Registration Dossier

Diss Factsheets

Administrative data

Endpoint:
bioaccumulation in aquatic species: fish
Type of information:
(Q)SAR
Adequacy of study:
other information
Study period:
2021
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 : CATALOGIC 5.13.1
2. MODEL (incl. version number) : BCF base-line model v.03.10
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
CNS(=O)(=O)C(F)(F)C(F)(F)C(F)(F)C(F)(F)F

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: The BCF base-line model consists of two major components: a model for predicting the maximum potential for bioaccumulation based solely on chemicals’ lipophilicity (based on multi-compartment diffusion), and a set of mitigating factors that account for the reduction of the bioaccumulation potential of chemicals based on chemical (e.g., molecular size, ionization, etc.) and organism-dependent factors (e.g., metabolism). In the BCF base-line model the tissue metabolism simulator is used to account for the effect of metabolism.
- Unambiguous algorithm:
- Defined domain of applicability: The applicability domain of the BCF base-line model contains four layers:
General properties requirements
Structural domain
Mechanistic domain (discriminates between modes of bioaccumulation - passive (partitioning in lipid phase) or active (based on protein binding). Only chemicals with expected passive diffusion driven bioaccumulation are considered to be in the mechanistic domain of the model)
Metabolic domain (describes how well the metabolism is simulated based on the available observed metabolism in the database of the model)

- Appropriate measures of goodness-of-fit and robustness and predictivity:
Residual Sum of Squares = 197
Coefficient of Correlation, R = 0.92
Root mean square error, 0.51
Distribution of residual error: ca. 88% of residuals of the fitted data are <0.75 log units

- Mechanistic interpretation: The BCF base-line model reflects the current understanding of the process by which lipophilic organic chemicals are bioaccumulated in fish through the respiratory organs only. Chemicals, bioaccumulating by other mechanisms (e.g., binding to proteins) are considered out of the mechanistic domain of the model. The BCFmax model is a theoretical model based on the assumption that the only driving force of bioconcentration is lipophilicity and the effect of any other factors are insignificant. Its mathematical formalism is derived considering multi-compartment diffusion. The bioconcentration predicted by BCFmax model could be limited by variety of mitigating factors that account for the reduction of the bioaccumulation potential of chemicals based on chemical and organism-dependent factors. The effect of mitigating factors mathematically is quantified by probabilities: to penetrate through the cell membrane, to be ionized, to be metabolised, etc. In the BCF baseline model the tissue metabolism simulator is used to account for the effect of metabolism. It consists of a sequence of spontaneous abiotic and enzyme controlled steps. Probabilities of these molecular transformations are assessed by fitting the training set data.

5. APPLICABILITY DOMAIN
- Descriptor domain: General properties requirements (log Kow, MW, WS) are in domain.
- Structural domain:
Correct fragments = 78%
Incorrect fragments = 0%
Unknown fragments = 22%. "Unknown" structural features are atom centered fragments which do not have a prediction. The "unknown" features relate to the n-methylsulfonamido fragment, whether centered on methyl carbon or nitrogen, as well as the sulfonamidomethylene/sulfonamidoethylene fragment. The model training set contains several aromatic sulfonamides including N-substituted sulfonamides. The unknown assignment regarding the n-methylsulfonamido fragment appears to be partially an artifact.
- Mechanistic domain: The model applies a decision rule that perfluoroalkyl substances with a perfluoroalkyl chain length of more than two carbons are out of mechanistic domain due to uptake mechanism being other than passive diffusion across biological membranes. This perfluoroalkyl chain length rule does not apply to materials which lack a terminal trifluoromethyl group. For example, the training set contains 2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11-eicosafluoro-1-undecanol (CAS# 307-70-0). This substance is considered to be in mechanistic domain, and the predicted log BCF agrees with the experimentally determined value within 0.20 log units. Performance with other fluorinated molecules in the training set is similar. Further, the model has good performance with pentafluoropropionic acid and nonafluorobutanesulfonic acid, for which measured BCF values are available, and with perfluoropentanoic acid, for which BCF values are too low to provide an measurement. The model therefore provides reasonable results despite ostensible exclusion from the model applicability domain. Active bioaccumulation not expected.
- Similarity with analogues in the training set: see Any other information on results including tables.

6. ADEQUACY OF THE RESULT
The modeled result predicts bioconcentration potential of the substance.

Data source

Reference
Reference Type:
other: QSAR model results
Title:
CATALOGIC 5.13.1 (MeFBSA)
Year:
2021
Bibliographic source:
BCF base-line model v.03.10
Report date:
2021

Materials and methods

Test guideline
Qualifier:
according to guideline
Guideline:
other: Guidance on information requirements and chemical safety assessment: Chapter R.6: QSARs and grouping of chemicals
Principles of method if other than guideline:
- Software tool(s) used including version: CATALOGIC 5.13.1
- Model(s) used: BCF base-line model v.03.10
- Model description: see field 'Attached justification'
- Justification of QSAR prediction: 'Attached justification'
GLP compliance:
no
Remarks:
QSAR model

Test material

Constituent 1
Chemical structure
Reference substance name:
1-BUTANESULFONAMIDE, 1,1,2,2,3,3,4,4,4-NONAFLUORO-N-METHYL-
EC Number:
614-396-3
Cas Number:
68298-12-4
Molecular formula:
C5H4F9NO2S
IUPAC Name:
1-BUTANESULFONAMIDE, 1,1,2,2,3,3,4,4,4-NONAFLUORO-N-METHYL-
Specific details on test material used for the study:
SMILES:
CNS(=O)(=O)C(F)(F)C(F)(F)C(F)(F)C(F)(F)F

Results and discussion

Bioaccumulation factor
Value:
370 dimensionless
Remarks on result:
other: QSAR model results, physical conditions such as pH and temperature are not relevant

Any other information on results incl. tables

Table 1, Predicted and observed BCF values

Substance

Predicted log BCF

Predicted BCF

Observed log BCF

Observed BCF

MeFBSA

2.57±0.107

370

Training set compounds

 

 

 

 

1,1,1,3,3,3-Hexafluoro-2-propanol

1.00

10

0.301

2.0

2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11-Eicosafluoro-1-undecanol

3.22

1700

3.41

2600

2,2,3,3,4,4,5,5-octafluoro-1-pentanol

1.88

76

1.46

29

External analogs

 

 

 

 

Perfluorobutanesulfonic acid

0.87

7.4

0.30-27.5¹

Perfluoropropanoic acid

0.57

3.7

 <4.8²

Perfluoropentanoic acid

0.86

7.2

Not detected³

1, Information from registration dossier for PFBS potassium salt (CAS# 29420-49-3)

2, Information from registration dossier for CAS# 756-13-8

3, Martin JW, SA Mabury, KR Solomon, DCG Muir. 2003. Environ. Toxicol. Chem. 22: 196-204. Only carboxylates with more than six perfluoroalkyl carbons were detected in blood, liver, and carcass of rainbow trout at all sampling times. Shorter PFAs are expected to have insignificant bioconcentration potential. For comparison, PFOA had a measured BCF in blood of 27.

Applicant's summary and conclusion

Validity criteria fulfilled:
not applicable
Conclusions:
Estimated BCF of MeFBSA is 370
Executive summary:

QSAR modeling in the BCF base-line model v.03.10 of CATALOGIC 5.13.1 was done to address bioconcentration potential of MeFBSA. The result has been reported to other regulatory jurisdictions. This model is a validated QSAR with extensive parameterization to take molecular size, metabolism, and other parameters into account. Model performance with other highly fluorinated materials is reasonable. The result is therefore considered reliable with restrictions.