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EC number: 214-527-0 | CAS number: 1141-38-4
- 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:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Hou & Xu is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
The model (SLOGP v1.0) estimates the log Pow values by summing the contribution of atom-weighted solvent accessible surface Ares (SASA) and correction factors. A total of 100 atom and group types were used to classify atoms with different chemical environments, and two correlation factors were used to consider the intermolecular hydrophobic interactions and intramolecular hydrogen bonds. Coefficient values for 100 atoms and groups and two correction factors have been derived from a training set of 1850 compounds. The parametrization procedure from different atom and group types based on SMARTS language, and the correction factors were determined by substructure searching; then, SASA for each atom and group type was calculated and added; finally, multivariate linear regression analysis was applied to optimize the hydrophobic parameters for different atom and group types and correction factors in order to reproduce the experimental log Pow. The correlation cased on the training set gives a model with a correlation coefficient (r) of 0.988, the standard deviation (SD) of 0.368 log units, and the absolute unsigned mean error of 0.261. Comparison of various procedures of log Pow calculations for the external test set of 138 organic compounds demonstrates that the method bears very good accuracy. More details about the model are stated in the publication which is accessible under DOI 10.1021/ci034007m
6. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- GLP compliance:
- not specified
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.12
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
VEGA QSAR application version 1.2.4 (2017), developed by the Istituto di Ricerche Farmacologiche Mario Negri (Laboratory of Environmental Chemistry and Toxicology) and EPI Suite 4.1, developed by the EPA's Office of Pollutin Prevention Toxics and Syracure Research Corporation (SRC)
2. MODEL (incl. version number)
The model of Meylan et al. is implemented in both software tools
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The SMILES was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
Atom/fragment contribution values, used to estimate the log octanol-water partition coefficient (log P) of organic compounds, have been determined for 130 simple chemical substructures by a multiple linear regression of 1120 compounds with measured log P values. An additional 1231 compounds were used to determine 235 “correction factors” for various substructure orientations. The log P of a compound is estimated by simply summing all atom/fragment contribution values and correction factors occurring in a chemical structure. For the 2351 compound training set, the correlation coefficient (P) for the estimated vs measured log P values is 0.98 with a standard deviation (SD) of 0.22 and an absolute mean error (ME) of 0.16 log units. This atom/fragment contribution (AFC) method was then tested on a separate validation set of 6055 measured log P values that were not used to derive the methodology and yielded an P of 0.943, an SD of 0.408, and an ME of 0.31. The method is able to predict log P within +/- 0.8 log units for over 96% of the experimental dataset of 8406 compounds. Because of the simple atom/fragment methodology, “missing fragments” (a problem encountered in other methods) do not occur in the AFC method. Statistically, it is superior to other comprehensive estimation methods.
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow.
Istituto di Ricerche Farmacologiche
Mario Negri (Laboratory of Environmental Chemistry and Toxicology) - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.93
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- calculation (if not (Q)SAR)
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification
- Justification for type of information:
- The log-log relationship between the bioconcentration tendency of organic chemicals in fish and the z i -octanol/water partition coefficients breaks down for very hydrophobic compounds. The use of parabolic and bilinear models allows this problem to be overcome. The QSAR equation log BCF = 0.910 log P - 1.975 log (6.8 lo-’ P + 1) - 0.786 (n = 154; r = 0.950; s = 0.347; F = 463.51) was found to be a good predictor of bioconcentration in fish.
More details about the model can be found under DOI 10.1080/10629369308028814 - Reason / purpose for cross-reference:
- read-across: supporting information
- Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- GLP compliance:
- no
- Key result
- Type:
- log Pow
- Partition coefficient:
- 1.84
- Remarks on result:
- other: Result of calculation
- Endpoint:
- partition coefficient
- Type of information:
- calculation (if not (Q)SAR)
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification
- Justification for type of information:
- The publication of Veith et al. (1979) describes a method of estimating the bioconcentration factor of organic chemicals in fish. A structure-actovity correlation between the bioconcentration factor (BCF) and Pow of the tested chemicals is desribed in an equation, which permits the estimation of the bioconcentration factor of chemicas to within 60%.
More details regarding the method development are available under DOI 10.1139/f79-146 - Reason / purpose for cross-reference:
- read-across: supporting information
- Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- GLP compliance:
- no
- Key result
- Type:
- log Pow
- Partition coefficient:
- 1.87
- Remarks on result:
- other: Result of calculation
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Ghose et al. is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- GLP compliance:
- no
- Key result
- Type:
- log Pow
- Partition coefficient:
- 1.79
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Broto et al. is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
The model describes a system of additive atomic contributions for the calculation of LogP. The contributions take into account the nature of the atoms and their environment. This system makes it possible to calculate the LogP of most organic molecules with an accuracy of 0.4 log units and makes it possible to evaluate the distribution of lipophilicity on the molecular structure.
According to ChemProp, the values of the fragmentation are originally fitted by two different methods: Monte Carlo and multiple linear regressions. MLR has proofed to be superior.
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.24
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Dubost et al. is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
The principle of deteminng lipophilicity contribution values fi of atomic fragments assumes the additive character of the logarithm of the partition coefficiednt of a molecule to be log P = Σaifi, where ai is a numerical factor indication the frequency of a given atomic fragment (i) in the structure i.e. the number of times this atomic fragment appears in the mulecule. More details about this model can be found under the following DOI: 10.1002/qsar.200430004
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.08
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Wang et al. is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
A new atom-additive method is presented for calculating octanol/water partition coefficient (log P) of organic compounds. The method, XLOGP v2.0, gives log P values by summing the contributions of component atoms and correction factors. Altogether 90 atom types are used to classify carbon, nitrogen, oxygen, sulfur, phosphorus and halogen atoms, and 10 correction factors are used for some special substructures. The contributions of each atom type and correction factor are derived by multivariate regression analysis of 1853 organic compounds with known experimental log P values. The correlation coefficient (r) for fitting the whole set is 0.973 and the standard deviation (s) is 0.349 log units. More details about this model can be found under the following DOI: 10.1023/A:1008763405023
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.52
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Platts et al. is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
A previously published method for the prediction of molecular linear free energy relationship descriptors is tested against experimentally determined partition coefficients in various solvent systems. Sets of partition data between water and octanol, cyclohexane, and chloroform were taken from the literature. For each set of partition data used, r2 values ranged from 0.8 to 0.9 and RMS errors from 0.7 to 1.0 log unit, comparable to errors obtained with previously published models for octanol−water partition. Modified solvation equations for water−octanol and water−cyclohexane partition are presented, and their implications discussed. The possibility of applying the current approach to a wide range of solvation and transport properties is put forward. The partitioning coefficients were calculated according to the following formula:
log Kow = 0.088 + 0.562 E - 1.054 S + 0.032 A - 3.46 BO + 3.814 V
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.2
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Marrero and Gani is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
The model describes a method of the estimation of the Pow and aquaous solubility at ambient temperature. The property values are estimated by using a three-level group-contribution estimation approach requiring only molecular structural information. The primary level uses contributions from simple first-order groups that allow for the description of a wide variety of organic compounds, whereas the higher levels (i.e. second-and third-order groups) involve polyfunctional and structural groups that provide more information about molecular fragments whose description through first-order groups is not possible. The group-contribution values were calculated by linear regression analysos usins a data set of 9560 values for Kow and 2087 values for water solubility. The data set included compound ranging from C3 to C70, including large and heterocyclic compounds. The average absolute error derived by this mode is 0.24 for the Pow.
More details about this model can be found under the following DOI: 10.1021/ie0205290
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.83
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
VEGA QSAR application version 1.2.4 (2017), developed by the Istituto di Ricerche Farmacologiche Mario Negri (Laboratory of Environmental Chemistry and Toxicology)
2. MODEL (incl. version number)
The model of Moriguchi et al. is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The SMILES was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
A method of calculation log Pow has been developed by the authors based on the quantitative structure-log Pow relationship for 1230 organic molecules having a wide variety of structures. The 1230 organic compounds investigated included general aliphatic, aromatic, and heterocyclic molecules together with various drugs and agrochemicals. The predictive structure-log P model obtained by multiple regression analysis involved only 13 parameters for hydrophobic atoms, hydrophilic atoms, their proximity effects, unsaturated bonds, amphoteric property, and several specific functionalities. A saturation effect was recognized in the parameters for hydrophobic and hydrophilic atoms, and unsaturated bonds. The structure-log P relationship was hihgly significant as the F-statistics = 900.4.
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow.
Istituto di Ricerche Farmacologiche
Mario Negri (Laboratory of Environmental Chemistry and Toxicology) - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 2.41
- Remarks on result:
- other: QSAR result
- Endpoint:
- partition coefficient
- Type of information:
- (Q)SAR
- Adequacy of study:
- weight of evidence
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
- Justification for type of information:
- 1. SOFTWARE
Chemprop(TM) Main Module 6.6 developed by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany
2. MODEL (incl. version number)
The model of Klopman et al. is implemented in the software
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS-No was used as identifier
4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL AND APPLICABILITY DOMAIN
A Computer Automated Structure Evaluation (CASE) approach to the calculation of partition coefficient (log P) has been developed. A linear regression equation was obtained linking the log P value of molecules to some of their fragments as identified by a CASE analysis. The relationship was obtained for a database consisting of 935 compounds (r2 = 0.93, s = 0.39, F(39, 895, 0.05) = 316.5). It was found that this approach produced accurate log P estimations even for complex molecules and, in general, gave better results than previously described techniques.
5. ADEQUACY OF THE RESULT
The log Pow is relevant for a chronic aquatic classification. A substance is classified if, amongst others, the log Pow is equal or greater than 4. The result of the present model does not result in a log Pow close to or greater than 4. Another criterion for a chronic classification is the bioaccumulation factor BCF, which must be equal or greater than 500. For 2,6-naphthalene dicarboxylic acid, data is available from a bioaccumulation study. The experimentally derived BCF is 7.7 and hence clearly below the trigger value. It can be assumed that an experimentally derived log Pow would also give a result below the relevant trigger value for log Pow. - Qualifier:
- no guideline required
- Principles of method if other than guideline:
- See field "Justification for type of information"
- Key result
- Type:
- log Pow
- Partition coefficient:
- 3.03
- Remarks on result:
- other: QSAR result
Referenceopen allclose all
Applicability of the domain:
Details regarding the applicability of the domain can be found in the respective model of Hou et al.
A detailed description regarding the applicability of the domain can be found in the attached publication of Bintein et al. As the log Pow values of the chemicals in the trainining set were within the range of 1.12 to 8.60, HNDA would fall within the applicabilty of the domain with a calulated log Pow of 1.84. However, HNDA is a dicarboxylic acid. The estimated pKa value of 3.69 (Chemaxon, implemented in the OECD QSAR toolbox) leads to the assumption, that the amount of dissociated HNDA under environmentally relevant pH values is high, whereas the ability of ionized substances to bioaccumulate is low. Therefore, the log Pow derived here is regarded as the worst-case for a non-dissociated substance.
Applicability of the domain:
Veith et al. tested a data set of 55 substances in a log Pow range of 1 -5.5. With a resulting log Pow of 1.87, HNDA would fall within the applicabilty of the domain. It should be noted, however, the training set of Veith et al. is based on neutral, non-ionized substances. The model is not applicable for to ionic or partly ionized substances, and organometallics. HNDA is a dicarboxylic acid. The estimated pKa value of 3.69 (Chemaxon, implemented in the OECD QSAR toolbox) leads to the assumption, that the amount of dissociated HNDA under environmentally relevant pH values is high, whereas the ability of ionized substances to bioaccumulate is low. Therefore, the log Pow derived here is regarded as the worst-case for a non-dissociated substance.
Description of key information
The log Pow of 2,6 -Naphthalene dicarboxylic acid was estimated by in total 12 QSAR models and calcualtions. A summary of the results is given in the following table:
Author | Log Pow |
Veith et al. (1979) | 1.87 |
Bintein et al. (1993) | 1.84 |
Hou et al. (2003) | 2.12 |
Marrero et al. (2002) | 2.83 |
Dubost et al. (2005) | 2.08 |
Wang et al. (2000) | 2.52 |
Broto et al. (1984) | 2.24 |
Ghose et al. (1989) | 1.79 |
Klopman et al. (1991) | 3.03 |
Platts et al. (2000) | 2.2 |
Meylan et al. (1995) | 2.93 |
Moriguchi et al. (1992) | 2.41 |
All models are scientifically well recognised and published in scientific journals. However, as the publications are not available, the applicability of the domain cannot be proven by each model. But based on the weight of evidence approach, the models in a whole can be considered to be suitable for the estimation of the log Pow, even if some of them do not fall into the applicablity of the respective domain. As the log Pow values were estimated with different models, the median of the values is more suitable as the arithmetic mean, as it is less sensitive for outliers than the arithmetic mean.
Key value for chemical safety assessment
- Log Kow (Log Pow):
- 2.22
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