2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate)

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, but not (completely) falling into its applicability domain, with adequate and reliable documentation / justification

Justification for type of information:

1. SOFTWARE
EPISuite (v4.11)

2. MODEL (incl. version number)
KOCWIN v2.01

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES: CCCCCC(CCCCCCCC)C(=O)OCC(COC(=O)C(CCCCCCCC)CCCCCC)(COC(=O)C(CCCCCCCC)CCCCCC)COC(=O)C(CCCCCCCC)CCCCCC

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
A reliable QSAR model was used to calculate the adsorption/desorption potential of 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate). Koc values were calculated using the KOCWIN v2.01 module embedded within the EPISuite (v4.11) computer model.
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.
- Defined endpoint and unambiguous algorithm:
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.
- Defined domain of applicability:
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.
- Appropriate measures of goodness-of-fit and robustness and predictivity:
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 for non-polar compounds:
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.

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 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate) is 1075.79, which is outside the range of both, the training set and the validation set.
But the ester structures (2 Ester (-C-CO-O-C-) or (HCO-O-C)) of 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate) are identified and represented in the training set and hence addressed by fragment correction.

--------------------------- KOCWIN v2.01 Results ---------------------------
Koc Estimate from MCI:
---------------------
First Order Molecular Connectivity Index ........... : 37.113
Non-Corrected Log Koc (0.5213 MCI + 0.60) .......... : 19.9467
Fragment Correction(s):
2 Ester (-C-CO-O-C-) or (HCO-O-C) ...... : -2.5939
Corrected Log Koc .................................. : 17.3528
Estimated Koc: 1e+010 L/kg <===========

Koc Estimate from Log Kow:
-------------------------
Log Kow (User entered ) ......................... : 11.03
Non-Corrected Log Koc (0.55313 logKow + 0.9251) .... : 7.0261
Fragment Correction(s):
2 Ester (-C-CO-O-C-) or (HCO-O-C) ...... : -0.1312
Corrected Log Koc .................................. : 6.8949
Estimated Koc: 7.851e+006 L/kg <===========


Although 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate) cannot be considered inside the estimation domain based on its molecular weight, but the results clearly indicate that the substance is immobile in soil.

6. ADEQUACY OF THE RESULT
The Koc values were calculated as 1e+010 L/kg and 7.851e+006 L/kg based on Molecular Connectivity Index (MCI) and log Kow method, respectively. These results both indicate that 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate) is immobile in soil. Hence, the KOCWIN predicted adsorption/desorption potential is considered adequate for the purpose of risk assessment.

Documentation of the KOCWIN model is provided in the following references:
Bahnick, D.A. and W.J. Doucette. 1988.  Use of molecular connectivity indices to estimate soil sorption coefficients for organic chemicals. Chemosphere 17:1703-1715. 
Baker, J.R., J.R. Mihelcic, D.C. Luehrs and J.P. Hickey.  1997.  Evaluation of estimation methods for organic carbon normalization sorption coefficients. Water Environ. Res. 69:136-145.
Boethling, R. S. 1994. Environmental aspects of cationic surfactants. In J. Cross and E. J. Singer (ed.), Cationic Surfactants: Analytical and Biological Evaluation, vol. 53. Marcel Dekker, Inc. , New York, USA
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). 
Gawlik, B.M. et al. 1998.  Application of the European reference soil set (eurosoils) to an HPLC-screening method for the estimation of soil adsorption coefficients of organic compounds. Chemosphere 36:2903-2919.
Howard, P.H. and M. Neal.  1992.  Dictionary of Chemical Names and Synonyms.  Lewis Publishers, Chelsea, MI (ISBN 0-87371-396-6)
Howard, P.H., G.W. Sage, A. LaMacchia and A. Colb.  1982.  The development of an environmental fate data base. J. Chem. Inf. Comput. Sci. 22:38-44 ... Internet availability: http://www.srcinc.com/what-we-do/efdb.aspx
Howard, P.H. et al. 1986.  BIOLOG, BIODEG, and Fate/Expos: New files on microbial degradation and toxicity as well as environmental fate/exposure of chemicals. Environ. Toxicol. Chem. 5:977-988 ... Internet availability: http://www.srcinc.com/what-we-do/efdb.aspx
HSDB.  2008.  Hazardous Substances Data Bank.  US National Library of Medicine. Internet availability via TOXNET (Databases on toxicology, hazardous chemicals, environmental health, and toxic releases): http://toxnet.nlm.nih.gov/
Kaune, A. et al.  1998.  Soil adsorption coefficients of s-triazines estimated with a new gradient HPLC method. J. Agric. Food Chem. 46:335-43.
Lyman, W.J.  1990.  Adsorption coefficient for soils and sediments. Chapter 4 in: Handbook of Chemical Property Estimation Methods.  Lyman, W.J. et al. (Eds.). Washington, DC: American Chemical Society.
Nguyen, T.H., K.U. Goss and P.W. Ball. 2005.  Polyparameter linear free energy relationships for estimating the equilibrium partition of organic compounds between water and the natural organic matter in soils and sediments. Environ. Sci. Technol. 39: 913-624.
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.
Sabljic, A. 1984.  Predictions of the nature and strength of soil sorption of organic pollutants by molecular topology. J. Agric. Food Chem. 32:243-246.
Sabljic, A. 1987.  On the prediction of soil sorption coefficients of organic pollutants from molecular structure: application of molecular topology model. Environ. Sci. Technol. 21:358-66.
Sabljic, A., H. Gusten, H. Verhaar and J. Hermens.  2005.  QSAR modeling of soil sorption. Improvements and systematics of log Koc vs. log Kow correlations. Chemosphere 31:4489-4514. (see also Chemosphere 33: 2577).
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
Schuurmann, G., R. Ebert and R. Kuhne.  2006.  Prediction of the sorption of organic compounds into soil organic matter from molecular structure. Environ. Sci. Technol. 40:7005-7011 .... "Supporting Information" available via Internet download from http://pubs.acs.org/journals/esthag/ (then selecting the journal issue, etc.).
USDA Pesticide Prop DB.   The ARS Pesticide Properties Database.  Agricultural Research Service, U.S. Department of Agriculture ...  Internet availability in 2008: http://www.ars.usda.gov/Services/docs.htm?docid=14199
VonOepen, B. et al.  1991.  Sorption of nonpolar and polar compounds to soils: processes, measurements and experience with applicability of the modified OECD - Guideline 106. Chemosphere 22:285-304.
Weininger, D. 1988.  SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules.   J. Chem. Inf. Comput. Sci. 28:31-36.

Guideline:

other: REACH Guidance on QSARs R.6

Principles of method if other than guideline:

Meylan, W., P.H. Howard and R.S. Boethling, "Molecular Topology/Fragment Contribution Method for Predicting Soil Sorption Coefficients", Environ. Sci. Technol. 26: 1560-7 (1992).

Specific details on test material used for the study:

SMILES: CCCCCC(CCCCCCCC)C(=O)OCC(COC(=O)C(CCCCCCCC)CCCCCC)(COC(=O)C(CCCCCCCC)CCCCCC)COC(=O)C(CCCCCCCC)CCCCCC

Key result

Type:

Koc

Value:

10 000 000 000 L/kg

Remarks on result:

other: estimate from MCI

Key result

Type:

Koc

Value:

7 851 000 L/kg

Remarks on result:

other: estimate from log Kow

KOCWIN v2.01 predicted that 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate) has a Koc > 1e+006 L/kg (1e+010  L/kg MCI method; 7.851e+006 L/kg logKow based method).

Executive summary:

.

Description of key information

KOCWIN v2.01 predicted that 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate) has a Koc > 1e+006 L/kg (1e+010  L/kg MCI method; 7.851e+006 L/kg logKow based method).

Key value for chemical safety assessment

Koc at 20 °C:

10 000 000 000

Additional information

The Koc values were calculated as 1e+010 L/kg and 7.851e+006 L/kg based on Molecular Connectivity Index (MCI) and log Kow method, respectively. Although 2,2-bis[[(2-hexyl-1-oxodecyl)oxy]methyl]-1,3-propanediyl bis(2-hexyldecanoate) cannot be considered inside the estimation domain based on its molecular weight, the results clearly indicate that the substance is immobile in soil. Hence, the KOCWIN predicted adsorption/desorption potential is considered adequate for the purpose of risk assessment.