Dimethyl sebacate

Adsorption / desorption

Link to relevant study record(s)

Reference

Endpoint:

adsorption / desorption

Remarks:

adsorption

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

2013

Reliability:

2 (reliable with restrictions)

Rationale for reliability incl. deficiencies:

other: see 'Remark'

Remarks:

The adsorption/desorption coefficient of the test substance was evaluated with KOCWIN model v2.00 from EPI Suite v4.1, which fulfilled all OECD principles. Test substance is within the domain of the model based on the molecular weight and fragments present in the KOCWIN database.

Justification for type of information:

QSAR prediction: migrated from IUCLID 5.6

Qualifier:

no guideline followed

Principles of method if other than guideline:

QSAR calculation
KOCWIN v2.00 (EPISuite) estimates the adsorption coefficient (Koc) of organic compounds to particulate organic matter, hence provides an indication of the extent to which a chemical partitions between solid and liquid phases in soil, or between water and sediment in aquatic ecosystems.
Koc = (µg adsorbed/g organic carbon) / (µg/mL solution)
The units of Koc are typically expressed as either L/kg or mL/g.
Traditional estimation methods rely upon the octanol/water partition coefficient or related parameters, but the first-order molecular connectivity index (MCI) has been used successfully to predict Koc values for hydrophobic organic compounds The original KOCWIN program (PCKOC) used MCI and a series of group contribution factors to predict Koc (Meylan et al., 1992). This group contribution method was s shown to outperform traditional estimation methods based on octanol/water partition coefficients and water solubility

GLP compliance:

no

Type of method:

other: QSAR

Media:

soil

Radiolabelling:

no

Test temperature:

Not applicable, QSAR estimation.

Details on study design: HPLC method:

Not applicable, QSAR estimation.

Analytical monitoring:

not required

Details on sampling:

Not applicable, QSAR estimation.

Details on matrix:

Not applicable, QSAR estimation.

Details on test conditions:

Not applicable, QSAR estimation.

Computational methods:

Methodology
PCKOCWIN (version 2) estimates Koc with two separate estimation methodologies:
(1) estimation using first-order Molecular Connectivity Index (MCI)
(2) estimation using log Kow (octanol-water partition coefficient)

Collection of Koc Data
The major source of experimental Koc data was Schuurmann et al. (2006) which includes a compilation of selected Koc values for 571 compounds.  Data from the original PCKOWIN regression (that included a total of 389 compounds) were also used.  A new data source was the USDA Pesticide Properties Database (data for more than 150 compounds were collected).  Koc values for a few additional compounds were collected from references in Environmental Fate Data Base system (Howard et al., 1982, 1986).

For compounds appearing in more than one of the various compilations, a single Koc value was selected.  In general, values from the Schuurmann et al. (2006) compilation were used.  An average value was used for a few compounds.

After some additional quality control to ensure various reported Koc values were not estimated (as opposed to experimental), selected Koc values for 674 compounds were used to train and validate the updated regression from these sources:
(1) Schuurmann et al. (2006) compilation:  453 compounds
(2)  Original PCKOCWIN regression:  85 compounds
(3) USDA Pesticide Properties Database :  85 compounds
(4)  Average from multiple sources:  21 compounds
(5)  Miscellaneous sources:  30 compounds  (Nguyen et al, 2005; Sabljic et al, 1995; Baker et al, 1997; VonOepen et al, 1991; Kaune, 1998; Gawlik et al, 1998; HSBD, 2008)

The 674 compounds were eventually divided into a training set of 516 compounds and a validation set of 158 compounds.  The training set was divided further into a dataset of 69 non-polar organics and 447 polar organics (same as previously described in Meylan et al, 1992).  For the current model development, the non-polar dataset is designated as compounds having "No Correction Factors" while the polar compounds are designated as compounds "Having Correction factors".

Estimation Using Molecular Connectivity Index:
PCKOCWIN (version 1) 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).  PCKOCWIN (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.

QSAR Derivation
The same methodology as described in (Meylan et al, 1992) was used to develop the QSAR equations utilizing Molecular Connectivity Index (MCI).  Two separate regressions were performed.  The first regression related log Koc of non-polar compounds to the first-order MCI.  As noted above, non-polar compounds are now designated as "compounds having no correction factors" which simply means the MCI descriptor alone can adequately predict the Koc.  Measured log Koc values were fit to a simple linear equation of the form:

 log Koc  = a MCI  + b

where a and b are the coefficients fit by least-square analysis.  The 69 compounds used for this regression are listed in Appendix E.

The second regression included the 447 compounds having correction factors.  Correction factors are specific chemical classes or structural fragments.  The regression coefficients were derived via multiple linear regression of the correction descriptors to the residual error of the prediction from the non-polar equation.

Results Using Molecular Connectivity Index
The equation derived by the non-polar (no correction factor) regression is:

log Koc  =  0.5213 MCI  +  0.60
(n = 69, r2 = 0.967, std dev = 0.247, avg dev = 0.199)

Adding in the correction factor regression yields the final MCI equation:
log Koc  =  0.5213 MCI  +  0.60 + SPfN  
where SPfN is the summation of the products of all applicable correction factor coefficients multiplied by the number of times (N) that factor is counted for the structure.

Estimation Using Log Kow
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.

Separate equations correlating log Koc with log Kow were derived for nonpolar and polar compounds because it was statistically more accurate to do so than to use the approach taken with the MCI-based method.  The equation derived by the non-polar (no correction factor) regression is:

log Koc  =  0.8679 Log Kow  -  0.0004
(n = 68, r2 = 0.877, std dev = 0.478, avg dev = 0.371)

One non-polar compound was removed from the regression (hexabromobiphenyl) because it was the only compound without a recommended experimental log Kow and the accuracy of its estimated log Kow (9.10) is suspect.  This equation is used for any compound having no correction factors.

For the multiple-linear regression using correction factors, log Kow was included as an individual descriptor.  For compounds having correction factors, the equation is:

log Koc  =  0.55313 Log Kow  +  0.9251 + SPfN  
where SPfN is the summation of the products of all applicable correction factor coefficients multiplied by the number of times (N) that factor is counted for the structure.

Type:

Koc

Value:

460.8

Remarks on result:

other: Koc estimate based on log Pow (user entered log P=3.38)

Type:

log Koc

Remarks:

2.66

Remarks on result:

other: Koc estimate based on log Pow (user entered log P=3.38)

Details on results (HPLC method):

Not applicable, QSAR estimation.

Adsorption and desorption constants:

Not applicable, QSAR estimation.

Recovery of test material:

Not applicable, QSAR estimation.

Concentration of test substance at end of adsorption equilibration period:

Not applicable, QSAR estimation.

Concentration of test substance at end of desorption equilibration period:

Not applicable, QSAR estimation.

Details on results (Batch equilibrium method):

Not applicable, QSAR estimation.

Statistics:

Not applicable, QSAR estimation.

Validity criteria fulfilled:

not applicable

Conclusions:

The QSAR estimated log Koc for the test item is 2.66 (Log Kow method).

Executive summary:

The log Koc for the substance was estimated by QSAR (KOCWIN v2.00).The log Koc estimated based on log Kow is low (2.66), indicating no significant soil adsorption of the substance.

Description of key information

The log Koc for the substance was estimated by QSAR (KOCWIN v2.00): log Koc is low (2.66). 

Key value for chemical safety assessment

Koc at 20 °C:

460.8

Additional information

The performance of a test for adsorption/desorption screening is scientifically unjustified as the substance is readily biodegradable. However, the log Koc was estimated by QSAR (KOCWIN v2.00).The log Koc estimated based on log Kow is low (2.66), indicating no significant soil adsorption of the substance.

[LogKoc: 2.66]