the standard deviation (sd) is 0.479, and the absolute mean error (me) is 0.356.
- Mechanistic interpretation: The mechanistic basis for this QSAR is the specific chemical functional groups behave a certain way in n-octanol and water (the ratio of which is Kow). These fragments impart solubility characteristics on the given chemical and this is a constant. These constants have been calculated for a wide variety of functional groups and provide a basis by which to predict the Kow may be predicted for a chemical which contains functional groups from the training set. The individual mechanisms of this dissolution will vary between different chemical species and functional groups.

5. APPLICABILITY DOMAIN
- Descriptor domain: The total number of modelled fragments are not overrepresented in the structure. The total number of each modelled fragment within the substance is less than the maximum number of occurrence of that fragment in a single structure within the model training or validation sets.
- Structural and mechanistic domains: The parametric domain includes chemicals with molecular
weight of 18.02 D – 719.92 D and log Kow of -4.22 –8.18. The molecular weight and predicted log Kow for 1,10-decanediyl bismethacrylate are within the parametric range of the model. In addition, the software's training set contains a variety of acrylate compounds which are structurally related to the test substance, and the test substance is therefore within the applicability domain of this QSAR.
- Similarity with analogues in the training set: Structural analogues used by this QSAR in the prediction of the log Kow of the target substance are located in the supporting information provided with the software. The exact list of chemicals used to determine fragment coefficients and structure corrections are not available for each fragment type. Among the structural analogues identified by hand, there are 17 in the training and validation sets which contain acrylate functional group and these are used to determine prediction uncertainty. Data for three additional analogues were extracted from public databases for uncertainty analysis. Statistical variation of the 20 pairs of experimental and predicted log Kow values indicate that there is a 0.9593 correlation coefficient (r-squared), a standard deviation of 0.298 and an absolute mean error of 0.198.
- Other considerations (as appropriate):

6. ADEQUACY OF THE RESULT
In aquatic systems chemicals may partition to lipid rich tissue of aquatic organisms. Octanol is considered a reasonable analog for the lipid-rich tissues of aquatic organisms. The octanol
water partition coefficient is representative of a chemicals tendency to partition to the lipid rich tissues or remain in the aqueous phase. The log Kow is a basis by which to assess a chemicals potential for bioconcentration (via lipid-rich tissue partitioning)

Qualifier:

according to guideline

Guideline:

other: Guidance on information requirements and chemical safety assessment: Chapter R.6: QSARs

Deviations:

no

Principles of method if other than guideline:

- Software tool(s) used including version: Episuite 4.11
- Model(s) used: KOWWIN v.1.68
- Model description: see field 'Attached justification'
- Justification of QSAR prediction: see field 'Attached justification'

GLP compliance:

no

Remarks:

QSAR model

Type of method:

calculation method (fragments)

Remarks:

KOWWIN v1.68 as implemented through EPI Suite v4.11

Partition coefficient type:

octanol-water

Specific details on test material used for the study:

Molecular formula: C18H30O4 (molecular weight,310.44)
Smile: O=C(OCCCCCCCCCCOC(=O)C(=C)C)C(=C)C

Key result

Type:

log Pow

Partition coefficient:

6.14

Remarks on result:

other: Temperature and pH not in model output

Details on results:

Twenty structural analogues which contain acrylate functional groups are used to determine prediction uncertainty. Statistical variation of the 20 pairs of experimental and predicted log Kow values for these analogues indicate that there is a 0.9593 correlation coefficient (r-squared), a standard deviation of 0.298 and an absolute mean error of 0.198 (See Table 1)

Table 1. The predicted and experiment log Kow of analogous and target compounds

CAS Number	Exp LogKow	Kowwin Est	Residual
Analogues
96-33-3	0.80	0.73	-0.07
80-62-6	1.38	1.28	-0.10
140-88-5	1.32	1.22	-0.10
818-61-1	-0.21	-0.25	0.04
97-63-2	1.94	1.77	-0.17
106-63-8	2.22	2.13	-0.09
4655-34-9	2.25	2.18	-0.07
141-32-2	2.36	2.20	-0.16
585-07-9	2.54	2.64	0.10
868-77-9	0.47	0.30	-0.17
999-61-1	0.35	0.17	-0.18
923-26-2	0.97	0.72	-0.25
101-43-9	3.13	3.54	0.41
1188-09-6	1.86	2.70	0.84
688-84-6	4.54	4.64	0.10
1985-51-9	2.79	3.57	0.78
3290-92-4	4.39	4.50	0.11
2082-81-7	3.10*	3.19	0.09
6606-59-3	4.08*	4.17	0.09
13048-34-5	5.00*	5.04	0.04
Target compound
6701-13-9		6.14

*from public data source

Conclusions:

1,10-Decanediyl bismethacrylate is a constituent of MDP. 1,10-Decanediyl bismethacrylate has an estimated log Kow of 6.14 using KOWWIN v1.68 as implemented through EPISuite v4.11.

Executive summary:

1,10-Decanediyl bismethacrylate is a constituent of MDP. The logarithm of the partition coefficient n-octanol/water (log Kow) of 1,10-decanediyl bismethacrylate was estimated to be 6.14 using the KOWWIN v1.68 QSAR as implemented through EPI Suite v4.11. The software is an accepted, valid model for estimation of partition coefficient. The structure of 1,10 -decanediyl bismethacrylate is within the parametric domain of the model (molecular weight, maximum number of structural fragments per structure, predicted log Kow). The use of this QSAR to predict log Kow for this substance was determined to be applicable and reliable based on representation of analogous substances within the training set and performance statistics (a correlation coefficient (r^2) of 0.9593, a standard deviation of 0.298 and an absolute mean error of 0.198) derived from a comparison of experimental and estimated log Kow values for 20 representative analogous substances.

This study is classified as an acceptable QSAR and satisfies the requirements for partition coefficient study. It is pertinent to the fate of MDP and may be used for risk analysis, classification and labelling, and PBT analysis.

Reference 2

Endpoint:

partition coefficient

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

28 May 2021

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 : ACD/Labs v.12.00

2. MODEL (incl. version number) : ACD/Log D, v.12.00

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL : CC(=C)C(=O)OCCCCCCCCCCOP(=O)(O)O

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: Partition Coefficient which is a ratio of the quantity of test substance which partitions into both phases of an octanol-water biphasic system. This unitless ratio is expressed as log Kow, log P, log Pow, or log D (for ionizable substances).

- Unambiguous algorithm: ACD/Labs is proprietary commercial software. The general method for calculating Log Ko/w is described in the publisher's QMRF. The model uses Global linear baseline QSAR + local similarity based corrections. The global QSAR was developed using linear regression by partial least squares (PLS) in combination with a bootstrapping technique. This method implies random compound sampling from the initial training set, i.e. generation of new “training sub-sets”. Each of the sampled sub-sets is of the same size as the initial training set, however, the random manner of their population results in some compounds being selected more than once, others being omitted. This procedure is performed 100 times and an independent PLS model is derived for every sub-set. Each of those PLS models is based on 2D fragmental descriptors: log Ko/w = SUM[i=1..n](ai*fi) + c
where fi is the number of occurences of the i-th fragment in a molecule, ai - its statistical coefficient, and c - intercept.

- Defined domain of applicability: Applicability domain of the model is defined based on the training set compounds. The software database contains 16277 chemicals in the entire dataset with log Kow of -5.08 to 11.29. The predicted log Kow for 10-methacryloyl-oxy-decylphosphate is within the parametric range of the model. The structure modelled does not contain any unidentified fragments, and there is complete coverage of the structure by the molecule descriptors. The test substance is therefore within the applicability domain of this QSAR model.

- Appropriate measures of goodness-of-fit and robustness and predictivity: The model dataset was divided into training (11387 compounds) and validation sets (4890 compounds). For validation, the developers defined a reliability index (RI) to determine applicability of the model to members of the set, where all substances have RI >0.3 were defined as within the applicability domain. There are 11371 out of 11387 (99.9% ) of the training set compounds that fall within the aplicability domain of the model with correlation coefficient (R²) = 0.944 and standard deviation (Std. Dev.) = 0.457. There are 4872 out of 4890 (99.6%) of the validation set compounds that fall within the aplicability domain of the model (RI > 0.3) with R² = 0.940 and Std. Dev. = 0.464.
- Mechanistic interpretation: The primary mechanism of partitioning is an inherent property of the chemical and directly related to the elemental composition, function groups, and structural configuration thereof. The only mechanistic consideration utilized in model building is the use of a linear regression method (PLS) and the fragmental descriptors. In other words it is assumed that the final predicted value is composed of a linear combination of all the contributions of structural moieties making up the test molecule.

5. APPLICABILITY DOMAIN

- Descriptor domain: The model uses a molecular fragment approach with 377 specific defined fragments.

- Structural and mechanistic domain: The list of the structural or compositional analogues used by this QSAR in the prediction of the partition coefficient, log D, are proprietary information. The software database contains 16277 chemicals in the entire dataset with log Kow of -5.08 to 11.29 with standard deviatrion of 1.92. The predicted log Kow for 10-methacryloyl-oxy-decylphosphate is within the parametric range of the model. The structure modelled does not contain any unidentified fragments, and there is complete coverage of the structure by the molecule descriptors. The test substance is therefore within the applicability domain of this QSAR model.
- Similarity with analogues in the training set: The list of the structural or compositional analogues used by this QSAR in the prediction of the partition coefficient, log D, are proprietary information.
- Other considerations (as appropriate):

6. ADEQUACY OF THE RESULT
In aquatic systems chemicals may partition to lipid rich tissue of aquatic organisms. The partition coefficient, log D, of a substance is an indicator of its lipophilicity or lipophobicity. This value indicates whether a compound is likely to dissolve into lipid rich
environments (i.e. fat deposits or adipose tissue in fish). High (log D >4.5) positive values indicate a preference to partition to lipid rich environments and to bioconcentrate in aquatic species while negative values indicate a preference for aqueous environments. The partition coefficient directly translates into the transport and distribution of chemicals in the aquatic environment and/or aquatic biota.

Qualifier:

according to guideline

Guideline:

other: Guidance on information requirements and chemical safety assessment: Chapter R.6: QSARs

Deviations:

no

Principles of method if other than guideline:

- Software tool(s) used including version: ACDLabs V.12.00
- Model(s) used: ACD/Log D DB v.12.00
- Model description: see field 'Attached justification'
- Justification of QSAR prediction: see field 'Attached justification'

GLP compliance:

no

Remarks:

QSAR model

Type of method:

calculation method (fragments)

Partition coefficient type:

octanol-water

Specific details on test material used for the study:

Molecular formula: C14H27O6P1 (molecular weight,322. 34)
Smile: CC(=C)C(=O)OCCCCCCCCCCOP(=O)(O)O

Key result

Type:

log Pow

Partition coefficient:

-2.02

pH:

7

Remarks on result:

other: Temperature not in model output

Type:

log Pow

Partition coefficient:

-0.94

pH:

5

Remarks on result:

other: Temperature not in model output

Type:

log Pow

Partition coefficient:

-2.5

pH:

9

Remarks on result:

other: Temperature not in model output

Details on results:

The estimated partition coefficient, log D, has a standard error of ± 0.27 log units, the error determination method is not provided and is consequently unknown.

10-Methacryloyl-oxy-decylphosphate has estimated pKa values of 1.95 and 6.46, it will be present as monoanions and dianions in environmental pH 5 – 9.

Predicted log P value for neutral form is 1.99 ± 0.27 (pH < 1.95);
Predicted log P for monoanions is: -1.51 ± 1.00 (1.95 < pH < 6.46);
Predicted log P for di-anions is: -2.51 ± 1.50 (pH > 6.46);

Conclusions:

10-Methacryloyl-oxy-decylphosphate is a constituent of MDP. The predicted range of log D (partition coefficient) for 10-methacryloyl-oxy-decylphosphate is -0.94± 0.27 (at pH 5), -2.02 ± 0.27 (at pH 7), and -2.50 ± 0.27 (at pH 9) using ACD/ Log D DB as implemented through ACD/Labs v.12.00.

Executive summary:

10-Methacryloyl-oxy-decylphosphate is a constituent of MDP. The logarithm of the partition coefficient (log D) of 10-methacryloyl-oxy-decylphosphate was estimated using ACD/ Log D DB as implemented through ACD/Labs v.12.00.

The software is an accepted, valid model for estimation of partition coefficient. The software database contains 16277 chemicals in the entire dataset with log Kow of -5.08 to 11.29. The predicted log Kow for 10-methacryloyl-oxy-decylphosphate is within the parametric range of the model. The structure modelled does not contain any unidentified fragments, and there is complete coverage of the structure by the molecule descriptors. The use of this QSAR to predict log D for this substance was determined to be applicable and reliable based on representation of analogous substances within the training set and performance statistics.

10-Methacryloyl-oxy-decylphosphate has estimated pKa values of 1.95 and 6.46, it will be present as monoanions and dianions in environmental pH 5 – 9. The predicted range of log D (partition coefficient) is -0.94± 0.27 (at pH 5), -2.02 ± 0.27 (at pH 7), and -2.50 ± 0.27 (at pH 9), indicates that 10-methacryloyl-oxy-decylphospha is not anticipated to bioconcentrate by partitioning to the lipid rich tissues of aquatic organisms at environmental relevant pH.  

This study is classified as an acceptable QSAR and satisfies the requirements for partition coefficient study. It is pertinent to the fate of MDP and may be used for risk analysis, classification and labelling,

and PBT analysis.

Description of key information

MDP consists of two main constituents. The constituent 1,10-decanediyl bismethacrylate has an estimated log Kow of 6.14. The constituent 10-methacryloyl-oxy-decylphosphate has an estimated log D of -2.02 at pH 7.

Additional information

MDP consists of two main constituents: 1,10-decanediyl bismethacrylate and 10-methacryloyl-oxy-decylphosphate. Each constituent was modeled separately using different modeling software.

1,10-Decanediyl bismethacrylate is a neutral compound at environmental pH, the partition coefficient (log Kow) is modeled using KOWWIN v1.68 QSAR as implemented through EPI Suite v4.11 since the software is an accepted, valid model for estimation of partition coefficient of neutral compound. The log Kow of 1,10-decanediyl bismethacrylate was estimated to be 6.14, indicating a potential to be bioconcentrative or very bioconcentrating in aquatic organisms. The use of this QSAR to predict log Kow for this substance was determined to be applicable and reliable based on representation of analogous substances within the training set and performance statistics derived from a comparison of experimental and estimated log Kow values for representative analogous substances. The model results are considered reliable with restrictions (Klimisch 2) and a key study.  

10-Methacryloyl-oxy-decylphosphate has estimated pKa values of 1.95 and 6.46, it will be present as monoanions and dianions in environmental pH 5 – 9, thus the partition coefficient is modeled using ACD/ Log D DB as implemented through ACD/Labs v.12.00, since the software is an accepted, valid model for estimation of partition coefficient for ionized compound. The predicted range of log D (partition coefficient) is -0.94± 0.27 (at pH 5), -2.02 ± 0.27 (at pH 7), and -2.50 ± 0.27 (at pH 9), indicated that 10-methacryloyl-oxy-decylphosphate has a low potential to bioconcentrate in aquatic organisms. The use of this QSAR to predict log D for this substance was determined to be applicable and reliable based on representation of analogous substances within the training set and performance statistics. The model results are considered reliable with restrictions (Klimisch 2) and a key study.

Both studies are classified as acceptable QSARs and satisfy the requirements for partition coefficient study. They are pertinent to the fate of MDP and may be used for risk analysis, classification, and labelling, and PBT analysis.