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Physical & Chemical properties

Water solubility

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Endpoint:
water solubility
Type of information:
experimental study
Adequacy of study:
weight of evidence
Reliability:
1 (reliable without restriction)
Rationale for reliability incl. deficiencies:
guideline study
Qualifier:
according to guideline
Guideline:
EU Method A.6 (Water Solubility)
GLP compliance:
yes
Type of method:
column elution method
Water solubility:
< 0.05 mg/L
Temp.:
20 °C
pH:
>= 6.6 - <= 8

The solubility is determined via column elution method in two separate runs with a high and low water flow rate. The observed substance concentrations were well below the limit of quantification (LOQ) of <0.05 mg/L. Although the steady state was not reached in the test, the registered substance was still observed (i.e. concentrations above the LOD) and the results of the two runs at different flow rates were not in agreement, the study was stopped, since the conclusion on the solubility could already be reached (<LOQ).

Conclusions:
The water solubility is <0.05 mg/L at 20°C (Bayer 1999 c).
Executive summary:

In a study according to EG guideline A.6 92/69 the water solubility of the registered substance was examined via High Performance Liquid Chromatography, using 85 % Acetonitrile and 15 % water as eluent (flow rate 2 ml/min, column temperature 40 °C, detection by 224 nm UV), and quantifying by external standardisation. The solubility is determined via column elution method in two separate runs with a high and low water flow rate. The observed substance concentrations were well below the limit of quantification (LOQ) of <0.05 mg/L. Although the steady state was not reached in the test, the registered substance was still observed (i.e. concentrations above the LOD) and the results of the two runs at different flow rates were not in agreement, the study was stopped, since the conclusion on the solubility could already be reached (<LOQ).

Endpoint:
water solubility
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, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification
Remarks:
The molecular weight and log Kow of the test substance are slightly above the range in the training set. However, the WSKOWWIN model implemented shows high predictivity based on adequate accuracy and goodness of fit of both the training (r2 = 0.934) and validation (r2 = 0.902) sets.
Justification for type of information:
1. SOFTWARE
Individual model WSKOWWIN included in the Estimation Programs Interface (EPI) Suite.

2. MODEL (incl. version number)
WSKOWWIN v1.43 included in EPISuite v 4.11, 2000 – 2015.

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The SMILES CODE was entered in the initial data entry screen. In addition, the experimental log Kow (12) was entered to be used as a model descriptor.

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL

a. Defined endpoint: Water Solubility

b. Explicit algorithm (OECD Principle 2):
This program (WSKOWWIN) estimates the water solubility (WSol) of an organic compound using the compounds log octanol-water partition coefficient (Kow).
WSKOWWIN estimates water solubility for any compound with one of two possible equations:
log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + ΣCorrections (1)
log S (mol/L) = 0.693 - 0.96 log Kow - 0.0092(Tm-25) - 0.00314 MW + ΣCorrections (2)
where MW is molecular weight, Tm is melting point (MP) in deg C [used only for solids]). When a measured MP is available, equation (2) is used; otherwise, the equation (1) with just MW is used. Summation of Corrections (ΣCorrections) are applied as described in Appendix E of WSKOWWIN Help documentation. Corrections are applied to 15 structure types (eg. alcohols, acids, selected phenols, nitros, amines, alkyl pyridines, amino acids, PAHS, multi-nitrogen types, etc); application and magnitude depend on available MP.

c. Descriptor selection:
WSKOWWIN requirement for water solubility estimation includes:
SMILES: This is the structure of the compound as a SMILES notation and allows the estimation of molecular weight.
Melting Pt: WSKOWWIN uses an estimation equation that excludes melting point. In terms of method accuracy, this equation is not as good as the equation that uses a measured melting point.
Log Kow: When a value is entered, it is used to estimate water solubility. If no value is entered, WSKOWWIN estimates a log Kow for every SMILES notation by using the estimation engine from the KOWWIN Program. WSKOWWIN also automatically retrieves experimental log Kow values from a database containing more than 13200 organic compounds with reliably measured values.
In addition, corrections based on residual errors from the initial regression fit are applied to 15 structure types (eg. alcohols, acids, selected phenols, nitros, amines, alkyl pyridines, amino acids, PAHS, multi-nitrogen types, etc). Each correction factor is counted a maximum of once per structure [if applicable], no matter how many times the applicable fragment occurs.

d. Defined domain of applicability: The range of data in the training set could be used to describe the applicability domain of the model. The minimum and the maximum values for molecular weight, water solubilities and log Kow are the following:
Training Set Molecluar Weights: 27.03 - 627.62 g/mol
Training Set Water Solubility Ranges: 4x10-7 mg/L – completely soluble
Training set log Kow: -3.89 – 8.27

e. Statistics for goodness-of-fit:
WSKOWWIN estimates water solubility with one of two possible equations. When an experimental melting point is available, WSKOWWIN applies the equation containing both a melting point and the molecular weight (MW) parameters. In the absence of a melting point, the equation containing just the molecular weight is used to make the estimate. All compounds in the 1450 compound training set have known melting points or are known to be liquids at 25C. The equation without melting point was used in this case and the accuracy statistics is:
Correlation coefficient for training set r² = 0.934
Correlation coefficient for validation set r² = 0.902

f. Mechanistic interpretation: The WSKOWWIN program estimates the water solubility of an organic compound using the compounds log octanol-water partition coefficient (log Kow). Log Kow represents the capacity of a compound to dissolve in fatty solution (lipophilicity) and this factor is negatively correlated to the capacity of the compound to dissolve in water (hydrophilicity).

5. APPLICABILITY DOMAIN
a. Descriptor Domains:
With a molecular weight of 693.1 g/mole the substance is slightly out of the range of the training set (27.03 – 627.62 g/mole) but molecular weight is not the main descriptor and is not expected to significantly influence the prediction of water solubility.
Log Kow is the main descriptor and the experimental log Kow (10.4) used for the prediction was also slightly higher than the maximum value of 8.27 in the training set. However, the regression analysis shows adequate goodness of fit (r2 = 0.934) and linearity. Therefore, the model is considered robust to predict values outside the dataset.
b. Mechanism domain: No information available.
c. Metabolic domain: Not relevant.
d. Structural analogues: No information available.

6. ADEQUACY OF THE RESULT
a. Regulatory purpose: The data may be used for regulatory purpose.
b. Approach for regulatory interpretation of the model result: If no experimental data are available, the estimated value may be used to fill data gaps needed for hazard and risk assessment.
c. Outcome: The prediction of water solubility yields a useful result for further evaluation.
d. Conclusion: The result is considered as useful for regulatory purposes.
Guideline:
other: REACH guidance on QSARs R.6
Principles of method if other than guideline:
Individual model WSKOWWIN included in the Estimation Programs Interface (EPI) Suite v4.11.
The Estimation Programs Interface was developed by the US Environmental Agency's Office of Pollution Prevention and Toxics and Syracuse Research Corporation (SRC).
Type of method:
other: QSAR prediction
Specific details on test material used for the study:
S=C(SSCCCCCCSSC(=S)N(Cc1ccccc1)Cc2ccccc2)N(Cc3ccccc3)Cc4cccc4
Water solubility:
0 mg/L
Conc. based on:
test mat.
Remarks on result:
other: QSAR predicted value

Validity of model:
1. Defined Endpoint: Water solubility
2. Unambiguous algorithm: WSKOWWIN estimates water solubility with one of two possible equations. The equation without melting point was used in this case:
log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + ΣCorrections
where MW is molecular weight and log Kow is the octanol-water partition coefficient.
The following fragment descriptors were applied for the test substance:
Log Kow = 12
MW = 693.1
Correction for aliphatic amine = 1.008
3. Applicability domain: With a molecular weight of 693.1 g/mole the substance is slightly out of the range of the training set (27.03 – 627.62 g/mole) but molecular weight is not the main descriptor and is not expected to significantly influence the prediction of water solubility. Log Kow is the main descriptor and the estimated log Kow (12) used for the prediction was also slightly higher than the maximum value of 8.27 in the training set. However, the regression analysis shows adequate goodness of fit (r2 = 0.934) and linearity. Therefore, the model is considered robust to predict values outside the dataset.
4. Statistical characteristics:
Correlation coefficient for training set r² = 0.934
Correlation coefficient for validation set r² = 0.902
5. Mechanistic interpretation: The WSKOWWIN program estimates the water solubility of an organic compound using the compounds log octanol-water partition coefficient (log Kow). Log Kow represents the capacity of a compound to dissolve in fatty solution (lipophilicity) and this factor is negatively correlated to the capacity of the compound to dissolve in water (hydrophilicity).
6. Adequacy of prediction: the molecular weight and log Kow of the test substance is slightly above the range in the training set and could lead to increased uncertainty for inadequate models. However, the WSKOWWIN model implemented shows high predictivity based on adequate accuracy and goodness of fit of both the training (r2 = 0.934) and validation (r2 = 0.902) sets. Therefore, the rules applied for the substance appear appropriate

Conclusions:
The QSAR determination of the water solubility for the test substance using the WSKOWWIN model included in the Estimation Program Interface (EPI) Suite v4.11 revealed a value of 2.1e-8 mg/L mg/L.
Executive summary:

The water solubility for the test substance was predicted based on the estimated log Kow of 12 using the WSKOWWIN model of the Estimation Program Interface (EPI) Suite v 4.11. The water solubility was estimated to be 2.1e-8 mg/L mg/L. The predicted value can be considered reliable yielding a useful result for further assessment.

Endpoint:
water solubility
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, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification
Remarks:
The molecular weight and log Kow of the test substance are slightly above the range in the training set. However, the WSKOWWIN model implemented shows high predictivity based on adequate accuracy and goodness of fit of both the training (r2 = 0.934) and validation (r2 = 0.902) sets.
Justification for type of information:
1. SOFTWARE
Individual model WSKOWWIN included in the Estimation Programs Interface (EPI) Suite.

2. MODEL (incl. version number)
WSKOWWIN v1.43 included in EPISuite v 4.11, 2000 – 2015.

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The SMILES CODE was entered in the initial data entry screen. In addition, the experimental log Kow (10.4) was entered to be used as a model descriptor.

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL

a. Defined endpoint: Water Solubility

b. Explicit algorithm (OECD Principle 2):
This program (WSKOWWIN) estimates the water solubility (WSol) of an organic compound using the compounds log octanol-water partition coefficient (Kow).
WSKOWWIN estimates water solubility for any compound with one of two possible equations:
log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + ΣCorrections (1)
log S (mol/L) = 0.693 - 0.96 log Kow - 0.0092(Tm-25) - 0.00314 MW + ΣCorrections (2)
where MW is molecular weight, Tm is melting point (MP) in deg C [used only for solids]). When a measured MP is available, equation (2) is used; otherwise, the equation (1) with just MW is used. Summation of Corrections (ΣCorrections) are applied as described in Appendix E of WSKOWWIN Help documentation. Corrections are applied to 15 structure types (eg. alcohols, acids, selected phenols, nitros, amines, alkyl pyridines, amino acids, PAHS, multi-nitrogen types, etc); application and magnitude depend on available MP.

c. Descriptor selection:
WSKOWWIN requirement for water solubility estimation includes:
SMILES: This is the structure of the compound as a SMILES notation and allows the estimation of molecular weight.
Melting Pt: WSKOWWIN uses an estimation equation that excludes melting point. In terms of method accuracy, this equation is not as good as the equation that uses a measured melting point.
Log Kow: When a value is entered, it is used to estimate water solubility. If no value is entered, WSKOWWIN estimates a log Kow for every SMILES notation by using the estimation engine from the KOWWIN Program. WSKOWWIN also automatically retrieves experimental log Kow values from a database containing more than 13200 organic compounds with reliably measured values.
In addition, corrections based on residual errors from the initial regression fit are applied to 15 structure types (eg. alcohols, acids, selected phenols, nitros, amines, alkyl pyridines, amino acids, PAHS, multi-nitrogen types, etc). Each correction factor is counted a maximum of once per structure [if applicable], no matter how many times the applicable fragment occurs.

d. Defined domain of applicability: The range of data in the training set could be used to describe the applicability domain of the model. The minimum and the maximum values for molecular weight, water solubilities and log Kow are the following:
Training Set Molecluar Weights: 27.03 - 627.62 g/mol
Training Set Water Solubility Ranges: 4x10-7 mg/L – completely soluble
Training set log Kow: -3.89 – 8.27

e. Statistics for goodness-of-fit:
WSKOWWIN estimates water solubility with one of two possible equations. When an experimental melting point is available, WSKOWWIN applies the equation containing both a melting point and the molecular weight (MW) parameters. In the absence of a melting point, the equation containing just the molecular weight is used to make the estimate. All compounds in the 1450 compound training set have known melting points or are known to be liquids at 25C. The equation without melting point was used in this case and the accuracy statistics is:
Correlation coefficient for training set r² = 0.934
Correlation coefficient for validation set r² = 0.902

f. Mechanistic interpretation: The WSKOWWIN program estimates the water solubility of an organic compound using the compounds log octanol-water partition coefficient (log Kow). Log Kow represents the capacity of a compound to dissolve in fatty solution (lipophilicity) and this factor is negatively correlated to the capacity of the compound to dissolve in water (hydrophilicity).

5. APPLICABILITY DOMAIN
a. Descriptor Domains:
With a molecular weight of 693.1 g/mole the substance is slightly out of the range of the training set (27.03 – 627.62 g/mole) but molecular weight is not the main descriptor and is not expected to significantly influence the prediction of water solubility.
Log Kow is the main descriptor and the experimental log Kow (10.4) used for the prediction was also slightly higher than the maximum value of 8.27 in the training set. However, the regression analysis shows adequate goodness of fit (r2 = 0.934) and linearity. Therefore, the model is considered robust to predict values outside the dataset.
b. Mechanism domain: No information available.
c. Metabolic domain: Not relevant.
d. Structural analogues: No information available.

6. ADEQUACY OF THE RESULT
a. Regulatory purpose: The data may be used for regulatory purpose.
b. Approach for regulatory interpretation of the model result: If no experimental data are available, the estimated value may be used to fill data gaps needed for hazard and risk assessment.
c. Outcome: The prediction of water solubility yields a useful result for further evaluation.
d. Conclusion: The result is considered as useful for regulatory purposes.
Guideline:
other: REACH guidance on QSARs R.6
Principles of method if other than guideline:
Individual model WSKOWWIN included in the Estimation Programs Interface (EPI) Suite v4.11.
The Estimation Programs Interface was developed by the US Environmental Agency's Office of Pollution Prevention and Toxics and Syracuse Research Corporation (SRC).
Type of method:
other: QSAR prediction
Specific details on test material used for the study:
S=C(SSCCCCCCSSC(=S)N(Cc1ccccc1)Cc2ccccc2)N(Cc3ccccc3)Cc4cccc4
Water solubility:
0 mg/L
Conc. based on:
test mat.
Remarks on result:
other: QSAR predicted value

Validity of model:
1. Defined Endpoint: Water solubility
2. Unambiguous algorithm: WSKOWWIN estimates water solubility with one of two possible equations. The equation without melting point was used in this case:
log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + ΣCorrections
where MW is molecular weight and log Kow is the octanol-water partition coefficient.
The following fragment descriptors were applied for the test substance:
Log Kow = 10.4
MW = 693.1
Correction for aliphatic amine = 1.008
3. Applicability domain: With a molecular weight of 693.1 g/mole the substance is slightly out of the range of the training set (27.03 – 627.62 g/mole) but molecular weight is not the main descriptor and is not expected to significantly influence the prediction of water solubility. Log Kow is the main descriptor and the experimental log Kow (10.4) used for the prediction was also slightly higher than the maximum value of 8.27 in the training set. However, the regression analysis shows adequate goodness of fit (r2 = 0.934) and linearity. Therefore, the model is considered robust to predict values outside the dataset.
4. Statistical characteristics:
Correlation coefficient for training set r² = 0.934
Correlation coefficient for validation set r² = 0.902
5. Mechanistic interpretation: The WSKOWWIN program estimates the water solubility of an organic compound using the compounds log octanol-water partition coefficient (log Kow). Log Kow represents the capacity of a compound to dissolve in fatty solution (lipophilicity) and this factor is negatively correlated to the capacity of the compound to dissolve in water (hydrophilicity).
6. Adequacy of prediction: the molecular weight and log Kow of the test substance are slightly above the range in the training set and could lead to increased uncertainty for inadequate models. However, the WSKOWWIN model implemented shows high predictivity based on adequate accuracy and goodness of fit of both the training (r2 = 0.934) and validation (r2 = 0.902) sets. Therefore, the rules applied for the substance appear appropriate

Conclusions:
The QSAR determination of the water solubility for the test substance using the WSKOWWIN model included in the Estimation Program Interface (EPI) Suite v4.11 revealed a value of 5.2e-7 mg/L.
Executive summary:

The water solubility for the test substance was predicted based on the experimental log Kow of 10.4 using the WSKOWWIN model of the Estimation Program Interface (EPI) Suite v 4.11. The water solubility was estimated to be 5.2e-7 mg/L. The predicted value can be considered reliable yielding a useful result for further assessment.

Endpoint:
water solubility
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
Individual model WATERNT included in the Estimation Programs Interface (EPI) Suite.

2. MODEL (incl. version number)
WATERNT v1.02 included in EPISuite v 4.11, 2000 – 2015.

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The SMILES CODE was entered in the initial data entry screen.

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
a. Defined endpoint: Water Solubility

b. Explicit algorithm (OECD Principle 2):
The program methodology is known as an Atom/Fragment Contribution (AFC) method. WATERNT uses a "fragment constant" methodology to predict water solubility. In a "fragment constant" method, a structure is divided into atoms/fragments and coefficient values of each fragment or group are summed together to yield the water solubility estimate.
The equation is as follows:
log WatSol (moles/L) = Σ(fi * ni) + Σ(cj * nj) + 0.24922
(n = 1128, correlation coef (r2) = 0.940, standard deviation = 0.537, avg deviation = 0.355)
where Σ(fi * ni) is the summation of fi (the coefficient for each atom/fragment) times ni (the number of times the atom/fragment occurs in the structure) and Σ(cj * nj) is the summation of cj (the coefficient for each correction factor) times nj (the number of times the correction factor is applied in the molecule).
The program requires only a chemical structure to estimate water solubility. WATERNT initially separates a molecule into distinct atom/fragments. For various types of structures, that water solubility estimates made from atom/fragment values alone could or needed to be improved by inclusion of substructures larger or more complex than "atoms"; hence, correction factors were added to the AFC method.

c. Descriptor selection:
As the program requires only a chemical structure to estimate water solubility, WATERNT initially separates a molecule into distinct atom/fragments.
Each non-hydrogen atom (e.g. carbon, nitrogen, oxygen, sulfur, etc.) in a structure is a "core" for a fragment; the exact fragment is determined by what is connected to the atom. Several functional groups are treated as core "atoms". Connections to each core "atom" are either general or specific. For example, aromatic carbon, aromatic oxygen and aromatic sulfur atoms have nothing but general connections; i.e., the fragment is the same no matter what is connected to the atom. In contrast, there are 5 aromatic nitrogen fragments: (a) in a five-member ring, (b) in a six-member ring, (c) if the nitrogen is an oxide-type {i.e. pyridine oxide}, (d) if the nitrogen has a fused ring location (i.e. indolizine), and (e) if the nitrogen has a +5 valence (i.e. N-methyl pyridinium iodide); since the oxide-type is most specific, it takes precedence over the other four. In contrast, the aliphatic carbon atom does not matter what is connected to -CH3, -CH2-, or -CH< , the fragment is the same; however, an aliphatic carbon with no hydrogens has two possible fragments: (a) if there are four single bonds with 3 or more carbon connections and (b) any other not meeting the first criteria.
Additionally, for various types of structures, need to be improved by inclusion of substructures larger or more complex than "atoms" by adding correction factors.
The correction factors have two main groupings: first, factors involving aromatic ring substituent positions and second, miscellaneous factors. In general, the correction factors are values for various steric interactions, hydrogen-bondings, and effects from polar functional substructures. Individual correction factors were selected through a tedious process of correlating the differences (between solubility estimates from atom/fragments alone and measured solubility values) with common substructures.

d. Defined domain of applicability: For each fragment the maximum number of instances of that fragment in any of the 1128 training set compounds is located in Appendix D of the help menu of the EPISuite data entry page. The minimum and the maximum values for molecular weight and water solubility are the following:
Training Set Molecluar Weights: 30.30-627.62 g/mol
Training Set Water Solubility Ranges: 4x10-7 mg/L – miscible

e. Statistics for goodness-of-fit:
Correlation coefficient of the total training set r² = 0.940; Correlation coefficient of the total validation set r² = 0.815.
WATERNT has been tested on a validation dataset of 4636 compounds not included in the training set. These 4636 compounds were collected from the PHYSPROP Database. The validation set includes a diverse selection of chemical structures that rigorously test the predictive accuracy of any model. It contains many chemicals that are similar in structure to chemicals in the training set, but also many chemicals that are different from and structurally more complex than chemicals in the training set. The training set includes 1128 compounds.

f. Mechanistic interpretation: WATERNT uses a "fragment constant" methodology to predict water solubility. 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 solubility estimate. Coefficients for individual fragments and groups in WATERNT were derived by multiple regression of >1000 reliably measured water solubility values.

5. APPLICABILITY DOMAIN
a. Descriptor Domains:
i. Molecular weight: With a molecular weight of 693.1 g/mole the substance is slightly out of the range of the training set (30.30 – 627.62 g/mole) but molecular weight is not expected to significantly influence the prediction of water solubility since it is not explicitly included in the model equation.
ii. Structural fragment domain: Regarding the structure, the fragment descriptors used by the program for the estimation of the water solubility are complete and listed in Appendix D of the WATERNT help file, except the N-C(=S)-S fragment value which was estimated to be 0.000 and as a conclusion does not contribute to the prediction.
iii. Mechanism domain: NO INFORMATION AVAILABLE
iv. Metabolic domain: NOT RELEVANT

b. Structural analogues: No information available.

6. ADEQUACY OF THE RESULT
a. Regulatory purpose: The data may be used for regulatory purpose.
b. Approach for regulatory interpretation of the model result: If no experimental data are available, the estimated value may be used to fill data gaps needed for hazard and risk assessment.
c. Outcome: The prediction of water solubility yields a useful result for further evaluation.
d. Conclusion: The result is considered as useful for regulatory purposes.
Guideline:
other: REACH guidance on QSARs R.6
Principles of method if other than guideline:
Individual model WATERNT included in the Estimation Programs Interface (EPI) Suite v4.11.
The Estimation Programs Interface was developed by the US Environmental Agency's Office of Pollution Prevention and Toxics and Syracuse Research Corporation (SRC).
Type of method:
other: QSAR prediction
Specific details on test material used for the study:
S=C(SSCCCCCCSSC(=S)N(Cc1ccccc1)Cc2ccccc2)N(Cc3ccccc3)Cc4cccc4
Water solubility:
0 mg/L
Conc. based on:
test mat.
Remarks on result:
other: QSAR predicted value

Validity of model:
1. Defined Endpoint: Water solubility
2. Unambiguous algorithm: The molecule is separated into distinct atom/fragments using an Atom/Fragment Contribution method. Based on structure of the molecule, the following fragments were applied: aliphatic carbon (-CH2-), -N< aliphatic attach, aromatic carbon (C-H type), aromatic Carbon (C-substituent type), disulfide (-SS-) and N-C(=S)-S (linear). The number of times of the fragments that occurs in the structure of the substance applied by the program is verified.
3. Applicability domain: With a molecular weight of 693.1 g/mole the substance is slightly out of the range of the training set (30.30 – 627.62 g/mole) but molecular weight is not expected to significantly influence the prediction of water solubility since it is not explicitly included in the model equation.
4. Statistical characteristics: Correlation coefficient of the total training set r² = 0.940; Correlation coefficient of the total validation set r² = 0.815.
5. Mechanistic interpretation: WATERNT uses a "fragment constant" methodology to predict water solubility. 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 solubility estimate.
6. Adequacy of prediction: The rules applied for the substance appear appropriate. The N-C(=S)-S fragment is not in the training set and its value was estimated to be 0.000. Therefore, this fragment does not contribute to the prediction and is not expected to influence the predicted value since the predicted value was based on the minimum solubility boundary of the model and not strictly on the fragments.


 

Conclusions:
The QSAR determination of the water solubility for the test substance using the WATERNT model included in the Estimation Program Interface (EPI) Suite v4.11 revealed a value of 6.9e-7 mg/L.
Executive summary:

The water solubility for the test substance was predicted using the WATERNT model of the Estimation Program Interface (EPI) Suite v 4.11. The water solubility was estimated to be 6.9e-7 mg/L. The predicted value can be considered reliable yielding a useful result for further assessment.

Description of key information

The water solubility of the test substance was measured via the column elution method according to the EU method A.6. The observed substance concentrations in this test were well below the limit of quantification (LOQ) of <0.05 mg/L. Two separate runs with a high and low flow rate were used. Although the steady state was not reached in the test, the test substance was still observed (i.e. concentrations above the LOD) and the results of the two runs at different flow rates were not in agreement. The study was stopped, since the conclusion on the solubility could already be reached (<LOQ).


Additional information from QSAR calculations support the conclusion that the test substance is to be considered highly insoluble in water. In calculations conducted with WSKOWWIN v1.43 included in EPI Suite 4.11 based on the partition coefficients (experimental log Kow 10.4 and estimated log Kow 12), water solubilities between of 5.2E-7 mg/L and 2.1E-8 mg/L at 25 °C were estimated, respectively. In addition, a fragment-based estimation was conducted using WATERNT v1.02 included in EPI Suite 4.11 resulting in a predicted solubility of 6.9E-7 mg/L. Based on this weight of evidence, the test substance can be considered highly insoluble in water.

Key value for chemical safety assessment

Water solubility:
0.05 mg/L
at the temperature of:
20 °C

Additional information