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Partition coefficient

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Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
weight of evidence
Study period:
2018-03-19
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 v4.11
2. MODEL (incl. version number)
KOWWIN v1.66
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES
Smiles code for relevant constituents:
Dimer1: 
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NN 
Dimer2: 
O=C(NNC1CC(N(C2=CC=C(CC3=CC=C(N4C(C=CC4=O)=O)C=C3)C=C2)C1=O)=O)C5=CC=CC(N)=C5 
Trimer1: 
O=C(NN)C1=CC=CC(NC2C(N(C(C2)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(NNC(C6=CC=CC(N)=C6)=
O)CC5=O)=O)=O)=C1 
Trimer2: 
O=C1N(C(C(C1)NNC(C2=CC=CC(N)=C2)=O)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(NNC(C6=CC=CC(
N)=C6)=O)CC5=O)=O 
Trimer3: 
O=C(NN)C1=CC=CC(NC2C(N(C(C2)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(CC5=O)NC6=CC(C(NN)=
O)=CC=C6)=O)=O)=C1 
Trimer4: 
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NNC6C
(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(C=C9)=O)C9=O)=O 
Tetramer1: 
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NNC6C
(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(CC9NC%10=CC(C(NN)=O)=CC=C%10)=O)C9=O)=O 
Tetramer2: 
Nc1cccc(c1)C(=O)NNC1CC(=O)N(C1=O)c1ccc(Cc2ccc(cc2)N2C(=O)CC(NNC(=O)c3cccc(NC4CC(=O)N(C4
=O)c4ccc(Cc5ccc(cc5)N5C(=O)C=CC5=O)cc4)c3)C2=O)cc1 Tetramer3: 
O=C1N(C2=CC=C(CC3=CC=C(N4C(C(CC4=O)NC5=CC(C(NNC6C(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C
=C8)N9C(C=CC9=O)=O)=O)=O)=CC=C5)=O)C=C3)C=C2)C(CC1NC%10=CC(C(NN)=O)=CC=C%10)=O 
Tetramer4: 
O=C(C=CC1=O)N1C(C=C2)=CC=C2CC(C=C3)=CC=C3N4C(CC(NNC(C5=CC=CC(NC(CC(N6C7=CC=C(CC8=C
C=C(N(C9=O)C(CC9NNC(C%10=CC=CC(N)=C%10)=O)=O)C=C8)C=C7)=O)C6=O)=C5)=O)C4=O)=O 

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: Partion coefficient octanol/water (log Kow)
- Unambiguous algorithm: 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 available 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.
Log P estimates made from atom/fragment values alone could or need to be improved by inclusion of substructures larger or more complex than "atoms"; hence, correction factors were added to the AFC method. They are either factors involving aromatic ring substituent positions, or miscellaneous factors. Correction factors are values for various steric interactions, hydrogen-bondings, and effects from polar functional substructures. Individual correction factors were selected through a tedious process of correlating the differences (between log P estimates from atom/fragments alone and measured log P values) with common substructures.


- Defined domain of applicability: Currently there is no universally accepted definition of model domain. However, it should be considered that log P estimates may be less accurate for compounds outside the molecular weight range of the training set compounds, and/or that have more instances of a given fragment than the maximum for all training set compounds. Although the training set of the model contains a large number of diverse molecules and can be considered abundant, it is also possible that a compound may be characterised by structural features (e.g. functional groups) not represented in the training set, with no respective fragment/correction coefficient developed. These points should be taken into consideration when interpreting model results.

- Appropriate measures of goodness-of-fit and robustness and predictivity: Please refer to 'attached justification' for detailed information
- Mechanistic interpretation: Please refer to 'attached justification' for detailed information

5. APPLICABILITY DOMAIN
- Descriptor domain: Molecular weight, type of „fragment“
- Similarity with analogues in the training set: APPENDIX D of the HELP section in KOWWIN v1.66 contains the fragments used in the training set. The substance consists of fragments which are part of the training set. Moreover, as depicted above also the logKow´s of chemicals exceeding the molecular weight of the training set and/or exceeding the complexicity of the training set fragments are predicted with sufficient accuracy.

6. ADEQUACY OF THE RESULT
Please refer to 'attached justification' for detailed information
Qualifier:
no guideline followed
Principles of method if other than guideline:
- Software tool(s) used including version: EPISUITE v4.11, KOWWIN v1.68
- Model description: see field 'Attached justification'
- Justification of QSAR prediction: see field 'Attached justification'
GLP compliance:
no
Type of method:
other: QSAR estimation
Partition coefficient type:
octanol-water
Key result
Type:
log Pow
Partition coefficient:
0.572
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Dimer1
Key result
Type:
log Pow
Partition coefficient:
0.091
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Dimer2
Key result
Type:
log Pow
Partition coefficient:
-1.137
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer1
Key result
Type:
log Pow
Partition coefficient:
-1.618
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer2
Key result
Type:
log Pow
Partition coefficient:
-0.655
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer3
Key result
Type:
log Pow
Partition coefficient:
1.205
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer4
Key result
Type:
log Pow
Partition coefficient:
-0.023
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer1
Key result
Type:
log Pow
Partition coefficient:
-0.504
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer2
Key result
Type:
log Pow
Partition coefficient:
-0.023
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer3
Key result
Type:
log Pow
Partition coefficient:
-0.504
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer4
Conclusions:
In this study report the partition coefficient of Compimide 183 was estimated for the main occurring oligomers using EPISuite/KOWWIN v1.68. Based on the results the logKow is considered to be in the range of -1.6181 and 1.2047.
Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
weight of evidence
Study period:
2018-03-20
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
ACDLabs/ACD/Percepta 14.0.0 (Build 2726)
2. MODEL (incl. version number)
ACD/LogP GALAS module
3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES
Dimer1:
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NN
Dimer2:
O=C(NNC1CC(N(C2=CC=C(CC3=CC=C(N4C(C=CC4=O)=O)C=C3)C=C2)C1=O)=O)C5=CC=CC(N)=C5
Trimer1:
O=C(NN)C1=CC=CC(NC2C(N(C(C2)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(NNC(C6=CC=CC(N)=C6)=
O)CC5=O)=O)=O)=C1
Trimer2:
O=C1N(C(C(C1)NNC(C2=CC=CC(N)=C2)=O)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(NNC(C6=CC=CC(
N)=C6)=O)CC5=O)=O
Trimer3:
O=C(NN)C1=CC=CC(NC2C(N(C(C2)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(CC5=O)NC6=CC(C(NN)=
O)=CC=C6)=O)=O)=C1
Trimer4:
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NNC6C
(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(C=C9)=O)C9=O)=O
Tetramer1:
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NNC6C
(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(CC9NC%10=CC(C(NN)=O)=CC=C%10)=O)C9=O)=O
Tetramer2:
O=C(NNC1C(N(C2=CC=C(CC3=CC=C(N(C4=O)C(CC4NNC(C5=CC=CC(N)=C5)=O)=O)C=C3)C=C2)C(C1)=O)
=O)C6=CC=CC(NC7C(N(C(C7)=O)C8=CC=C(C=C8)CC9=CC=C(C=C9)N%10C(C=CC%10=O)=O)=O)=C6
Tetramer3:
O=C1N(C2=CC=C(CC3=CC=C(N4C(C(CC4=O)NC5=CC(C(NNC6C(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C
=C8)N9C(C=CC9=O)=O)=O)=O)=CC=C5)=O)C=C3)C=C2)C(CC1NC%10=CC(C(NN)=O)=CC=C%10)=O
Tetramer4:
O=C(C=CC1=O)N1C(C=C2)=CC=C2CC(C=C3)=CC=C3N4C(CC(NNC(C5=CC=CC(NC(CC(N6C7=CC=C(CC8=C
C=C(N(C9=O)C(CC9NNC(C%10=CC=CC(N)=C%10)=O)=O)C=C8)C=C7)=O)C6=O)=C5)=O)C4=O)=O
Pentamer1:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C=C4)=O)C4=O)C(NC5=CC(C(NNC(C6)C(N(C6=O)C(C=C7)=
CC=C7CC(C=C8)=CC=C8N9C(C(NC%10=CC(C(NNC(C%11)C(N(C%11=O)C(C=C%12)=CC=C%12CC(C=C%1
3)=CC=C%13N%14C(C=CC%14=O)=O)=O)=O)=CC=C%10)CC9=O)=O)=O)=O)=CC=C5)CC1=O
Pentamer2:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C=C4)=O)C4=O)C(NC5=CC(C(NNC(C6)C(N(C6=O)C(C=C7)=
CC=C7CC(C=C8)=CC=C8N9C(C(NNC(C%10=CC=CC(NC(C%11)C(N(C%11=O)C(C=C%12)=CC=C%12CC(C=
C%13)=CC=C%13N%14C(C=CC%14=O)=O)=O)=C%10)=O)CC9=O)=O)=O)=O)=CC=C5)CC1=O
Pentamer3:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C=C4)=O)C4=O)C(NNC(C5=CC=CC(NC(C6)C(N(C6=O)C(C=
C7)=CC=C7CC(C=C8)=CC=C8N9C(C(NC%10=CC(C(NNC(C%11)C(N(C%11=O)C(C=C%12)=CC=C%12CC(C=
C%13)=CC=C%13N%14C(C=CC%14=O)=O)=O)=O)=CC=C%10)CC9=O)=O)=O)=C5)=O)CC1=O
Pentamer4:
O=C(C1=CC=CC(NC(CC2=O)C(N2C3=CC=C(C=C3)CC4=CC=C(C=C4)N(C(C(NNC(C5=CC=CC(NC(CC6=O)C(
N6C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(C(NNC(C9=CC=CC(N)=C9)=O)C%10)=O)C%10=O)=O)=C5)=O)C
%11)=O)C%11=O)=O)=C1)NN
Pentamer5:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C(NNC(C4=CC=CC(N)=C4)=O)C5)=O)C5=O)C(NC6=CC(C(N
NC(C7)C(N(C7=O)C(C=C8)=CC=C8CC(C=C9)=CC=C9N%10C(C(NNC(C%11=CC=CC(N)=C%11)=O)CC%10=
O)=O)=O)=O)=CC=C6)CC1=O
Pentamer6:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C(NNC(C4=CC=CC(N)=C4)=O)C5)=O)C5=O)C(NNC(C6=CC=
CC(NC(C7)C(N(C7=O)C(C=C8)=CC=C8CC(C=C9)=CC=C9N%10C(C(NC%11=CC(C(NN)=O)=CC=C%11)CC%
10=O)=O)=O)=C6)=O)CC1=O
Pentamer7:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C(NC4=CC(C(NN)=O)=CC=C4)C5)=O)C5=O)C(NC6=CC(C(N
NC(C7)C(N(C7=O)C(C=C8)=CC=C8CC(C=C9)=CC=C9N%10C(C(NC%11=CC(C(NN)=O)=CC=C%11)CC%10=
O)=O)=O)=O)=CC=C6)CC1=O

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint:
Partion coefficient octanol/water (log P)

- Unambiguous algorithm:
ACD/LogP GALAS module provides the estimate of the octanol-water partitioning coefficient for neutral species derived on the basis of GALAS (Global, Adjusted Locally According to Similarity) modeling methodology
Each GALAS model consists of two parts:
• Global (baseline) statistical model that reflects general trends in the variation of the property of interest.
Similarity-based routine that performs local correction of baseline predictions taking into account the differences between baseline and experimental LogP values for the most similar training set compounds.

- Defined domain of applicability:
Currently there is no universally accepted definition of model domain. However, the algorithm for logP predictions is dependent on the training and validation dataset. Thus, one may wish to consider the possibility that property estimates are less accurate for compounds outside the molecular weight range of the dataset compounds and for substances with rare structural fragments. A compound may have a functional group(s) or other structural features not represented in the dataset, and for which no additive function was developed. These points should be taken into consideration when interpreting model results.

- Appropriate measures of goodness-of-fit and robustness and predictivity:
Please refer to 'attached justification' for more detailed informations

5. APPLICABILITY DOMAIN
- Descriptor domain:
Structural fragments
molecular weight
- Similarity with analogues in the training set:
In the documentation of the estimation results the first five substances exhibiting the closest similarity with the test item are listed. Since the reliability index is used and at least a moderate reliability was shown the results are considered to be adequate.
6. ADEQUACY OF THE RESULT
Please refer to 'attached justification' for more detailed informations
Qualifier:
no guideline followed
Principles of method if other than guideline:
- Software tool(s) used including version:
ACDLabs/ACD/Percepta 14.0.0 (Build 2726)
- Model description: see field 'Justification for type of information'
- Justification of QSAR prediction: see field 'Justification for type of information'
GLP compliance:
no
Type of method:
other: QSAR estimation
Partition coefficient type:
octanol-water
Key result
Type:
log Pow
Partition coefficient:
0.31
Temp.:
25
Remarks on result:
other: pH was not reported
Remarks:
Dimer1
Key result
Type:
log Pow
Partition coefficient:
0.23
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Dimer2
Key result
Type:
log Pow
Partition coefficient:
-0.17
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer1
Key result
Type:
log Pow
Partition coefficient:
-0.27
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer2
Key result
Type:
log Pow
Partition coefficient:
-0.16
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer3
Key result
Type:
log Pow
Partition coefficient:
1.77
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Trimer4
Key result
Type:
log Pow
Partition coefficient:
1.15
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer1
Key result
Type:
log Pow
Partition coefficient:
1.11
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer2
Key result
Type:
log Pow
Partition coefficient:
1.15
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer3
Key result
Type:
log Pow
Partition coefficient:
1.11
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Tetramer4
Key result
Type:
log Pow
Partition coefficient:
2.22
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Pentamer1
Key result
Type:
log Pow
Partition coefficient:
2.22
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Pentamer2
Key result
Type:
log Pow
Partition coefficient:
2.22
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Pentamer3
Key result
Type:
log Pow
Partition coefficient:
0.72
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Pentamer4
Key result
Type:
log Pow
Partition coefficient:
0.6
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Pentamer5
Key result
Type:
log Pow
Partition coefficient:
0.72
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Pentamer6
Key result
Type:
log Pow
Partition coefficient:
0.82
Temp.:
25 °C
Remarks on result:
other: pH was not reported
Remarks:
Pentamer7
Conclusions:
In this study report the partition coefficient of Compimide 183 was estimated by calculating the logP from every occurring oligomer using ACD / Percepta 14.0.0 . The logP of Compimide is considered to be in the range of 2.22 to -0.27 at 25°C
Endpoint:
partition coefficient
Type of information:
(Q)SAR
Adequacy of study:
weight of evidence
Study period:
2018-03-20
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
ACDLabs/ACD/Percepta 14.0.0 (Build 2726)

2. MODEL (incl. version number)
ACD/LogD module

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
SMILES
Dimer1:
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NN
Dimer2:
O=C(NNC1CC(N(C2=CC=C(CC3=CC=C(N4C(C=CC4=O)=O)C=C3)C=C2)C1=O)=O)C5=CC=CC(N)=C5
Trimer1:
O=C(NN)C1=CC=CC(NC2C(N(C(C2)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(NNC(C6=CC=CC(N)=C6)=O)CC5=O)=O)=O)=C1
Trimer2:
O=C1N(C(C(C1)NNC(C2=CC=CC(N)=C2)=O)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(NNC(C6=CC=CC(N)=C6)=O)CC5=O)=O
Trimer3:
O=C(NN)C1=CC=CC(NC2C(N(C(C2)=O)C3=CC=C(C=C3)CC4=CC=C(C=C4)N5C(C(CC5=O)NC6=CC(C(NN)=O)=CC=C6)=O)=O)=C1
Trimer4:
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NNC6C(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(C=C9)=O)C9=O)=O
Tetramer1:
O=C(C1=CC=CC(NC2C(N(C3=CC=C(CC4=CC=C(N(C(C=C5)=O)C5=O)C=C4)C=C3)C(C2)=O)=O)=C1)NNC6C(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(CC9NC%10=CC(C(NN)=O)=CC=C%10)=O)C9=O)=O
Tetramer2:
O=C(NNC1C(N(C2=CC=C(CC3=CC=C(N(C4=O)C(CC4NNC(C5=CC=CC(N)=C5)=O)=O)C=C3)C=C2)C(C1)=O)=O)C6=CC=CC(NC7C(N(C(C7)=O)C8=CC=C(C=C8)CC9=CC=C(C=C9)N%10C(C=CC%10=O)=O)=O)=C6
Tetramer3:
O=C1N(C2=CC=C(CC3=CC=C(N4C(C(CC4=O)NC5=CC(C(NNC6C(N(C(C6)=O)C7=CC=C(C=C7)CC8=CC=C(C=C8)N9C(C=CC9=O)=O)=O)=O)=CC=C5)=O)C=C3)C=C2)C(CC1NC%10=CC(C(NN)=O)=CC=C%10)=O
Tetramer4:
O=C(C=CC1=O)N1C(C=C2)=CC=C2CC(C=C3)=CC=C3N4C(CC(NNC(C5=CC=CC(NC(CC(N6C7=CC=C(CC8=CC=C(N(C9=O)C(CC9NNC(C%10=CC=CC(N)=C%10)=O)=O)C=C8)C=C7)=O)C6=O)=C5)=O)C4=O)=O
Pentamer1:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C=C4)=O)C4=O)C(NC5=CC(C(NNC(C6)C(N(C6=O)C(C=C7)=CC=C7CC(C=C8)=CC=C8N9C(C(NC%10=CC(C(NNC(C%11)C(N(C%11=O)C(C=C%12)=CC=C%12CC(C=C%13)=CC=C%13N%14C(C=CC%14=O)=O)=O)=O)=CC=C%10)CC9=O)=O)=O)=O)=CC=C5)CC1=O
Pentamer2:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C=C4)=O)C4=O)C(NC5=CC(C(NNC(C6)C(N(C6=O)C(C=C7)=CC=C7CC(C=C8)=CC=C8N9C(C(NNC(C%10=CC=CC(NC(C%11)C(N(C%11=O)C(C=C%12)=CC=C%12CC(C=C%13)=CC=C%13N%14C(C=CC%14=O)=O)=O)=C%10)=O)CC9=O)=O)=O)=O)=CC=C5)CC1=O
Pentamer3:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C=C4)=O)C4=O)C(NNC(C5=CC=CC(NC(C6)C(N(C6=O)C(C=C7)=CC=C7CC(C=C8)=CC=C8N9C(C(NC%10=CC(C(NNC(C%11)C(N(C%11=O)C(C=C%12)=CC=C%12CC(C=C%13)=CC=C%13N%14C(C=CC%14=O)=O)=O)=O)=CC=C%10)CC9=O)=O)=O)=C5)=O)CC1=O
Pentamer4:
O=C(C1=CC=CC(NC(CC2=O)C(N2C3=CC=C(C=C3)CC4=CC=C(C=C4)N(C(C(NNC(C5=CC=CC(NC(CC6=O)C(N6C7=CC=C(C=C7)CC8=CC=C(C=C8)N(C(C(NNC(C9=CC=CC(N)=C9)=O)C%10)=O)C%10=O)=O)=C5)=O)C%11)=O)C%11=O)=O)=C1)NN
Pentamer5:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C(NNC(C4=CC=CC(N)=C4)=O)C5)=O)C5=O)C(NC6=CC(C(NNC(C7)C(N(C7=O)C(C=C8)=CC=C8CC(C=C9)=CC=C9N%10C(C(NNC(C%11=CC=CC(N)=C%11)=O)CC%10=O)=O)=O)=O)=CC=C6)CC1=O
Pentamer6:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C(NNC(C4=CC=CC(N)=C4)=O)C5)=O)C5=O)C(NNC(C6=CC=CC(NC(C7)C(N(C7=O)C(C=C8)=CC=C8CC(C=C9)=CC=C9N%10C(C(NC%11=CC(C(NN)=O)=CC=C%11)CC%10=O)=O)=O)=C6)=O)CC1=O
Pentamer7:
O=C(N1C2=CC=C(C=C2)CC3=CC=C(C=C3)N(C(C(NC4=CC(C(NN)=O)=CC=C4)C5)=O)C5=O)C(NC6=CC(C(NNC(C7)C(N(C7=O)C(C=C8)=CC=C8CC(C=C9)=CC=C9N%10C(C(NC%11=CC(C(NN)=O)=CC=C%11)CC%10=O)=O)=O)=O)=CC=C6)CC1=O

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
- Defined endpoint: apparent partition coefficient D (logD)
- Unambiguous algorithm:
Please refer to 'attached justification' for more detailed information
- Defined domain of applicability:
Please refer to 'attached justification' for more detailed information
- Appropriate measures of goodness-of-fit and robustness and predictivity:
Please refer to 'attached justification' for more detailed information
5. APPLICABILITY DOMAIN
- Descriptor domain:
Please refer to 'attached justification' for more detailed information

6. ADEQUACY OF THE RESULT
Please refer to 'attached justification' for more detailed information
Qualifier:
no guideline followed
Principles of method if other than guideline:
- Software tool(s) used including version:
ACDLabs/ACD/Percepta 14.0.0 (Build 2726)
ACD/LogD module
- Model description: see field 'Justification for type of information'
- Justification of QSAR prediction: see field 'Justification for type of information'
GLP compliance:
no
Type of method:
other: QSAR prediction
Partition coefficient type:
octanol-water
Key result
Type:
log Pow
Partition coefficient:
0.31
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Dimer1
Key result
Type:
log Pow
Partition coefficient:
0.23
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Dimer2
Key result
Type:
log Pow
Partition coefficient:
-0.17
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Trimer1
Key result
Type:
log Pow
Partition coefficient:
-0.27
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Trimer2
Key result
Type:
log Pow
Partition coefficient:
-0.16
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Trimer3
Key result
Type:
log Pow
Partition coefficient:
1.77
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Trimer4
Key result
Type:
log Pow
Partition coefficient:
1.15
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Tetramer1
Partition coefficient:
1.11
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Tetramer2
Key result
Type:
log Pow
Partition coefficient:
1.15
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Tetramer3
Type:
log Pow
Partition coefficient:
1.11
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Tetramer4
Key result
Type:
log Pow
Partition coefficient:
2.22
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Pentamer1
Key result
Type:
log Pow
Partition coefficient:
2.22
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Pentamer2
Key result
Type:
log Pow
Partition coefficient:
2.22
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Pentamer3
Key result
Type:
log Pow
Partition coefficient:
0.72
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Pentamer4
Key result
Type:
log Pow
Partition coefficient:
0.6
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Pentamer5
Key result
Type:
log Pow
Partition coefficient:
0.72
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Pentamer6
Key result
Type:
log Pow
Partition coefficient:
0.82
Temp.:
25 °C
pH:
7.4
Remarks on result:
other: Pentamer7

Dimer1:

LogD at:  pH = 1.7 (Stomach): -1.23, pH = 4.6 (Duodenum): 0.3, pH = 6.5 (Jejunum and Ileum): 0.31, pH = 7.4 (Blood): 0.31, pH = 8.0 (Colon): 0.31, pH = 4.0: 0.26, pH = 7.0: 0.31, pH = 9.0: 0.31

Dimer2:

LogD at: pH = 1.7 (Stomach): -1.4, pH = 4.6 (Duodenum): 0.2, pH = 6.5 (Jejunum and Ileum): 0.23, pH = 7.4 (Blood): 0.23, pH = 8.0 (Colon): 0.23, pH = 4.0: 0.14, pH = 7.0: 0.23, pH = 9.0: 0.23

Trimer1:

LogD at: pH = 1.7 (Stomach): -3.36, pH = 4.6 (Duodenum): -0.21, pH = 6.5 (Jejunum and Ileum): -0.17, pH = 7.4 (Blood): -0.17, pH = 8.0 (Colon): -0.17, pH = 4.0: -0.31, pH = 7.0: -0.17, pH = 9.0: -0.17

Trimer2:

LogD at: pH = 1.7 (Stomach): -3.58, pH = 4.6 (Duodenum): -0.32, pH = 6.5 (Jejunum and Ileum): -0.27, pH = 7.4 (Blood): -0.27, pH = 8.0 (Colon): -0.27, pH = 4.0: -0.46, pH = 7.0: -0.27, pH = 9.0: -0.27

Trimer3:

LogD at: pH = 1.7 (Stomach): -3.24, pH = 4.6 (Duodenum): -0.19, pH = 6.5 (Jejunum and Ileum): -0.16, pH = 7.4 (Blood): -0.16, pH = 8.0 (Colon): -0.16, pH = 4.0: -0.26, pH = 7.0: -0.16, pH = 9.0: -0.16

Trimer4:

LogD at: pH = 1.7 (Stomach): 1.58, pH = 4.6 (Duodenum): 1.77, pH = 6.5 (Jejunum and Ileum): 1.77, pH = 7.4 (Blood): 1.77, pH = 8.0 (Colon): 1.77, pH = 4.0: 1.77, pH = 7.0: 1.77, pH = 9.0: 1.77

Tetramer1:

LogD at: pH = 1.7 (Stomach): -0.83, pH = 4.6 (Duodenum): 1.14, pH = 6.5 (Jejunum and Ileum): 1.15, pH = 7.4 (Blood): 1.15, pH = 8.0 (Colon): 1.15, pH = 4.0: 1.1, pH = 7.0: 1.15, pH = 9.0: 1.15

Tetramer2:

LogD at: pH = 1.7 (Stomach): -0.96, pH = 4.6 (Duodenum): 1.08, pH = 6.5 (Jejunum and Ileum): 1.11, pH = 7.4 (Blood): 1.11, pH = 8.0 (Colon): 1.11, pH = 4.0: 1.01, pH = 7.0: 1.11, pH = 9.0: 1.11

Tetramer3:

LogD at: pH = 1.7 (Stomach): -0.71, pH = 4.6 (Duodenum): 1.14, pH = 6.5 (Jejunum and Ileum): 1.15, pH = 7.4 (Blood): 1.15, pH = 8.0 (Colon): 1.15, pH = 4.0: 1.1, pH = 7.0: 1.15, pH = 9.0: 1.15

Tetramer4:

LogD at: pH = 1.7 (Stomach): -0.92, pH = 4.6 (Duodenum): 1.08, pH = 6.5 (Jejunum and Ileum): 1.11, pH = 7.4 (Blood): 1.11, pH = 8.0 (Colon): 1.11, pH = 4.0: 1.01, pH = 7.0: 1.11, pH = 9.0: 1.11

Pentamer1:

LogD at: pH = 1.7 (Stomach): 1.84, pH = 4.6 (Duodenum): 2.22, pH = 6.5 (Jejunum and Ileum): 2.22, pH = 7.4 (Blood): 2.22, pH = 8.0 (Colon): 2.22, pH = 4.0: 2.22, pH = 7.0: 2.22, pH = 9.0: 2.22

Pentamer2:

LogD at: pH = 1.7 (Stomach): 1.84, pH = 4.6 (Duodenum): 2.22, pH = 6.5 (Jejunum and Ileum): 2.22, pH = 7.4 (Blood): 2.22, pH = 8.0 (Colon): 2.22, pH = 4.0: 2.22, pH = 7.0: 2.22, pH = 9.0: 2.22

Pentamer3:

LogD at: pH = 1.7 (Stomach): 1.84, pH = 4.6 (Duodenum): 2.22, pH = 6.5 (Jejunum and Ileum): 2.22, pH = 7.4 (Blood): 2.22, pH = 8.0 (Colon): 2.22, pH = 4.0: 2.22, pH = 7.0: 2.22, pH = 9.0: 2.22

Pentamer4:

LogD at: pH = 1.7 (Stomach): -2.84, pH = 4.6 (Duodenum): 0.68, pH = 6.5 (Jejunum and Ileum): 0.72, pH = 7.4 (Blood): 0.72, pH = 8.0 (Colon): 0.72, pH = 4.0: 0.57, pH = 7.0: 0.72, pH = 9.0: 0.72

Pentamer5:

LogD at: pH = 1.7 (Stomach): -2.92, pH = 4.6 (Duodenum): 0.55, pH = 6.5 (Jejunum and Ileum): 0.6, pH = 7.4 (Blood): 0.6, pH = 8.0 (Colon): 0.6, pH = 4.0: 0.41, pH = 7.0: 0.6, pH = 9.0: 0.6

Pentamer6:

LogD at: pH = 1.7 (Stomach): -2.84, pH = 4.6 (Duodenum): 0.68, pH = 6.5 (Jejunum and Ileum): 0.72, pH = 7.4 (Blood): 0.72, pH = 8.0 (Colon): 0.72, pH = 4.0: 0.57, pH = 7.0: 0.72, pH = 9.0: 0.72

Pentamer7:

LogD at: pH = 1.7 (Stomach): -2.37, pH = 4.6 (Duodenum): 0.79, pH = 6.5 (Jejunum and Ileum): 0.82, pH = 7.4 (Blood): 0.82, pH = 8.0 (Colon): 0.82, pH = 4.0: 0.72, pH = 7.0: 0.82, pH = 9.0: 0.82

Conclusions:
In this study report the partition coefficient of Compimide 183 was estimated by ACD/logD Suite from ACD/Percepta ACD /Labs 2015 Release (Build 2726. 27 Nov 2014). Since the test item is an UVCB substance containing of oligomers formed from MDAB and ABH of varying length (Dimers, Trimers, Tetramers and Pentamers) for each possible oligomer the logD was predicted. Depending on different pH (4 to 9) values the calculated logD values were in the range of -0.46 to 2.22 for the oligomers tested.

Description of key information

- QSAR estimation with EPISuite/KOWWIN v1.68, logKow was estimated for the possible dimers, trimers and tetramers, the partition coefficient of Compimide 183 is considered to be in the range of -1.6 to 1.2

- QSAR estimation with ACD/Percepta/GALAS methodology, log P was estimated for the possible dimers, trimers, tetramers and pentamers, the partition coefficient of Compimide is considered to be in the range of -0.27 to 2.22

- QSAR estimation with ACD/Percepta/ACD/logD Suite, the apparent logD was predicted for every possible oligomer that can be formed by MDAB and ABH for the pH range of 0 -14, the logD of Compimide 183 is considered to be in the range of -0.46 and 2.22.

Key value for chemical safety assessment

Additional information

The partition coefficient of Compimide 183 was estimated as a range using EPISuite/KOWWINv1.68. For each oligomer (dimer, trimer, tetramer) in the reaction product of MDAB and ABH the partition coefficient was calculated, thus the logKow of Compimide is considered to be in the range of -1.6 to 1.2. The estimation is supposed to be reliable due to the molecular weight of the respective oligomers which is in the range for predictions with sufficient reliability and because the structural fragments are present in the training and validation dataset of the QSAR-model. However, also pentamers of MDAB and ABH can be formed but the prediction of the partition coefficient would be outside the applicability domain due to a molecular weight of > 1000 g/mol, hence the partition coefficients for pentamers were not established.

In a second prediction using ACD/Percepta and the GALAS methodology the partition coeffcients of all occurring oligomers (including pentamers) were calculated. This methodology compares the occurrence of certain structural fragments with training set substances that are structurally very similar to the test substance. The predictions were of sufficient reliability even for the high molecular weight oligomers since this methodology uses the Reliability Index which takes into account the similarity of the tested compound to the training set molecules and the consistence of experimental LogP values and baseline model prediction for the most similar compounds from the training set. Thus, only predictions with sufficient reliability were taken into account. The partition coefficient of Compimide is considered to be in the range of -0.27 and 2.22. Since the methodology used allows also the prediction of the high molecular weight oligomers with sufficient reliability the prediction is considered to provide representative and reliable results.

Since the substance contains functional groups or structural elements that are considered to be ionogenic groups, the apparent partition coefficient for every possible oligomer formed by MDAB and ABH was calculated dependent on pH. The logD of Compimide 183 is considered to be in the range -0.46 and 2.22.

After calculation of the partition coefficient with three different methods the log Kow of the individual constituents of Compimide 183 is between -1.6 and 2.22. This range covers all predicted log Kow values and substantiate that Compimide 183 can be assumed to be a hydrophilic substance.