Sodium 1,4-bis(1,3-dimethylbutyl) sulphonatosuccinate

Adsorption / desorption

Link to relevant study record(s)

Reference

Endpoint:

adsorption / desorption: screening

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

Remarks:

EPISuite and its modules (including KOCWIN) have been utilized by the scientific community for prediction of phys/chem properties and environmental fate and effect properties since the 1990’s. The program underwent a comprehensive review by a panel of the US EPA’s independent Science Advisory Board (SAB) in 2007. The SAB summarized that the EPA used sound science to develop and refine EPISuite. The SAB also stated that the property estimation routines (PERs) satisfy the Organization for Economic Cooperation and Development (OECD) principles established for quantitative structure-activity relationship ((Q)SAR) validation. The EPISuite modules (including KOCWIN) have been incorporated into the OECD Toolbox. Inclusion in the OECD toolbox requires specific documentation, validation and acceptability criteria and subjects EPISuite to international use, review, providing a means for receiving additional and on-going input for improvements. In summary, the EPISuite modules (including KOCWIN) have had their scientific validity established repeatedly.

Justification for type of information:

1. SOFTWARE
EPISuite 4.11

2. MODEL (incl. version number)
KOCWIN (v2.00)

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
CAS 2373-38-8
CC(C)CC(C)OC(=O)C(S(=O)(=O)O([Na]))CC(=O)OC(C)CC(C)C

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
>>> Defined endpoint:
Yes
KOCWIN estimates Koc with two separate estimation methodologies: (1) estimation using first-order Molecular Connectivity Index (MCI) and (2) estimation using log Kow (octanol-water partition coefficient).
The initial KOCWIN (version 1) model estimated Koc solely with a QSAR utilizing Molecular Connectivity Index (MCI). This QSAR estimation methodology is described completely in a journal article (Meylan et al, 1992) and in a report prepared for the US EPA (SRC, 1991). KOCWIN (version 2) utilizes the same methodology, but the QSAR has been re-regressed using a larger database of experimental Koc values that includes many new chemicals and structure types. Two separate regressions were performed. The first regression related log Koc of non-polar compounds to the first-order MCI.
A traditional method of estimating soil adsorption Koc involves correlations developed with log octanol-water partition coefficient (log Kow) (Doucette, 2000). Since an expanded experimental Koc database was available from the new MCI regression, it was decided to develop a log Kow estimation methodology that was potentially more accurate than existing log Kow QSARs for diverse structure datasets. Effectively, the new log Kow methodology simply replaces the MCI descriptor with log Kow and derives similar equations. The derivation uses the same training and validation data sets. The training set is divided into the same non-polar (no correction factors) and correction factor sets. The same correction factors are also used.

>>> Unambiguous algorithm:
yes

>>> Defined domain of applicability:
yes
According to the KOCWIN documentation, there is currently no universally accepted definition of model domain. However, the documentation does provide information for reliability of the calculations. Estimates will possibly be less accurate for compounds that 1) have a MW outside the range of the training set compounds and 2) have a functional group(s) or other structural features not represented in the training set, and for which no fragment coefficient was developed; and that a compound has none of the fragments in the model’s fragment library.
(substance is within the training set)

>>> Appropriate measures of goodness-of-fit and robustness and predictivity:
yes
KOCWIN calculated the Koc values based on the following equations:
Estimation Using MCI: log Koc = 0.5213 MCI + 0.60
Estimation Using Log Kow: log Koc = 0.8679 Log Kow - 0.0004
The KOCWIN model had the following statistics:
MCI Methodology (Training Set): number = 69 correlation coef (r2) = 0.967
MCI Methodology (Validation Set): number = 158 correlation coef (r2) = 0.850
log Kow Methodology (Training Set): number = 68 correlation coef (r2) = 0.877
log Kow Methodology (Validation Set): number = 150 correlation coef (r2) = 0.778
These correlation coefficients indicate the KOCWIN model calculates results that are equivalent to those generated experimentally and are, hence, adequate for the purpose of classification and labelling and/or risk assessment.
Overall, the MCI methodology is somewhat considered more accurate than the Log Kow methodology, although both methods yield good results. If the Training datasets are combined in to one dataset of 516 compounds (69 having no corrections plus 447 with corrections), the MCI methodology has an r2, standard deviation and average deviation of 0.916, 0.330 and 0.263, respectively, versus 0.86, 0.429 and 0.321 for the Log Kow methodology.

>>> Mechanistic interpretation:
no

5. APPLICABILITY DOMAIN

As described above, according to the KOCWIN documentation, there is currently no universally accepted definition of model domain. In general, the intended application domain for all models embedded in EPISuite is organic chemicals. Specific compound classes, besides organic chemicals, require additional correction factors. Indicators for the general applicability of the KOCWIN model are the molecular weight of the target substance and the identification of functional group(s) or other structural features and their representation in the training set. The training set molecular weights are within the range of 32.04 – 665.02 with an average molecular weight of 224.4 (Validation set molecular weights: 73.14 – 504.12 and average of 277.8). The molecular weight of the substance is 388, which falls within the range of both, the training set and the validation set.
In additional a similar substance of the same category (CAS 577-11-7) is part of the training and validation set.


6. ADEQUACY OF THE RESULT

The KOCWIN predicted adsorption/desorption potential is considered valid and adequate for the purpose of risk assessment.

Documentation of the KOCWIN model is provided in the following references:
Doucette, W.J. 2000. Soil and sediment sorption coefficients. In: Handbook of Property Estimation Methods, Environmental and Health Sciences. R.S. Boethling & D. Mackay (Eds.), Boca Raton, FL: Lewis Publishers (ISBN 1 -56670 -456 -1).
Meylan, W., P.H. Howard and R.S. Boethling. 1992. Molecular topology/fragment contribution method for predicting soil sorption coefficients. Environ. Sci. Technol. 26: 1560 -1567.
McFarland, M. et al. 2007. “Science Advisory Board (SAB) Review of the Estimation Programs Interface Suite (EPI SuiteTM)”. SRC. 1991. Group Contribution Method for Predicting Soil Sorption Coefficients. William Meylan & Philip H. Howard, Syracuse Research Corporation (June 3, 1991). EPA Contract No. 68-D8-0117 (Work Assignment 2-19); SRC F0118-219

Principles of method if other than guideline:

Koc was estimated using the KOCWIN™ v2.00 module of EPI Suite v.4.11. KOCWIN™: Formerly called PCKOCWIN™.

Computational methods:

Koc was estimated using the KOCWIN™ v2.00 module of EPI Suite v.4.11. KOCWIN™: Formerly called PCKOCWIN™. This program estimates the organic carbon-normalized sorption coefficient for soil and sediment; i.e. Koc. Koc is estimated using two different models: the Sabljic molecular connectivity method with improved correction factors; and the traditional method based on log Kow (modeled or experimentally determined). All calculations were made by using the SMILES notation of the Na salts. Na was removed by KOCWIN in order to estimation via the MCI method, and hence, the Koc values are for the dissociated molecules (the acids) representing the worst case with respect to binding properties (see comparison MCI and Log Kow related values).

Type:

Koc

Value:

44.47

Type:

log Koc

Value:

1.65

Conclusions:

Log Koc estimation is 1.648 based on MCI method using the KOCWIN™ v2.00 module of EPI Suite™ v.4.11.

Executive summary:

Koc was estimated using the KOCWIN™ v2.00 module of EPI Suite™ v.4.11. KOCWIN™: Formerly called PCKOCWIN™. This program estimates the organic carbon-normalized sorption coefficient for soil and sediment; i.e. Koc. Koc is estimated using two different models: the Sabljic molecular connectivity method with improved correction factors; and the traditional method based on log Kow. Koc estimated from MCI was 44.47 L/kg (Log Koc 1.648) and is used for this risk assessment, due to its independency from modeled and experimentally determined Kow values.

Description of key information

Koc was estimated using the KOCWIN™ v2.00 module of EPI Suite™ v.4.11. KOCWIN™. The resulting value is 44.47  L/kg, which corresponds to a Log Koc of 1.65. 

Key value for chemical safety assessment

Koc at 20 °C:

44.47

Additional information

According to the FAO mobility classification, the substance is mobile, i.e., it does not adsorb to soils or sediments should these environmental compartments be exposed to it.

[LogKoc: 1.648]