Oils, neroli

Partition coefficient

Administrative data

Endpoint:

partition coefficient

Type of information:

(Q)SAR

Adequacy of study:

key study

Study period:

2018

Reliability:

1 (reliable without restriction)

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

Remarks:

Neroli Oil is a well-defined NCS (Natural Complex Substance), which is characterized to at least 90%. The partition coefficient of a NCS has a little meaning. According to the NCS protocol, a range of Low Kow can be given from the calculated or measured values of the constituents of the NCS.

Justification for type of information:

1. SOFTWARE
Episuite platform (version 4.11)

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

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
The CAS number database is used to input SMILES notations and chemical names onto the data entry by entering the Chemical Abstract Service (CAS) Registry number for each target substances (see annex I of the attached QPRF).

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
See attached QPRF

5. APPLICABILITY DOMAIN
See attached QPRF

6. ADEQUACY OF THE RESULT
See attached QPRF

Cross-reference

Reason / purpose for cross-reference:

reference to same study

Data source

Reference

Reference Type:

other: QSAR Model

Title:

KOWWIN v1.68

Author:

U.S. Environmental Protection Agency

Year:

2012

Bibliographic source:

US EPA. [2012]. Estimation Programs Interface Suite™ for Microsoft® Windows, v 4.11. United States Environmental Protection Agency, Washington, DC, USA.

Materials and methods

Test guideline

Qualifier:

according to guideline

Guideline:

other: REACH Guidance on QSAR R.6

Deviations:

not applicable

Principles of method if other than guideline:

Meylan, W.M and P.H. Howard. 1995. Atom/fragment contribution method for estimating octanol-water partition coefficients. J. Pharm. Sci. 84:83-92.

Type of method:

calculation method (fragments)

Partition coefficient type:

octanol-water

Test material

Test material information

Constituent 1

Reference substance name:

(R)-p-mentha-1,8-diene

EC Number:

227-813-5

EC Name:

(R)-p-mentha-1,8-diene

Cas Number:

5989-27-5

Molecular formula:

C10H16

IUPAC Name:

4-isopropenyl-1-methylcyclohexene

Constituent 2

Reference substance name:

Linalool

EC Number:

201-134-4

EC Name:

Linalool

Cas Number:

78-70-6

Molecular formula:

C10H18O

IUPAC Name:

3,7-dimethylocta-1,6-dien-3-ol

Constituent 3

Reference substance name:

Pin-2(10)-ene

EC Number:

204-872-5

EC Name:

Pin-2(10)-ene

Cas Number:

127-91-3

Molecular formula:

C10H16

IUPAC Name:

6,6-dimethyl-2-methylenebicyclo[3.1.1]heptane

Constituent 4

Reference substance name:

Linalyl acetate

EC Number:

204-116-4

EC Name:

Linalyl acetate

Cas Number:

115-95-7

Molecular formula:

C12H20O2

IUPAC Name:

1,5-dimethyl-1-vinylhex-4-en-1-yl acetate

Constituent 5

Reference substance name:

3,7-dimethylocta-1,3,6-triene

EC Number:

237-641-2

EC Name:

3,7-dimethylocta-1,3,6-triene

Cas Number:

13877-91-3

Molecular formula:

C10H16

IUPAC Name:

3,7-dimethylocta-1,3,6-triene

Constituent 6

Reference substance name:

p-menth-1-en-8-ol

EC Number:

202-680-6

EC Name:

p-menth-1-en-8-ol

Cas Number:

98-55-5

Molecular formula:

C10H18O

IUPAC Name:

p-menth-1-en-8-ol

Constituent 7

Reference substance name:

7-methyl-3-methyleneocta-1,6-diene

EC Number:

204-622-5

EC Name:

7-methyl-3-methyleneocta-1,6-diene

Cas Number:

123-35-3

Molecular formula:

C10H16

IUPAC Name:

7-methyl-3-methyleneocta-1,6-diene

Constituent 8

Reference substance name:

Geranyl acetate

EC Number:

203-341-5

EC Name:

Geranyl acetate

Cas Number:

105-87-3

Molecular formula:

C12H20O2

IUPAC Name:

3,7-dimethylocta-2,6-dien-1-yl acetate

Constituent 9

Reference substance name:

Geraniol

EC Number:

203-377-1

EC Name:

Geraniol

Cas Number:

106-24-1

Molecular formula:

C10H18O

IUPAC Name:

3,7-dimethylocta-2,6-dien-1-ol

Constituent 10

Reference substance name:

3,7,11-trimethyldodeca-1,6,10-trien-3-ol,mixed isomers

EC Number:

230-597-5

EC Name:

3,7,11-trimethyldodeca-1,6,10-trien-3-ol,mixed isomers

Cas Number:

7212-44-4

Molecular formula:

C15H26O

IUPAC Name:

3,7,11-trimethyldodeca-1,6,10-trien-3-ol

Constituent 11

Reference substance name:

Nerol

EC Number:

203-378-7

EC Name:

Nerol

Cas Number:

106-25-2

Molecular formula:

C10H18O

IUPAC Name:

3,7-dimethylocta-2,6-dien-1-ol

Constituent 12

Reference substance name:

Farnesol

EC Number:

225-004-1

EC Name:

Farnesol

Cas Number:

4602-84-0

Molecular formula:

C15H26O

IUPAC Name:

3,7,11-trimethyldodeca-2,6,10-trien-1-ol

Constituent 13

Reference substance name:

Neryl acetate

EC Number:

205-459-2

EC Name:

Neryl acetate

Cas Number:

141-12-8

Molecular formula:

C12H20O2

IUPAC Name:

3,7-dimethylocta-2,6-dien-1-yl acetate

Constituent 14

Reference substance name:

Pin-2(3)-ene

EC Number:

201-291-9

EC Name:

Pin-2(3)-ene

Cas Number:

80-56-8

Molecular formula:

C10H16

IUPAC Name:

2,6,6-trimethylbicyclo[3.1.1]hept-2-ene

Constituent 15

Reference substance name:

Thuj-4(10)-ene

EC Number:

222-212-4

EC Name:

Thuj-4(10)-ene

Cas Number:

3387-41-5

Molecular formula:

C10H16

IUPAC Name:

1-isopropyl-4-methylenebicyclo[3.1.0]hexane

Constituent 16

Reference substance name:

Indole

EC Number:

204-420-7

EC Name:

Indole

Cas Number:

120-72-9

Molecular formula:

C8H7N

IUPAC Name:

1H-indole

Constituent 17

Reference substance name:

Methyl anthranilate

EC Number:

205-132-4

EC Name:

Methyl anthranilate

Cas Number:

134-20-3

Molecular formula:

C8H9NO2

IUPAC Name:

methyl 2-aminobenzoate

Test material form:

other: not applicable for in silico study

Results and discussion

Partition coefficient

Partition coefficient 1

Key result

Type:

log Pow

Partition coefficient:

>= 2.05 - <= 5.77

Remarks on result:

other: Log Kow range for Neroli oil consitutents

Partition coefficient 2

Type:

log Pow

Partition coefficient:

4.83

Remarks on result:

other: d-LIMONENE

Remarks:

QSAR predicted value

Partition coefficient 3

Key result

Type:

log Pow

Partition coefficient:

4.57

Remarks on result:

other: d-LIMONENE

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 4

Key result

Type:

log Pow

Partition coefficient:

2.97

Remarks on result:

other: LINALOOL

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 5

Type:

log Pow

Partition coefficient:

3.38

Remarks on result:

other: LINALOOL

Remarks:

QSAR predicted value

Partition coefficient 6

Key result

Type:

log Pow

Partition coefficient:

4.16

Remarks on result:

other: BETA-PINENE

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 7

Type:

log Pow

Partition coefficient:

4.35

Remarks on result:

other: BETA-PINENE

Remarks:

QSAR predicted valude

Partition coefficient 8

Key result

Type:

log Pow

Partition coefficient:

3.93

Remarks on result:

other: LINALYL ACETATE

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 9

Type:

log Pow

Partition coefficient:

4.37

Remarks on result:

other: LINALYL ACETATE

Remarks:

QSAR predicted value

Partition coefficient 10

Key result

Type:

log Pow

Remarks on result:

other: OCIMENE

Remarks:

QSAR predicted value

Partition coefficient 11

Key result

Type:

log Pow

Partition coefficient:

2.98

Remarks on result:

other: ALPHA-TERPINEOL

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 12

Type:

log Pow

Partition coefficient:

3.33

Remarks on result:

other: ALPHA-TERPINEOL

Remarks:

QSAR predicted value

Partition coefficient 13

Key result

Type:

log Pow

Partition coefficient:

4.17

Remarks on result:

other: MYRCENE

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 14

Type:

log Pow

Partition coefficient:

4.88

Remarks on result:

other: MYRCENE

Remarks:

QSAR predicted value

Partition coefficient 15

Key result

Type:

log Pow

Partition coefficient:

4.04

Remarks on result:

other: GERANYL ACETATE

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 16

Type:

log Pow

Partition coefficient:

4.48

Remarks on result:

other: GERANYL ACETATE

Remarks:

QSAR predicted value

Partition coefficient 17

Type:

log Pow

Partition coefficient:

3.56

Remarks on result:

other: GERANIOL

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 18

Type:

log Pow

Partition coefficient:

3.47

Remarks on result:

other: GERANIOL

Remarks:

QSAR predicted value

Partition coefficient 19

Key result

Type:

log Pow

Partition coefficient:

5.68

Remarks on result:

other: NEROLIDOL

Remarks:

QSAR predicted value

Partition coefficient 20

Key result

Type:

log Pow

Partition coefficient:

3.47

Remarks on result:

other: NEROL

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 21

Type:

log Pow

Remarks on result:

other: NEROL

Remarks:

QSAR predicted value

Partition coefficient 22

Key result

Type:

log Pow

Partition coefficient:

5.77

Remarks on result:

other: FARNESOL

Remarks:

QSAR predicted value

Partition coefficient 23

Key result

Type:

log Pow

Partition coefficient:

3.98

Remarks on result:

other: NERYL ACETATE

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 24

Type:

log Pow

Partition coefficient:

4.48

Remarks on result:

other: NERYL ACETATE

Remarks:

QSAR predicted value

Partition coefficient 25

Key result

Type:

log Pow

Partition coefficient:

4.83

Remarks on result:

other: ALPHA-PINENE

Remarks:

experimental Log Kow from the training or the validation dataset of KOWWIN

Partition coefficient 26

Type:

log Pow

Partition coefficient:

4.27

Remarks on result:

other: ALPHA-PINENE

Remarks:

QSAR predicted value

Partition coefficient 27

Key result

Type:

log Pow

Partition coefficient:

4.96

Remarks on result:

other: SABINENE

Remarks:

QSAR predicted value

Partition coefficient 28

Key result

Type:

log Pow

Partition coefficient:

2.05

Remarks on result:

other: INDOLE

Remarks:

QSAR predicted value

Partition coefficient 29

Key result

Type:

log Pow

Partition coefficient:

2.26

Remarks on result:

other: METHYL ANTHRANILATE

Remarks:

QSAR predicted value

Any other information on results incl. tables

No study was conducted on the NCS itself.

The KOWWIN model was used to predict the octanol/water partition coefficients of the constituents of the NCS.

Full details are provided in the QPRF attached.

All the constituents were within the applicability domain of the model and all the target substances were containing regular and common fragments included in this model; there are no limits to the mechanistic domain.

The Low Kow was predicted as follows:

Target Substance	MW	KOWWIN Estimated Log Kow	Experimental Log Kow from the training or the validation dataset
d-Limonene	136.24	4.83	4.57
Linalool	154.25	3.38	2.97
β-pinene	136.24	4.35	4.16
Linalyl acétate	196.29	4.37	3.93
Ocimene	136.24	4.80	-
α-terpineol	154.25	3.33	2.98
Myrcene	136.24	4.88	4.17
Geranyl acetate	196.29	4.48	4.04
Geraniol	154.25	3.47	3.56
Nerolidol (trans)	222.37	5.68	-
Nerol	154.25	3.47	3.47
Farnesol (trans trans)	222.37	5.77	-
Neryl acetate	196.29	4.48	3.98
α-pinene	136.24	4.27	4.83
Sabinene	136.24	4.96	-
Indole	117.15	2.05	-
Methyl anthranilate	151.17	2.26	-
The partition coefficient of the known constituents of the Substance were found to be in the range from 2.05 to 5.77.

Applicant's summary and conclusion

Conclusions:

The Log Kow of the constituents of Neroli Oil ranges between 2.05 and 5.77

Executive summary:

Neroli oil is a well-defined NCS containing multiple constituents.

As the partition coefficient for a NCS has little meaning, and according to the NCS protocol, the partition coefficients of the individual known consituents were predicted using the KOWWIN v1.67 QSAR by US-EPA.

The Log Kow of the constituents of Neroli Oil ranges between 2.05 and 5.77.