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EC number: - | CAS number: -
- Life Cycle description
- Uses advised against
- Endpoint summary
- Appearance / physical state / colour
- Melting point / freezing point
- Boiling point
- Density
- Particle size distribution (Granulometry)
- Vapour pressure
- Partition coefficient
- Water solubility
- Solubility in organic solvents / fat solubility
- Surface tension
- Flash point
- Auto flammability
- Flammability
- Explosiveness
- Oxidising properties
- Oxidation reduction potential
- Stability in organic solvents and identity of relevant degradation products
- Storage stability and reactivity towards container material
- Stability: thermal, sunlight, metals
- pH
- Dissociation constant
- Viscosity
- Additional physico-chemical information
- Additional physico-chemical properties of nanomaterials
- Nanomaterial agglomeration / aggregation
- Nanomaterial crystalline phase
- Nanomaterial crystallite and grain size
- Nanomaterial aspect ratio / shape
- Nanomaterial specific surface area
- Nanomaterial Zeta potential
- Nanomaterial surface chemistry
- Nanomaterial dustiness
- Nanomaterial porosity
- Nanomaterial pour density
- Nanomaterial photocatalytic activity
- Nanomaterial radical formation potential
- Nanomaterial catalytic activity
- Endpoint summary
- Stability
- Biodegradation
- Bioaccumulation
- Transport and distribution
- Environmental data
- Additional information on environmental fate and behaviour
- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
- Long-term toxicity to fish
- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
- Toxicity to aquatic plants other than algae
- Toxicity to microorganisms
- Endocrine disrupter testing in aquatic vertebrates – in vivo
- Toxicity to other aquatic organisms
- Sediment toxicity
- Terrestrial toxicity
- Biological effects monitoring
- Biotransformation and kinetics
- Additional ecotoxological information
- Toxicological Summary
- Toxicokinetics, metabolism and distribution
- Acute Toxicity
- Irritation / corrosion
- Sensitisation
- Repeated dose toxicity
- Genetic toxicity
- Carcinogenicity
- Toxicity to reproduction
- Specific investigations
- Exposure related observations in humans
- Toxic effects on livestock and pets
- Additional toxicological data
Water solubility
Administrative data
Link to relevant study record(s)
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 6.35 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.046 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.04558 mg/L at 25°C (log Kow: 6.35 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 0.04558 mg/L at 25°C (log Kow: 6.35 used as input, No MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 6.94 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.014 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.01429 mg/L at 25°C (log Kow: 6.94 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 0.01429 mg/L at 25°C (log Kow: 6.94 used as input, No MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 4.84 (QSAR, EpiSuite)
- Water solubility:
- ca. 7.959 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 7.959 mg/L at 25°C (log Kow: 4.84 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 7.959 mg/L at 25°C (log Kow: 4.84 used as input, No MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 6.12 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.072 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.07164 mg/L at 25°C (log Kow: 6.12 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated (QSAR) water solubility of test item is estimated to be 0.07164 mg/L at 25°C (log Kow: 6.12 used as input, no MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 6.19 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.22 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.2202 mg/L at 25°C (log Kow: 6.19 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 0.2202 mg/L at 25°C (log Kow: 6.19 used as input, No MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 4.33 (QSAR, EpiSuite)
- Water solubility:
- ca. 21.88 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 21.88 mg/L at 25°C (log Kow: 4.33 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated (QSAR) water solubility of test item is estimated to be 21.88 mg/L at 25°C (log Kow: 4.33 used as input, no MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 5.74 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.15 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.1504 mg/L at 25°C (log Kow: 5.74 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated (QSAR) water solubility of test item is estimated to be 0.1504 mg/L at 25°C (log Kow: 5.74 used as input, no MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 2.29 (QSAR, EpiSuite)
- Water solubility:
- ca. 2 083 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 2083 mg/L at 25°C (log Kow: 2.29 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 2083 mg/L at 25°C (log Kow: 2.29 used as input, No MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 5.82 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.129 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.1292 mg/L at 25°C (log Kow: 5.82 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 0.1292 mg/L at 25°C (log Kow: 5.82 used as input, No MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 6.99 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.013 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.01295 mg/L at 25°C (log Kow: 6.99 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 0.01295 mg/L at 25°C (log Kow: 6.99 used as input, No MP used as input).
- Endpoint:
- water solubility
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Study period:
- March 2022
- 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:
- QSAR prediction:
The value is not an experimental result, however the QSAR model is recommended by the ECHA guidance document on information requirements, and is well documented with regard to validation parameters according to OECD principles. In addition, the substance investigated matches with the parameters of training set compounds and the result is considered fully reliable. - Reason / purpose for cross-reference:
- reference to other study
- Reason / purpose for cross-reference:
- reference to other study
- Qualifier:
- no guideline followed
- Principles of method if other than guideline:
- QSAR estimation
- Specific details on test material used for the study:
- Input: Log Kow: 6.26 (QSAR, EpiSuite)
- Water solubility:
- ca. 0.054 mg/L
- Temp.:
- 25 °C
- Remarks on result:
- other: Conc. based, loading rate, incubation duration and pH not provided
- Conclusions:
- The calculated (QSAR) water solubility of test item is estimated to be 0.0544 mg/L at 25°C (log Kow: 6.26 used as input, no MP used as input).
- Executive summary:
The water solubility of the test substance was estimated using the recommended QSAR model WSKOWwin v1.42. Even if the result shall be considered with restrictions considering the type of information (QSAR), the test item properties are within the application of domain of the model, so validation apply with acceptable restrictions.
The calculated water solubility is 0.0544 mg/L at 25°C (log Kow: 6.26 used as input, No MP used as input).
Referenceopen allclose all
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Hydrocarbon | -0.5370 | 33 |
which is applied to any aliphatic hydrocarbon that contains just carbons and hydrogens.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Hydrocarbon | -0.5370 | 33 |
which is applied to any aliphatic hydrocarbon that contains just carbons and hydrogens.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No in Dataset |
Alcohol, aliphatic | 0.5100 | 18 |
which is applied to to compounds containing one -OH group attached to an aliphatic carbon.Compounds with multiple -OH groups (e.g. ethylene glycol) are excluded. Compounds containing acetamide, amino-azo-, or -S(=O) type functions (e.g. sulfonamides or sulfoxides) are also excluded.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Hydrocarbon | -0.5370 | 33 |
which is applied to any aliphatic hydrocarbon that contains just carbons and hydrogens.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
No correction was appplicable.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No in Dataset |
Alcohol, aliphatic | 0.5100 | 18 |
which is applied to to compounds containing one -OH group attached to an aliphatic carbon.Compounds with multiple -OH groups (e.g. ethylene glycol) are excluded. Compounds containing acetamide, amino-azo-, or -S(=O) type functions (e.g. sulfonamides or sulfoxides) are also excluded.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Hydrocarbon | -0.5370 | 33 |
which is applied to any aliphatic hydrocarbon that contains just carbons and hydrogens.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Acid, aliphatic | -0.395 | 70 |
which is applied to compounds with the aliphatic acid function. Amino acids and compounds with the C(=O)-N-C-COOH structure are excluded.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Hydrocarbon | -0.5370 | 33 |
which is applied to any aliphatic hydrocarbon that contains just carbons and hydrogens.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Hydrocarbon | -0.5370 | 33 |
which is applied to any aliphatic hydrocarbon that contains just carbons and hydrogens.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Estimation Accuracy
Training
The regression equations used by the WSKOWWIN program were trained with a dataset of 1450 compounds.
As noted in the methodology section, 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 25°C. In this particular case, where the melting point of the test item has not been used as input the accurancy statistic is as follows:
r2: 0.934
std deviation: 0.585
avg deviation: 0.442
Validation
The WSKOWWIN estimation equations were initially validated on two datasets of compounds that were not included in the model training. A relatively small dataset was tested that consisted of 85 compounds having experimental log Kow values, but no available melting points. Many compounds in the 85 compound test set decompose before melting and would theoretically have very high melting points (e.g. amino acids and compounds having multiple nitrogens). The accuracy statistics for the equation used by WSKOWWIN are:
number: 85
r2: 0.865
std deviation: 0.961
avg deviation: 0.714
A much larger dataset of 817 compounds was also tested. All 817 compounds had experimental melting points, but none of the 817 compounds had a reliable experimental log Kow. The log Kow values used for the validation-testing were estimated (primarily using the KOWWIN program available at that time); therefore, the water solubility estimates are based on estimates for log Kow. Typically, estimates based on estimates reduce estimation accuracy, but this type of validation can provide insight into the ability of the method. The accuracy statistics for this dataset are:
number: 817
r2: 0.902
std deviation: 0.615
avg deviation: 0.480
Estimation Domain
Appendix E of the Help section in EpiSuite gives the number compounds in the 1450 compound training set containing each of the correction factors. The WSKOWWIN program applies an individual correction factor only once per structure [if at all] regardless of how many instances of the applicable structural feature occur in the structure. The minimum number of instances is zero and the maximum is one.
In this particular case:
Equation Used to Make Water Sol estimate: Log S (mol/L) = 0.796 - 0.854 log Kow - 0.00728 MW + Correction
and the following correction has been applied:
Correction Factor shown in Wskowwin Program | Without MP Coef | No. In Dataset |
Hydrocarbon | -0.5370 | 33 |
which is applied to any aliphatic hydrocarbon that contains just carbons and hydrogens.
Range of water solubilities in the Training set:
Minimum = 4 x 10-7 mg/L (octachlorodibenzo-p-dioxin)
Maximum = completely soluble (various)
Range of Molecular Weights in the Training set:
Minimum = 27.03 (hydrocyanic acid)
Maximum = 627.62 (hexabromobiphenyl)
Range of Log Kow values in the Training set:
Minimum = -3.89 (aspartic acid)
Maximum = 8.27 (decachlorobiphenyl)
Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that water solubility estimates are less accurate for compounds outside the MW range, water solubility range and log Kow range of the 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 correction factor was developed. These points should be taken into consideration when interpreting model results.
Description of key information
The Water Solubility of the test item based on water solubility of known constituents is estimated to be in the range between 0.01295 and 2083 mg/L at 25°C.
Key value for chemical safety assessment
Additional information
No study was conducted on the test chemical iself, as not relevant for an UVCB.
The water solubility, WS, of the test item was estimated from data on its known constituents (covering almost the 64% of the composition). Data on the known constituents were reliably calculated using the recommended QSAR(EpiSuite). All the constituents fall inside the Applicability domain of the model.
The results are listed below:
Constituent | Wate Solubility (mg/L) at 25°C |
Thujopsene | 0.07164 |
Cedrol | 21.88 |
Cedrene alpha | 0.1504 |
Cedrene beta | 0.1292 |
Cuparene | 0.2202 |
Widdrol | 7.959 |
alpha Chamigrene | 0.01429 |
β-himachalene | 0.04558 |
Alpha-Pseudowiddrene | 0.0544 |
Beta-Acoradiene | 0.01295 |
3-phenylpropionic acid | 2083 |
As the substance is an UVCB the water solubility of the test item will be determined using the lowest and the highest water solubility values of known constituents.
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