Printing Date 2013-08-05 13:48:37 CEST 

Restriction of specific regulatory purposes 

EU: REACH 

Owner 2-Butenedioic acid (E)-, di-C8-18-alkyl esters, CAS 68610-90-2 / 

 

Legal entity 

owner 

 

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Endpoint study record: WoE, RA-A C8 FA component, 

 2011, KOWWIN v1.68, RL2 

Administrative Data 

Data source 

Reference 

Data access 

Materials and methods 

Partition coefficient type 

Principles of method if other than guideline 

GLP compliance 

Test materials 

Identity of test material same as for substance defined in section 1 (if not read-across) 

Details on test material 

Any other information on materials and methods incl. tables 

UUID IUC5-6e41f4b5-deb7-4c45-be1d-c0dc0466ee3e 

Dossier UUID 0 

Author 

Date 2011-09-09 14:31:43 CEST 

Remarks 

EU: REACH 

Purpose flag weight of evidence; robust study summary 

Study result type (Q)SAR 

Reliability 2 (reliable with restrictions) 

Rationale for reliability incl. deficiencies Accepted calculation method 

Reference 

type 

Author Year Title Bibliographic 

source 

Testing 

laboratory 

Report 

no. 

Owner 

company 

Company 

study no. 

Report 

date 

study 

report 

2011 Episuite 

4.10 

calculation 

with 2-

Butenedioic 

acid (E)-, 

di-C8-18-

alkyl esters 

 

20110609-

Hop-2 

Fatty acid 

ester 

umbrella 

consortium 

(FEUC), 

PFAE 

linear 

subgroup 

2011-

06-09 

data submitter is data owner 

octanol-water 

Calculation based on KOWWIN v1.68, Estimation Programs Interface SuiteTM for Microsoft® Windows v4.10. US EPA, 

United States Environmental Protection Agency, Washington, DC, USA. 

no 

no 

- Name of test material (as cited in study report): 2-Butenedioic acid (E)-, di-C8-alkyl ester

- Molecular formula (if other than submission substance): C20 H36 O4 

- Molecular weight (if other than submission substance): 340.51 g/mol 

- Smiles notation: CCCCCCCCOC(=O)C=CC(=O)OCCCCCCCC 

- Analytical purity: not applicable 

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Input data: 

SMILES: CCCCCCCCOC(=O)C=CC(=O)OCCCCCCCC 

KOWWIN(the Log Octanol-Water Partition Coefficient Program) estimates the 

octanol-water partition coefficient (log P) of organic compounds. KOWWIN 

requires only a chemical structure to estimate a log P.In the method applied, 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.

Validity of the model according to the OECD principles: 

1. Defined endpoint:

 log Kow (log P) – logarithmic octanol/water partition coefficient.The partition 

coefficient Kow (P) is the ratio of concentrations of a chemical in n-octanol and 

in water at equilibrium at a specified temperature (typically 25 °C, although 

partition coefficient is not usually very temperature dependent and training data 

for KOWWIN are collected at different temperatures). 

2. Unambiguous algorithm:

KOWWIN uses a "fragment constant" methodology to predict log P. 

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.

To estimate log P, KOWWIN initially separates a molecule into distinct 

atom/fragments. In general, each non-hydrogen atom 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;specific connections take 

precedence over general connections.

Log P estimates made from atom/fragment values alone could or need to be 

improved by inclusion of substructures larger or more complex than "atoms"; 

hence, correction factors were added to the AFC method. They are either 

factors involving aromatic ring substituent positions, or miscellaneous factors. 

Correction factors are values for various steric interactions, hydrogenbondings, 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.

The general regression equation has the following form:

log P = ∑(f(i)*n(i)) + ∑(c(j)*n(j)) + b

where f(i) is the coefficient of atom/fragment i, n(i) – the number of times the 

fragment i occurs in the molecule, c(j) is the coefficient for the correction factor 

j, and n(j) the number of times the factor j occurs (or is applied) in the molecule. 

b is the linear equation constant; b = 0.229.

Values of f and c coefficients are available.

3. Applicability domain:

Currently there is no universally accepted definition of model domain. 

 However, it should be considered that log P estimates may be less accurate 

for compounds outside the molecular weight range of the training set 

compounds, and/or that have more instances of a given fragment than the 

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Results and discussions 

maximum for all training set compounds. Although the training set of the model 

contains a large number of diverse molecules and can be considered 

abundant, it is also possible that a compound may be characterised by 

structural features (e.g. functional groups) not represented in the training set, 

with no respective fragment/correction coefficient developed. These points 

should be taken into consideration when interpreting model results.

Training set molecular weights:

Minimum MW: 18.02

Maximum MW: 719.82 (in the validation set: 991.15)

Average in the training set: 199.98.

4.Appropriate measures of goodness of fit, robustness and predictivity: 

Training set statistics: 

N = 2447 compounds 

correlation coefficient R2= 0.982

standard deviation = 0.217 

absolute deviation = 0.159 

Training set estimation error: 

within≤0.10 – 45.0% 

within≤0.20 – 72.5% 

within≤0.40 – 92.4% 

within≤0.50 – 96.4% 

within≤0.60 – 98.2% 

External validation set statistics:

N = 10946 compounds 

correlation coefficient R2= 0.943

standard deviation = 0.479 

absolute deviation = 0.356 

Validation set estimation error: 

within≤0.20 – 39.6% 

within≤0.40 – 66.0% 

within≤0.50 – 75.6% 

within≤0.60 – 82.5% 

within≤0.80 – 91.6% 

within≤1.00 – 95.6% 

5. Mechanistic interpretation, if possible:

KOWWIN’s "reductionist" fragment constant methodology (i.e. derivation via 

multiple regression) differs from the "constructionist" fragment constant 

methodology of Hansch and Leo (Hansch, C. and Leo, A.J., Substituent 

Constants for Correlation Analysis in Chemistry and Biology, Wiley, New York, 

1979). More complete description of KOWWIN methodology is described in: 

Meylan, W.M., and Howard, P.H., Atom/Fragment Contribution Method for 

Estimating Octanol-Water Partition Coefficients, J. Pharm. Sci 84: 83-92, 1995.

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Partition coefficient 

Any other information on results incl. tables 

Overall remarks, attachments 

Remarks on results including tables and figures 

Type Partition coefficient Temp. pH Remarks 

log Pow 8.09 

QSAR result; pH and temperature are not reported. For detailed description of the 

model and its applicability, see "Any other information on materials and methods incl. 

tables".

The substance fits in the applicability domain of the model. The prediction is 

valid and can be 

used for classification and risk assessment. 

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