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Diss Factsheets

Administrative data

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:
1. SOFTWARE EpiSuite version 4.1

2. MODEL (incl. version number) KOWWIN Version 1.68

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES: Cc1ccc(cc1)S(=O)(ON(H)(H)(H))=O


4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL

 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 
 
Log P estimates made from atom/fragment values alone can be improved by inclusion of  substructures larger or more complex than "atoms". Correction factors were added to the AFC method.  The term "correction factor" is derived from the differences between the log P estimates from atoms alone and the measured log P values.  The correction factors have two main groupings: factors involving aromatic ring substituent positions and,  miscellaneous factors.  Tthe correction factors are values for various steric interactions, hydrogen-bondings, and effects from polar functional substructures.  Individual correction factors were selected through correlating the differences (between log P estimates from atom/fragments alone and measured log P values) with common substructures.
 
Two separate regression analyses were performed.  The first regression related log P to atom/fragments of compounds that do not require correction factors (i.e., compounds estimated adequately by fragments alone).  The general regression equation has the following form:
 
 log P  = Σ(fini ) +  b     (Equation 1)
 
where Σ (fini )  is the summation of fi (the coefficient for each atom/fragment) times ni (the number of times the atom/fragment occurs in the structure) and b  is the linear equation constant.  This initial regression used 1120 compounds of the 2447 compounds in the total training dataset.
 
The correction factors were then derived from a multiple linear regression that correlated differences between the experimental (expl) log P and the log P estimated by Equation 1 above with the correction factor descriptors.  This regression did not utilize an additional equation constant.  The equation for the second regression is:
 
 lop P (expl)  -  log P (eq 1)  = Σ(cjnj )       (Equation 1)
 
where S(cjnj )  is the summation of cj (the coefficient for each correction factor) times nj  (the number of times the correction factor occurs (or is applied) in the molecule).
 
 Results of the two successive multiple regressions (first for atom/fragments and second for correction factors) yield the following general equation for estimating log P of any organic compound:
 
 log P  = Σ(fini ) + Σ(cjnj ) + 0.229     (Equation 3)
 
(num = 2447,   r² = 0.982,  std dev = 0.217,  mean error = 0.159)
Appendix D lists KOWWIN atom/fragment and correction factor descriptors with corresponding coefficient values. Appendix D also includes the number of compounds in the training and validation datasets containing each descriptor and the maximum number of instances that each descriptor occurs in any single compound.
 

5. APPLICABILITY DOMAIN
The model has no domain, however the substance falls within the fragments included in the training set.

6. ADEQUACY OF THE RESULT
Further evaluation is not required for risk assessment purposes. The test material is non-hazardous.

Data source

Reference
Reference Type:
other company data
Title:
Unnamed
Year:
2019
Report date:
2019

Materials and methods

Test guideline
Qualifier:
according to guideline
Guideline:
other: ECHA Guidance on information requirements and chemical safety assessment Chapter R.6: QSARs and grouping of chemicals (May 2008)
Deviations:
not applicable
Principles of method if other than guideline:
The partition coefficient was determined using the constant fragment methodology via the KOWWIN Version 1.68 model (EPIWEB Version 4.1) produced by the U.S. Environmental Protection Agency (EPA) included in the OECD QSAR Toolbox Version 4.2.
GLP compliance:
no
Remarks:
not applicable
Type of method:
calculation method (fragments)
Partition coefficient type:
octanol-water

Test material

Constituent 1
Chemical structure
Reference substance name:
Ammonium toluene-4-sulphonate
EC Number:
223-927-4
EC Name:
Ammonium toluene-4-sulphonate
Cas Number:
4124-42-9
Molecular formula:
C7H8O3S.H3N
IUPAC Name:
ammonium 4-methylbenzenesulfonate
Specific details on test material used for the study:
SMILES:
Cc1ccc(cc1)S(=O)(ON(H)(H)(H))=O

Results and discussion

Partition coefficient
Type:
log Pow
Partition coefficient:
-0.67
Remarks on result:
other: Temperature and pH not available in calculation. Assumed to be environmentally relevant conditions.

Any other information on results incl. tables

Table 1: Estimation of Log Kow (Fragments)

Type

Number

Log Kow Fragment Description

Coefficient

Value

Fragment

1

-CH3 [aliphatic carbon]

0.5473

0.5473

Fragment

6

Aromatic carbon

0.2940

1.7640

Fragment

1

-SO2-O [sulfonate, aromatic attach]

-0.3650

-0.3650

Fragment

1

>N<[+5 valence; single bonds; H attach]

-4.6000

-4.6000

Fragment

1

{-O- or -S-} to nitrogen (+5 valence)

1.7500**

1.7500

Constant

 

Equation Constant

0.2290

 

** Estimated coefficient used.

Molecular weight: 188.22

Log Kow -0.6747

Applicant's summary and conclusion

Conclusions:
The partition coefficient of the substance was predicted to be log Kow -0.67.