Disodium oxalate

Partition coefficient

Link to relevant study record(s)

Reference

Reference 1

Endpoint:

partition coefficient

Type of information:

(Q)SAR

Adequacy of study:

weight of evidence

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 and MODEL
OPERA-Model for Octanol-water partition
OPERA v1.5

2. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES : O=C(C(=O)O[Na])O[Na]
NAME : disodium oxalate
CAS Number : 62-76-0

3. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
See QMRF_LogKow_disodium oxalate-OPERA_Q17-16-0016_document

4. APPLICABILITY DOMAIN
See QMRF_LogKow_disodium oxalate-OPERA_Q17-16-0016_document

Guideline:

other: REACH guidance on QSARs R.6

Principles of method if other than guideline:

- Software tool(s) used including version: OPERA-model for octano-water paritition
- Model(s) used: v1.5 (2016)
- Model description: see field 'Justification for type of information"
- Justification of QSAR prediction: see field 'Attached justification'

GLP compliance:

no

Specific details on test material used for the study:

SMILES : O=C(C(=O)O[Na])O[Na]

Type:

log Pow

Partition coefficient:

ca. -0.855

Remarks on result:

other: QSAR predicted value

OPERA predicted that disodium oxalate has a logKow = -0.855

Conclusions:

OPERA predicted that disodium oxalate has a logKow = -0.855

Executive summary:

OPERA predicted that disodium oxalate has a logKow = -0.855

Reference 2

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:

This endpoint study record is part of a Weight of Evidence approach. QSAR may be used in estimating the LogKow of the organic part, the oxalate and allows to fulfil the information requirements as further explained in the provided endpoint summary.
QSAR INFORMATIONS : Quantitative Structure Activity Relationships (QSAR) are theoretical models that can be used to predict in a qualitative or quantitative manner the physico-chemical, toxicological, ecotoxicological and environmental fate properties of compounds from a knowledge of their chemical structure.
1. SOFTWARE : EPI Suite
2. MODEL (incl. version number) : EPIWEB 4.11 Kowwin Version 1.68 (september 2010)
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL :
SMILES of the substance: O=C(C(=O)O[Na])O[Na]
Name : sodium oxalate
CAS : 62-76-0

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
According to the guidance R.7a - version 5 - December 2016, "When no experimental data of high quality are available, or if experimental methods are known to be unreliable, valid (Q)SARs for log Kow may be used e.g. in a weight-of-evidence approach."
No formal QMRF assessment of the model is currently available, however, the user's guide describes all the information.
- Defined endpoint: Partition coefficient
- Methodology : KOWWIN uses a "fragment constant" methodology to predict log P. In a "fragment constant" method, 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. 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.
KOWWIN’s "reductionist" fragment constant methodology (i.e. derivation via multiple regression) differs from the "constructionist" fragment constant methodology of Hansch and Leo (1979) that is a vailable in the CLOGP Program (Daylight, 1995). See the Meylan and Howard (1995) journal article for a more complete description of KOWWIN’s methodology.
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.
5. APPLICABILITY DOMAIN
No formal QMRF assessment of the model is currently available, however, the user's guide describes all the information.
- Descriptor domain: organic chemical QSAR may be used in estimating the LogKow of the organic part (but not applicable to the ion pair).
- Structural and mechanistic domains:
Training Set Molecular Weights: Minimum MW: 18.02 Maximum MW: 719.92 Average MW: 199.98
Appendix D of the KOWWIN Help gives the maximum number of fragments that occur in any individual compound of the training set.
- Similarity with analogues in the training set: The KOWWIN training and validation datasets can be downloaded from the Internet at http://esc.syrres.com/interkow/KowwinData.htm

Qualifier:

according to guideline

Guideline:

other: Episuite v1.68

Version / remarks:

KOWWIN’s methodology is known as an Atom/Fragment Contribution (AFC) method.
see Meylan, W.M. and P.H. Howard. 1995. Atom/fragment contribution method for estimating octanol-water partition coefficients. J. Pharm. Sci. 84: 83-92.

GLP compliance:

not specified

Type of method:

other: QSAR model

Partition coefficient type:

octanol-water

Specific details on test material used for the study:

The substance is a mono-constituent substance; the prediction is done on the constituent.

Type:

log Pow

Partition coefficient:

-7

Remarks on result:

other: QSAR (KOWWIN) with sodium oxalate. Na+ ion cannot be represented in the model. Temperature and pH value are not specified by the QSAR model.

Conclusions:

The partition coefficient (log Pow) of the test item (sodium oxalate) was estimated to be -7.00 with(Q)SAR model EPI Suite software tool.

Executive summary:

The partition coefficient was estimated using the (Q)SAR model EPI Suite v1.68.

The partition coefficient (log Pow) of the test item was estimated to be -7.00.

Description of key information

QSAR prediction with a good reliability predicted that disodium oxalate has a logKow :

• -7.00 with Kowwin
• -0.855 with OPERA

All these data indicates that diodium oxalate has a low partitient coefficient.

The OPERA value is retained as this QSAR confirmed to be in the applicability domain.

Key value for chemical safety assessment

Log Kow (Log Pow):

-0.855