Propylene didecanoate

Partition coefficient

Administrative data

Endpoint:

partition coefficient

Type of information:

(Q)SAR

Adequacy of study:

key study

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 EpiSuite version 4.1

2. MODEL (incl. version number) KOWWIN Version 1.68

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES: CCCCCCCCCC(=O)OCC(C)OC(=O)CCCCCCCCC
Although the substance is a multiconstituent substance, the two enantiomers of the material are represented by the same SMILES notation. As the models are based on the fragments (organic functional groups) and the molecular weight, which is the same for both enantiomers.


4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL

 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 
 
Log P estimates made from atom/fragment values alone can be improved by inclusion of  substructures larger or more complex than "atoms". Correction factors were added to the AFC method.  The term "correction factor" is 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: factors involving aromatic ring substituent positions and,  miscellaneous factors.  Tthe correction factors are values for various steric interactions, hydrogen-bondings, and effects from polar functional substructures.  Individual correction factors were selected through correlating the differences (between log P estimates from atom/fragments alone and measured log P values) with common substructures.
 
Two separate regression analyses were performed.  The first regression related log P to atom/fragments of compounds that do not require correction factors (i.e., compounds estimated adequately by fragments alone).  The general regression equation has the following form:
 
 log P  = Σ(fini ) +  b     (Equation 1)
 
where Σ (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 b  is the linear equation constant.  This initial regression used 1120 compounds of the 2447 compounds in the total training dataset.
 
The correction factors were then derived from a multiple linear regression that correlated differences between the experimental (expl) log P and the log P estimated by Equation 1 above with the correction factor descriptors.  This regression did not utilize an additional equation constant.  The equation for the second regression is:
 
 lop P (expl)  -  log P (eq 1)  = Σ(cjnj )       (Equation 1)
 
where S(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).
 
 Results of the two successive multiple regressions (first for atom/fragments and second for correction factors) yield the following general equation for estimating log P of any organic compound:
 
 log P  = Σ(fini ) + Σ(cjnj ) + 0.229     (Equation 3)
 
(num = 2447,   r² = 0.982,  std dev = 0.217,  mean error = 0.159)
Appendix D lists KOWWIN atom/fragment and correction factor descriptors with corresponding coefficient values. Appendix D also includes the number of compounds in the training and validation datasets containing each descriptor and the maximum number of instances that each descriptor occurs in any single compound.
 

5. APPLICABILITY DOMAIN
The model has no domain, however the substance falls within the fragments included in the training set.

6. ADEQUACY OF THE RESULT
The substance is known to be poorly soluble in water and soluble in organic solvents. The prediction confirms that the water solubility of the test material is less that 1 mg/L. Further evaluation is not required for risk assessment purposes. The test material is non-hazardous.

Data source

Reference

Reference Type:

other company data

Title:

Unnamed

Year:

2018

Report date:

2018

Materials and methods

Test guideline

Qualifier:

according to guideline

Guideline:

other: ECHA Guidance on information requirements and chemical safety assessment Chapter R.6: QSARs and grouping of chemicals (May 2008)

Principles of method if other than guideline:

The partition coefficient was determined using the constant fragment methodology via the KOWWIN Version 1.68 model (EPIWEB Version 4.1) produced by the U.S. Environmental Protection Agency (EPA) included in the OECD QSAR Toolbox Version 4.1.

GLP compliance:

no

Remarks:

Not applicable

Type of method:

calculation method (fragments)

Partition coefficient type:

octanol-water

Test material

Test material information

Constituent 1

Reference substance name:

Propylene didecanoate

EC Number:

258-814-9

EC Name:

Propylene didecanoate

Cas Number:

53824-77-4

Molecular formula:

C23H44O4

IUPAC Name:

1-(decanoyloxy)propan-2-yl decanoate

Test material form:

liquid

Specific details on test material used for the study:

SMILES: CCCCCCCCCC(=O)OCC(C)OC(=O)CCCCCCCCC
Although the substance is a multiconstituent substance, the two enantiomers of the material are represented by the same SMILES notation. As the models are based on the fragments (organic functional groups) and the molecular weight, which is the same for both enantiomers.

Results and discussion

Partition coefficient

Type:

log Pow

Partition coefficient:

8.68

Remarks on result:

other: Temperature and pH not available in calculation. Assumed to be environmentally relevant conditions.

Any other information on results incl. tables

Table 1: Results – partition coefficient estimation

Type	Count	Log Kow Fragment Description	Coefficient	Value
Fragment	3	-CH3 [aliphatic carbon]	0.5473	1.6419
Fragment	17	-CH2- [aliphatic carbon]	0.4911	8.3487
Fragment	1	-CH [aliphatic carbon]	0.3614	0.3614
Fragment	2	-C(=O)O [ester, aliphatic attach]	-0.9505	-1.9010
Constant		Equation constant		0.2290
Log Kow				8.6800

Applicant's summary and conclusion

Conclusions:

The partition coefficient of the substance was predicted to be log Kow 8.68.