Registration Dossier

Physical & Chemical properties

Partition coefficient

Currently viewing:

Administrative data

Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
key study
Study period:
2017-06-08
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
QSAR Toolbox 4.0 / EPISuite v4.11

2. MODEL (incl. version number)
Database version: 4.0//3.4 / KOWWIN v1.68

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
CAS 696-99-1
FB(F)F.NCc1ccccc1
N(Cc1ccccc1)B(F)(F)F
N(Cc1ccccc1) + B(F)(F)F

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
[Explain how the model fulfils the OECD principles for (Q)SAR model validation. Consider attaching the QMRF or providing a link]
- Defined endpoint: The octanol-water partition coefficient is a physical property used extensively to describe a chemical's lipophilic or hydrophobic properties.  It is the ratio of a chemical's concentration in the octanol-phase to its concentration in the aqueous phase of a two-phase system at equilibrium.  Since measured values range from less than 10-4 to greater than 10+8 (at least 12 orders of magnitude), the logarithm (log P) is commonly used to characterize its value.
The experimental Log Kow values in the training set and validation set were measured using one or more methods equivalent or similar to the following guidelines:
- Shake Flask method (OECD TG 107)
- HPLC method (OECD TG 117)
- Slow Stirring method (OECD TG 123)
Plus relevant EU (1992 as amended) and US EPA OPPTS (1982 as amended) and ASTM (1993) methods may be also used where appropriate.
A full list of experimental Log Kow reference citations is provided in the KOWWIN help menu with additional reference citations.
- Unambiguous algorithm: The KOWWIN program and estimation methodology were developed at Syracuse Research Corporation.  A journal article by Meylan and Howard (1995) describes the program methodology.
- Defined domain of applicability: Currently there is no universally accepted definition of model domain.  However, users may wish to consider the possibility that log P estimates are less accurate for compounds outside the MW range of the training set compounds, and/or that have more instances of a given fragment than the maximum for all 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 fragment coefficient was developed.  These points should be taken into consideration when interpreting model results.
Training Set Molecular Weights: Minimum MW:  18.02, Maximum MW:  719.92, Average MW:  199.98
Validation Molecular Weights: Minimum MW:  27.03, Maximum MW:  991.15, Average MW:  258.98
- Appropriate measures of goodness-of-fit and robustness and predictivity / Mechanistic interpretation: 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.   KOWWIN’s methodology is known as an Atom/Fragment Contribution (AFC) method.  Coefficients for individual fragments and groups were derived by multiple regression of 2447 reliably measured log P values.  KOWWIN’s "reductionist" fragment constant methodology (i.e. derivation via multiple regression) differs from the "constructionist" fragment constant methodology of Hansch and Leo (1979) that is available in the CLOGP Program (Daylight, 1995).  See the Meylan and Howard (1995) journal article for a more complete description of KOWWIN’s methodology.
To estimate log P, KOWWIN initially separates a molecule into distinct atom/fragments.  In general, 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"; these include carbonyl (C=O), thiocarbonyl (C=S), nitro (-NO2), nitrate (ONO2), cyano (-C/N), and isothiocyanate (-N=C=S).  Connections to each core "atom" are either general or specific; specific connections take precedence over general connections.  For example, aromatic carbon, aromatic oxygen and aromatic sulfur atoms have nothing but general connections; i.e., the fragment is the same no matter what is connected to the atom.  In contrast, there are 5 aromatic nitrogen fragments: (a) in a five-member ring, (b) in a six-member ring, (c) if the nitrogen is an oxide-type {i.e. pyridine oxide}, (d) if the nitrogen has a fused ring location {i.e. indolizine}, and (e) if the nitrogen has a +5 valence {i.e. N-methyl pyridinium iodide}; since the oxide-type is most specific, it takes precedence over the other four.  The aliphatic carbon atom is another example; it 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.
It became apparent, 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.  The term "correction factor" is appropriate because their values are derived from the differences between the log P estimates from atoms alone and the measured log P values.  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.

5. APPLICABILITY DOMAIN
[Explain how the substance falls within the applicability domain of the model]
- Descriptor domain: The molecular weight of the test substance is within the MW range of the training set compounds.
- Structural and mechanistic domains / Similarity with analogues in the training set: The test substance has number of instances of fragments that are under the maximum of all training set compounds. The test substance does not possess functional groups or other structural features that are not represented in the training set, and for which no fragment was developed.

6. ADEQUACY OF THE RESULT
[Explain how the prediction fits the purpose of classification and labelling and/or risk assessment]
The partition coefficient of the substance Benzylamine trifluoroboron was determined by the OECD QSAR Toolbox using the KOWWIN v1.68 model (EPIWIN software) by US-EPA. The program uses the chemical structure of a compound to predict the logarithmic octanol water partition coefficient (logPow). The structure is denoted in its SMILES notation. As first step the software determines the logPow contributions from individual molecular fragments. Afterwards these fragments are summed up to gain the logPow for the whole molecule.
This approach is justified as it is foreseen under REACH. REACH Annex VII column 2 foresees a QSAR estimation if testing cannot be performed, which is the case here and which is explained in the associated data waiver: "If the test cannot be performed (e.g. the substance decomposes, has a high surface activity, reacts violently during the performance of the test or does not dissolve in water or in octanol, or it is not possible to obtain a sufficiently pure substance), a calculated value for log P as well as details of the calculation method shall be provided."

Data source

Reference
Reference Type:
other: QSAR estimation report
Title:
EPI Suite Version 4.10, KOWWIN v1.68 (September 2010)
Author:
US EPA
Year:
2010
Bibliographic source:
EPI Suite Version 4.10, KOWWIN v1.68 (September 2010), copyright 2000 by U.S. Environmental Protection Agency

Materials and methods

Test guideline
Qualifier:
according to
Guideline:
other: REACH guidance on QSARs Chapter R.6
Version / remarks:
May 2008
Deviations:
not applicable
Principles of method if other than guideline:
KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds.  KOWWIN requires only a chemical structure to estimate a log P. 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.   KOWWIN’s methodology is known as an Atom/Fragment Contribution (AFC) method.  Coefficients for individual fragments and groups were derived by multiple regression of 2447 reliably measured log P values.
Meylan, W.M. and P.H. Howard. 1995. Atom/fragment contribution method for estimating octanol-water partition coefficients. J. Pharm. Sci. 84: 83-92
GLP compliance:
no
Type of method:
calculation method (fragments)
Partition coefficient type:
octanol-water

Test material

Reference
Name:
Unnamed
Type:
Constituent
Test material form:
other: not applicable
Remarks:
in silico study

Results and discussion

Partition coefficientopen allclose all
Key result
Type:
log Pow
Partition coefficient:
1.07
Remarks on result:
other: KOWWIN Experimental Database Structure Match for c1(CN)ccccc1 (Benzylamine)
Key result
Type:
log Pow
Partition coefficient:
0.22
Remarks on result:
other: QSAR predicted value for B(F)(F)F
Type:
log Pow
Partition coefficient:
0.98
Remarks on result:
other: QSAR predicted value for N(Cc1ccccc1)B(F)(F)F
Type:
log Pow
Partition coefficient:
0.645
Remarks on result:
other: QSAR predicted value for FB(F)F.NCc1ccccc1, average of fragments
Details on results:
There are 4 individual logPow values available by prediction:
1.07, KOWWIN Experimental Database Structure Match for c1(CN)ccccc1 (Benzylamine)
0.22, QSAR predicted value for B(F)(F)F
0.98, QSAR predicted value for N(Cc1ccccc1)B(F)(F)F
0.645, QSAR predicted value for FB(F)F.NCc1ccccc1, average of fragments
The substance decomposes immediately when getting in contact with water, and the formation of both BF3 and Benzylamine can be expected. Hence, it is considered most resonable to use both values of 1.07 and 0.22 respectively for further risk assessment.

Applicant's summary and conclusion

Conclusions:
The present entry describes a scientifically accepted calculation method for the partition coefficient using the US-EPA software KOWWIN v1.68. No GLP criteria are applicable for the usage of this tool and the QSAR estimation is easily repeatable. The result is adequate for the regulatory purpose. The substance falls into the applicability domain of the model. The substance decomposes immediately when getting in contact with water, and the formation of both BF3 and Benzylamine can be expected. Hence, it is considered most resonable to use both values of 1.07 and 0.22 respectively for further risk assessment.
Executive summary:

The partition coefficient of the substance Boron, (benzenemethanamine)trifluoro-, (T-4)- was determined by the computer program OECD Toolbox and hence KOWWIN v1.68 (EPIWIN software) by US-EPA (2010). The program uses the chemical structure of a compound to predict the logarithmic octanol water partition coefficient (logPow). The structure is denoted in its SMILES notation. As first step the software determines the logPow contributions from individual molecular fragments. Afterwards these fragments are summed up to gain the logPow for the whole molecule. The substance decomposes immediately when getting in contact with water, and the formation of both BF3 and Benzylamine can be expected. In this case a logPow of 1.07 and 0.22 was determined for BF3 and Benzylamine respectively as result. Adequacy of the QSAR:

- QSAR model is scientifically valid.

- The substance falls within the applicability domain of the QSAR model.

- The prediction is fit for regulatory purpose.