Registration Dossier
Registration Dossier
Data platform availability banner - registered substances factsheets
Please be aware that this old REACH registration data factsheet is no longer maintained; it remains frozen as of 19th May 2023.
The new ECHA CHEM database has been released by ECHA, and it now contains all REACH registration data. There are more details on the transition of ECHA's published data to ECHA CHEM here.
Diss Factsheets
Use of this information is subject to copyright laws and may require the permission of the owner of the information, as described in the ECHA Legal Notice.
Reaction mass of lithium sodium 5-amino-3-{[4-(2-{4-[(7-amino-1-hydroxy-3-sulfo-2-naphthyl)diazenyl]-2-sulfophenyl}vinyl)-3-sulfophenyl]diazenyl}-4-hydroxynaphthalene-2,7-disulfonate 2,2'-(methylimino)diethanol (1:1) and 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[6-amino-4-hydroxynaphthalene-2-sulphonic] acid, lithium sodium salt, compound with 2,2'-(methylimino)diethanol and 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[5-amino-4-hydroxynaphthalene-2,7-disulphonic] acid, lithium sodium salt, compound with 2,2'-(methylimino)diethanol
EC number: 916-916-7 | 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
Partition coefficient
Administrative data
Link to relevant study record(s)
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2013
- 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 KOWWIN included in the Estimation Programs Interface (EPI) Suite.
2. MODEL (incl. version number)
KOWWIN v1.68 included in EPISuite v 4.11, ©2000 - 2012
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
A SMILES notation was entered in the initial data entry screen. In the structure window, the molecular weight, structural formula and the structure of the input SMILES notation is shown.
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
a. Defined Endpoint: Octanol-water partition coefficient
b. Explicit algorithm:
The program methodology is known as an Atom/Fragment Contribution (AFC) method. KOWWIN uses a "fragment constant" methodology to predict log P. 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 log P estimate.
The equation is as follows: Log Kow = Sum (fini) + Sum (cjnj) + 0.229, where Sum (fini) 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 (cjnj) is the summation of cj (the coefficient for each correction factor) times nj (the number of times the correction factor occurs (or is applied) in the molecule). The program requires only a chemical structure to estimate a log P. KOWWIN initially separates a molecule into distinct atom/fragments. For various types of structures, that log P 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 a log P, KOWWIN 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, 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 log P estimates from atom/fragments alone and measured log P values) with common substructures.
d. Defined domain of applicability: For each fragment the maximum number of instances of that fragment in any of the 2447 training set compounds and 10946 validation 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 are the following:
Training Set Molecluar Weights: 18.02-719.92 g/mol
Validation Set Molecular Weights: 27.03-991.15 g/mol
e. Statistical characteristics: Correlation coefficient of the total training set r² = 0.982; Correlation coefficient of the total validation set r² = 0.943.
KOWWIN has been tested on an external validation dataset of 10,946 compounds. 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 average molecular weight of compounds in the validation set is 258.98 versus 199.98 for the training set.
(Training dataset includes a total of 2447 compounds)
(Validation dataset includes a total of 10946 compounds)
f. Mechanistic interpretation: The structural fragments used as descriptors reflect the lipophilic or hydrophobic properties of the substances, and so the octanol-water partition coefficient.
5. APPLICABILITY DOMAIN
a. Descriptor domains:
i. Molecular weights: With a molecular weight of 1030 g/mol the substance is not within the range of the training set (18.02 - 719.92 g/mol) but in the range of the validation set (27.03 - 991.15 g/mol).
ii. Structural fragment domain: Regarding the structure of the substance, the fragment descriptors found by the program are complete and listed in Appendix D (KOWWIN Fragment and Correction Factor descriptors). Additionally the substance is not listed in Appendix F (Compounds that exceed the Fragment & Molecular Weight Domains).
iii. Mechanism domain: No information available
iv. Metabolic domain, if relevant: Not relevant
b. Structural analogues: No information available
i. Considerations on structural analogues: No information available
c. Uncertainty of the prediction: 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[5-amino-4-hydroxynaphthalene-2,7-disulphonic] acid, lithium sodium salt, compound with 2,2'-(methylimino)diethanol is highly complex but the rules applied for the substance still appear appropriate. An individual uncertainty for the investigated substance is the molecular weight which exceeds the range of the trainging set.
6. ADEQUACY OF THE RESULT
a. Regulatory purpose: The data may be used under any regulatory purpose.
b. Approach for regulatory interpretation of the model result: If no experimental data are available, the estimated value is used to fill data gaps needed for hazard and risk assessment, classification and labelling and PBT / vPvB assessment. Further the value can be used for other calculations.
c. Outcome: The prediction of the logarithmic octanol-water partition coefficient yields a useful result for further evaluation.
d. Conclusion: The result is considered as useful for regulatory purposes. - Guideline:
- other: REACH guidance QSARs R6, May/July 2008
- Principles of method if other than guideline:
- Estimation Program Interface EPI-Suite version 4.1: KOWWIN for estimating the logarithmic octanol-water partition coefficient (log Kow).
The Estimation Programs Interface was developed by the US Environmental Agency's Office of Pollution Prevention and Toxics and Syracuse Research Corporation (SRC).© 2000 - 2011 U.S. Environmental Protection Agency for EPI SuiteTM (Published online in January 2011). - GLP compliance:
- no
- Type of method:
- other: QSAR
- Partition coefficient type:
- octanol-water
- Type:
- log Pow
- Partition coefficient:
- 1.823
- Temp.:
- 25 °C
- Remarks on result:
- other: pH not specified
- Conclusions:
- The QSAR determination of the logarithmic octanol-water partition coefficient for the substance using the model KOWWIN included in the Estimation Program Interface (EPI) Suite v4.1 revealed a value of 1.8230 of the substance.
- Executive summary:
The logarithmic octanol-water partition coefficient (log Kow) for the substance was predicted using the QSAR calculation of the Estimation Program Interface (EPI) Suite v 4.1. The log Kow was estimated to be 1.8230.
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2013
- 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 KOWWIN included in the Estimation Programs Interface (EPI) Suite.
2. MODEL (incl. version number)
KOWWIN v1.68 included in EPISuite v 4.11, ©2000 - 2012
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
A SMILES notation was entered in the initial data entry screen. In the structure window, the molecular weight, structural formula and the structure of the input SMILES notation is shown.
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
a. Defined Endpoint: Octanol-water partition coefficient
b. Explicit algorithm:
The program methodology is known as an Atom/Fragment Contribution (AFC) method. KOWWIN uses a "fragment constant" methodology to predict log P. 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 log P estimate.
The equation is as follows: Log Kow = Sum (fini) + Sum (cjnj) + 0.229, where Sum (fini) 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 (cjnj) is the summation of cj (the coefficient for each correction factor) times nj (the number of times the correction factor occurs (or is applied) in the molecule). The program requires only a chemical structure to estimate a log P. KOWWIN initially separates a molecule into distinct atom/fragments. For various types of structures, that log P 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 a log P, KOWWIN 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, 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 log P estimates from atom/fragments alone and measured log P values) with common substructures.
d. Defined domain of applicability: For each fragment the maximum number of instances of that fragment in any of the 2447 training set compounds and 10946 validation 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 are the following:
Training Set Molecluar Weights: 18.02-719.92 g/mol
Validation Set Molecular Weights: 27.03-991.15 g/mol
e. Statistical characteristics: Correlation coefficient of the total training set r² = 0.982; Correlation coefficient of the total validation set r² = 0.943.
KOWWIN has been tested on an external validation dataset of 10,946 compounds. 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 average molecular weight of compounds in the validation set is 258.98 versus 199.98 for the training set.
(Training dataset includes a total of 2447 compounds)
(Validation dataset includes a total of 10946 compounds)
f. Mechanistic interpretation: The structural fragments used as descriptors reflect the lipophilic or hydrophobic properties of the substances, and so the octanol-water partition coefficient.
5. APPLICABILITY DOMAIN
a. Descriptor domains:
i. Molecular weights: With a molecular weight of 870 g/mol the substance is not within the range of the training set (18.02 - 719.92 g/mol) but in the range of the validation set (27.03 - 991.15 g/mol).
ii. Structural fragment domain: Regarding the structure of the substance, the fragment descriptors found by the program are complete and listed in Appendix D (KOWWIN Fragment and Correction Factor descriptors). Additionally the substance is not listed in Appendix F (Compounds that exceed the Fragment & Molecular Weight Domains).
iii. Mechanism domain: No information available
iv. Metabolic domain, if relevant: Not relevant
b. Structural analogues: No information available
i. Considerations on structural analogues: No information available
c. Uncertainty of the prediction: 3,3'-[vinylenebis[(3-sulpho-p-phenlyene)azo]]bis[6-amino-4-hydroxynaphthalene-2-sulphonic] acid, lithium sodium salt, compound with 2,2'-(methylimino)diethanol is highly complex but the rules applied for the substance still appear appropriate. An individual uncertainty for the investigated substance is the molecular weight which exceeds the range of the trainging set.
6. ADEQUACY OF THE RESULT
a. Regulatory purpose: The data may be used under any regulatory purpose.
b. Approach for regulatory interpretation of the model result: If no experimental data are available, the estimated value is used to fill data gaps needed for hazard and risk assessment, classification and labelling and PBT / vPvB assessment. Further the value can be used for other calculations.
c. Outcome: The prediction of the logarithmic octanol-water partition coefficient yields a useful result for further evaluation.
d. Conclusion: The result is considered as useful for regulatory purposes. - Guideline:
- other: REACH guidance QSARs R6, May/July 2008
- Principles of method if other than guideline:
- Estimation Program Interface EPI-Suite version 4.1: KOWWIN for estimating the logarithmic octanol-water partition coefficient (log Kow).
The Estimation Programs Interface was developed by the US Environmental Agency's Office of Pollution Prevention and Toxics and Syracuse Research Corporation (SRC).© 2000 - 2011 U.S. Environmental Protection Agency for EPI SuiteTM (Published online in January 2011). - GLP compliance:
- no
- Type of method:
- other: QSAR
- Partition coefficient type:
- octanol-water
- Type:
- log Pow
- Partition coefficient:
- 3.718
- Temp.:
- 25 °C
- Remarks on result:
- other: pH not specified
- Conclusions:
- The QSAR determination of the logarithmic octanol-water partition coefficient for the substance using the model KOWWIN included in the Estimation Program Interface (EPI) Suite v4.1 revealed a value of 3.7178 of the substance. The predicted value can be considered reliable yielding a useful result for further assessment.
- Executive summary:
The logarithmic octanol-water partition coefficient (log Kow) for the substance was predicted using the QSAR calculation of the Estimation Program Interface (EPI) Suite v 4.1. The log Kow was estimated to be 3.7178. The predicted value can be considered reliable yielding a useful result for further assessment.
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2013
- 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 KOWWIN included in the Estimation Programs Interface (EPI) Suite.
2. MODEL (incl. version number)
KOWWIN v1.68 included in EPISuite v 4.11, ©2000 - 2012
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
A SMILES notation was entered in the initial data entry screen. In the structure window, the molecular weight, structural formula and the structure of the input SMILES notation is shown.
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
a. Defined Endpoint: Octanol-water partition coefficient
b. Explicit algorithm:
The program methodology is known as an Atom/Fragment Contribution (AFC) method. KOWWIN uses a "fragment constant" methodology to predict log P. 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 log P estimate.
The equation is as follows: Log Kow = Sum (fini) + Sum (cjnj) + 0.229, where Sum (fini) 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 (cjnj) is the summation of cj (the coefficient for each correction factor) times nj (the number of times the correction factor occurs (or is applied) in the molecule). The program requires only a chemical structure to estimate a log P. KOWWIN initially separates a molecule into distinct atom/fragments. For various types of structures, that log P 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 a log P, KOWWIN 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, 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 log P estimates from atom/fragments alone and measured log P values) with common substructures.
d. Defined domain of applicability: For each fragment the maximum number of instances of that fragment in any of the 2447 training set compounds and 10946 validation 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 are the following:
Training Set Molecluar Weights: 18.02-719.92 g/mol
Validation Set Molecular Weights: 27.03-991.15 g/mol
e. Statistical characteristics: Correlation coefficient of the total training set r² = 0.982; Correlation coefficient of the total validation set r² = 0.943.
KOWWIN has been tested on an external validation dataset of 10,946 compounds. 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 average molecular weight of compounds in the validation set is 258.98 versus 199.98 for the training set.
(Training dataset includes a total of 2447 compounds)
(Validation dataset includes a total of 10946 compounds)
f. Mechanistic interpretation: The structural fragments used as descriptors reflect the lipophilic or hydrophobic properties of the substances, and so the octanol-water partition coefficient.
5. APPLICABILITY DOMAIN
a. Descriptor domains:
i. Molecular weights: With a molecular weight of 950 g/mol the substance is not within the range of the training set (18.02 - 719.92 g/mol) but in the range of the validation set (27.03 - 991.15 g/mol).
ii. Structural fragment domain: Regarding the structure of the substance, the fragment descriptors found by the program are complete and listed in Appendix D (KOWWIN Fragment and Correction Factor descriptors). Additionally the substance is not listed in Appendix F (Compounds that exceed the Fragment & Molecular Weight Domains).
iii. Mechanism domain: No information available
iv. Metabolic domain, if relevant: Not relevant
b. Structural analogues: No information available
i. Considerations on structural analogues: No information available
c. Uncertainty of the prediction: 2,7-napthalenedisulfonic acid, 5-amino-3-[[4-[2-[4-[(7-amino-1-hydroxy-3-sulfo-2-naphthalenyl)azo]-2-sulphenyl]ethenyl]-3-sulphophenyl]azo]-4-hydroxy-, lithium sodium salt, compound with 2,2'-(methylimino)bis[ethanol] is highly complex but the rules applied for the substance still appear appropriate. An individual uncertainty for the investigated substance is the molecular weight which exceeds the range of the trainging set.
6. ADEQUACY OF THE RESULT
a. Regulatory purpose: The data may be used under any regulatory purpose.
b. Approach for regulatory interpretation of the model result: If no experimental data are available, the estimated value is used to fill data gaps needed for hazard and risk assessment, classification and labelling and PBT / vPvB assessment. Further the value can be used for other calculations.
c. Outcome: The prediction of the logarithmic octanol-water partition coefficient yields a useful result for further evaluation.
d. Conclusion: The result is considered as useful for regulatory purposes. - Guideline:
- other: REACH guidance QSARs R6, May/July 2008
- Principles of method if other than guideline:
- Estimation Program Interface EPI-Suite version 4.1: KOWWIN for estimating the logarithmic octanol-water partition coefficient (log Kow).
The Estimation Programs Interface was developed by the US Environmental Agency's Office of Pollution Prevention and Toxics and Syracuse Research Corporation (SRC).© 2000 - 2011 U.S. Environmental Protection Agency for EPI SuiteTM (Published online in January 2011). - GLP compliance:
- no
- Type of method:
- other: QSAR
- Partition coefficient type:
- octanol-water
- Type:
- log Pow
- Partition coefficient:
- 2.77
- Temp.:
- 25 °C
- Remarks on result:
- other: pH not specified
- Conclusions:
- The QSAR determination of the logarithmic octanol-water partition coefficient for the substance using the model KOWWIN included in the Estimation Program Interface (EPI) Suite v4.1 revealed a value of 2.7704 of the substance.
- Executive summary:
The logarithmic octanol-water partition coefficient (log Kow) for the substance was predicted using the QSAR calculation of the Estimation Program Interface (EPI) Suite v 4.1. The log Kow was estimated to be 2.7704.
Referenceopen allclose all
Validity of model:
1. Defined Endpoint: Octanol-water partition coefficient
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: =CH- or =C<, aromatic carbon, -OH, -N, -SO2 -OH, -N=N- and Ring reaction -> -OH ortho to Azo. 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 1030 g/mole the substance is not within in the range of the training set (18.02 - 719.92) and not in the range of the validation set (27.03 - 991.15).
3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[5-amino-4-hydroxynaphthalene-2,7-disulphonic] acid, lithium sodium salt, compound with 2,2'-(methylimino)diethanol is identified as structural analogue, because the substance contains the same structural fragments as CAS-no. 75701 -34 -7 and CAS-no. 85269 -32 -5.
4. Statistical characteristics: Correlation coefficient of the total training set r² = 0.982; Correlation coefficient of the total validation set r² = 0.943.
5. Mechanistic interpretation: The structural fragments used as descriptors reflect the lipophilic or hydrophobic properties of the substances, and so the octanol-water partition coefficient.
6. Adequacy of prediction: The result for 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[5-amino-4-hydroxynaphthalene-2,7-disulphonic] acid, lithium sodium salt, compound with 2,2'-(methylimino)diethanol falls not in the applicability domain described above and the estimation rules applied for the substance. Therefore the predicted value can be considered as not reliable yielding a useful result for further assessment.
Validity of model:
1. Defined Endpoint: Octanol-water partition coefficient
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: =CH- or =C<, aromatic carbon, -OH, -N, -SO2-OH, N=N- and Ring reaction -> -OH ortho to Azo. 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 870 g/mole the substance is not within the range of the training set (18.02 - 719.92) but it is in the range of the validation set (27.03 - 991.15). 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[6-amino-4-hydroxynaphthalene-2-sulphonic] acid, lithium sodium salt , compound with 2,2'-(methylimino)diethanol is identified as structural analogue, because the substance contains the same structural fragments as CAS-no. 75701 -36 -9 and CAS-no. 85269 -32 -5.
4. Statistical characteristics: Correlation coefficient of the total training set r² = 0.982; Correlation coefficient of the total validation set r² = 0.943.
5. Mechanistic interpretation: The structural fragments used as descriptors reflect the lipophilic or hydrophobic properties of the substances, and so the octanol-water partition coefficient.
6. Adequacy of prediction: The result for the 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[6-amino-4-hydroxynaphthalene-2-sulphonic] acid, lithium sodium salt , compound with 2,2'-(methylimino)diethanol falls within the applicability domain described above and the estimation rules applied for the substance appear appropriate. Therefore the predicted value can be considered reliable yielding a useful result for further assessment.
Validity of model:
1. Defined Endpoint: Octanol-water partition coefficient
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: =CH- or =C<, aromatic carbon, -OH, -N, -SO2 -OH, -N=N and Ring reaction -> -OH ortho to Azo. 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 950 g/mole the substance is not within the range of the training set (18.02 - 719.92) but it is in the range of the validation set (27.03 - 991.15).
2,7-Naphthalenedisulfonic acid, 5-amino-3-[[4-[2-[4-[(7-amino-1-hydroxy-3-sulfo-2-naphthalenyl)azo]-2-sulfophenyl]ethenyl]-3-sulfophenyl]azo]-4-hydroxy-, lithium sodium salt, compd. with 2,2'-(methylimino)bis[ethanol] is identified as structural analogue, because the substance contains the same structural fragments as CAS-no. 75701 -36 -9 and CAS-no. 75701 -34 -7.
4. Statistical characteristics: Correlation coefficient of the total training set r² = 0.982; Correlation coefficient of the total validation set r² = 0.943.
5. Mechanistic interpretation: The structural fragments used as descriptors reflect the lipophilic or hydrophobic properties of the substances, and so the octanol-water partition coefficient.
6. Adequacy of prediction: The result for 2,7-Naphthalenedisulfonic acid, 5-amino-3-[[4-[2-[4-[(7-amino-1-hydroxy-3-sulfo-2-naphthalenyl)azo]-2-sulfophenyl]ethenyl]-3-sulfophenyl]azo]-4-hydroxy-, lithium sodium salt, compd. with 2,2'-(methylimino)bis[ethanol] falls not in the applicability domain described above and the estimation rules applied for the substance. Therefore the predicted value can be considered as not reliable yielding a useful result for further assessment.
Description of key information
The partition coefficient was estimated from QSAR calculations for the three main components of the substance and determined to be in the range of 1.82 - 3.72.
Key value for chemical safety assessment
- Log Kow (Log Pow):
- 3
Additional information
The substance is handeled and used as an aqueous solution with a concentration of about 41%. With an estimated log Kow of about 3 the Shake Flask Method would be appropriate but may not be applied as the substance is surface active. Alternatively, the HPLC method could be applied but this may also not be used for a surface active substance.
Therefore, the only possible log Kow determination is via estimation with a valid and reliable QSAR method and this approach was used here.
The substance consists of three main components that were used for the log Kow estimation:
Component 1: CAS 83783-94-2; 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[5-amino-4-hydroxynaphthalene-2,7-disulphonic] acid, lithium sodium salt, compound with 2,2'-(methylimino)diethanol: LogPow = 1.82
Component 2:CAS 83783-96-4; 2,7-Naphthalenedisulfonic acid, 5-amino-3-[[4-[2-[4-[(7-amino-1-hydroxy-3-sulfo-2-naphthalenyl)azo]-2 -sulfophenyl]ethenyl]-3-sulfophenyl]azo]-4-hydroxy-, lithium sodium salt, compd. with 2,2'-(methylimino)bis[ethanol]: LogPow = 2.77
Component 3: CAS 83783-95-3; 3,3'-[vinylenebis[(3-sulpho-p-phenylene)azo]]bis[6-amino-4-hydroxynaphthalene-2-sulphonic] acid, lithium sodium salt , compound with 2,2'-(methylimino)diethanol: LogPow = 3.72
The log Kow of the three main components is estimated to be in the range of 1.82 - 3.72 which is assumed to be representative for the substance in total and the most critical log Kow of 3.72 is taken forward to the risk assessment.
Information on Registered Substances comes from registration dossiers which have been assigned a registration number. The assignment of a registration number does however not guarantee that the information in the dossier is correct or that the dossier is compliant with Regulation (EC) No 1907/2006 (the REACH Regulation). This information has not been reviewed or verified by the Agency or any other authority. The content is subject to change without prior notice.
Reproduction or further distribution of this information may be subject to copyright protection. Use of the information without obtaining the permission from the owner(s) of the respective information might violate the rights of the owner.