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Adsorption / desorption

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Reference
Endpoint:
adsorption / desorption, other
Type of information:
calculation (if not (Q)SAR)
Adequacy of study:
key study
Reliability:
4 (not assignable)
Rationale for reliability incl. deficiencies:
secondary literature
Justification for type of information:
Data is from Chemistry Dashboard.
Reference:
Composition 0
Qualifier:
according to
Guideline:
other: Refer below principle
Principles of method if other than guideline:
Prediction done using OPERA (OPEn (quantitative) structure-activity Relationship Application) V1.02 model in which calculation based on PaDEL descriptors (calculate molecular descriptors and fingerprints of chemical)
GLP compliance:
no
Type of method:
other: PaDEL descriptors
Media:
soil
Test material information:
Composition 1
Specific details on test material used for the study:
- Name of test material : 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3-trimethyl-3H-indolium chloride
- Molecular formula : C24H30Cl2N2
- Molecular weight : 417.421 g/mol
- Smiles notation : C1(=[N+](c2ccccc2C1(C)C)C)\C=C/c1c(cc(N(CCCl)CC)cc1)C.[ClH-]
- InChl : 1S/C24H30ClN2.ClH/c1-6-27(16-15-25)20-13-11-19(18(2)17-20)12-14-23-24(3,4)21-9-7-8-10-22(21)26(23)5;/h7-14,17H,6,15-16H2,1-5H3;1H/q+1;/p-1
- Substance type: Organic
- Physical state: Solid
Radiolabelling:
no
Test temperature:
No data
Analytical monitoring:
no
Details on sampling:
No data available
Details on matrix:
No data available
Details on test conditions:
No data available
Computational methods:
No data available
Key result
Type:
Koc
Value:
8 100 L/kg
Remarks on result:
other: (Log Koc= 3.908) Result based on the OECD principle 1-5
Details on results (HPLC method):
No data available
Adsorption and desorption constants:
No data available
Recovery of test material:
No data available
Concentration of test substance at end of adsorption equilibration period:
No data available
Concentration of test substance at end of desorption equilibration period:
No data available
Transformation products:
not specified
Details on results (Batch equilibrium method):
No data available
Statistics:
No data available

Prediction based on following 5 OECD principles:

OECD Principle 1 (Defining the endpoint):

The original data collected from the PHYSPROP database (788 chemicals) have undergone a series of processes to curate the chemical structures and remove duplicates, obvious outliers and erroneous entries. This procedure also included a consistency check to ensure only good quality data is used for the development of the QSAR model (750 chemicals).

 

Then, QSAR-ready structures were generated by standardizing all chemical structures and removing duplicates, inorganic and metallo-organic chemicals (735 chemicals). The descriptions of KNIME workflows that were developed for the purpose of the cleaning and standardization of the data are available in the papers [ref 1 and ref 4 Section 2.7].

 

The curated outlier-free experimental data (729 chemicals) was divided into training and validation sets before the machine learning and modeling steps.

 

OECD Principle 2(Defining the algorithm):

Type of model:

QSAR model using PaDEL descriptors

 

Explicit algorithm:

Distance weighted k-nearest neighbors (kNN) This is a refinement of the classical k-NN classification algorithm where the contribution of each of the k neighbors is weighted according to their distance to the query point, giving greater weight to closer neighbors.The used distance is the Euclidean distance. kNN is an unambiguous algorithm that fulfills the transparency requirements of OECD principle 2 with an optimal compromise between 4.Defining the algorithm - OECD Principle 2 model complexity and performance.

 

OECD Principle 3(Defining the applicability domain):

Method used to assess the applicability domain:The applicability domain of the model is assessed in two independent levels using two different distance-based methods. First, a global applicability domain is determined by means of the leverage approach that checks whether the query structure falls within the multidimensional chemical space of the whole training set. The leverage of a query chemical is proportional to its Mahalanob is distance measure from the centroid of the training set. The leverages of a given dataset are obtained from the diagonal values of the hat matrix. This approach is associated with a threshold leverage that corresponds 5.Defining the applicability domain - OECD Principle 3 to 3*p/n where p is the number of model variables while n is the number of training compounds. A query chemical with leverage higher than the threshold is considered outside the AD and can be associated with unreliable prediction. The leverage approach has specific limitations, in particular with respects to gaps within the descriptor space of the model or at the boundaries of the training set. To obviate such limitations, a second tier of applicability domain assessement was added. This comprised a local approach which only investigated the vicinity of the query chemical. This local approach provides a continuous index ranging from 0 to 1 which is different from the first approach which only provides Boolean answers (yes/no). This local AD-index is relative to the similarity of the query chemical to its 5 nearest neighbors in the p dimensional space of the model. The higher this index, the more the prediction is likely to be reliable.

 

OECD Principle 4 (Internal validation):

Availability of the training set: Yes

Statistics for goodness-of-fit: Performance in training: R2=0.81 RMSE=0.54

Robustness - Statistics obtained by leave-many-out cross-validation: Performance in 5-fold cross-validation: Q2=0.81 RMSE=0.55

 

OECD Principle 4(External validation):

Availability of the external validation set: Yes

.Predictivity - Statistics obtained by external validation: Performance in test: R2=0.71 RMSE=0.61

Experimental design of test set:

The structures are randomly selected to represent 25% of the available data keeping a similar normal distrubution of LogKoc vlaues in both training and test sets using the Venetian blinds method.

 

OECD Principle 5 (Providing a mechanistic interpretation):

Mechanistic basis of the model: The model descriptors were selected statistically but they can also be mechanistically interpreted. KOC is the ratio between the concentration of a chemical adsorbed by the soil normalized to soil organic carbon and the concentration dissolved in the soil water. Thussoil sorption is closely related to water solubility and logP. Therefore, the chemical features which determine the soil sorption are similar to those related to water solubility and logP. In particular, size related descriptors since larger compounds tend to have higher soil sorption because they do have lower water solubility. Also elctronic profile descriptors related to charges and to charge distribution are of high importance: the presence of active functional group next to carbon leads to better water solubility, likewise higher polarity leads to better water solubility.

Validity criteria fulfilled:
not specified
Conclusions:
From CompTox Chemistry Dashboard using OPERA (OPEn (quantitative) structure-activity Relationship Application) V1.02 model in which calculation based on PaDEL descriptors (calculate molecular descriptors and fingerprints of chemical) the adsorption coefficient i.e KOC for test substance 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3-trimethyl-3H-indolium chloride was estimated to be 8100 L/kg (Log Koc = 3.908).
Executive summary:

From CompTox Chemistry Dashboard using OPERA (OPEn (quantitative) structure-activity Relationship Application)  V1.02 model in which calculation based on PaDEL descriptors (calculate molecular descriptors and fingerprints of chemical)  the adsorption coefficient i.e KOC for test substance 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3- trimethyl-3H-indolium chloride was estimated to be 8100 L/kg (Log Koc = 3.908). The predicted KOC result based on the 5 OECD principles.

Thus based on the result it is concluded that the test substance 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3-trimethyl-3H-indolium chloride is have strong sorption to soil and sediment, negligible to slow migration potential to ground water.

Description of key information

From CompTox Chemistry Dashboard using OPERA (OPEn (quantitative) structure-activity Relationship Application)  V1.02 model in which calculation based on PaDEL descriptors (calculate molecular descriptors and fingerprints of chemical)  the adsorption coefficient i.e KOC for test substance 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3- trimethyl-3H-indolium chloride was estimated to be 8100 L/kg (Log Koc = 3.908). The predicted KOC result based on the 5 OECD principles.

Thus based on the result it is concluded that the test substance 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3-trimethyl-3H-indolium chloride is have strong sorption to soil and sediment, negligible to slow migration potential to ground water.

Key value for chemical safety assessment

Koc at 20 °C:
8 100

Additional information

From CompTox Chemistry Dashboard using OPERA (OPEn (quantitative) structure-activity Relationship Application)  V1.02 model in which calculation based on PaDEL descriptors (calculate molecular descriptors and fingerprints of chemical)  the adsorption coefficient i.e KOC for test substance 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3- trimethyl-3H-indolium chloride was estimated to be 8100 L/kg (Log Koc = 3.908). The predicted KOC result based on the 5 OECD principles.

Thus based on the result it is concluded that the test substance 2-[2-[4-[(2-chloroethyl)ethylamino]-o-tolyl]vinyl]-1,3,3-trimethyl-3H-indolium chloride is have strong sorption to soil and sediment, negligible to slow migration potential to ground water.

[LogKoc: 3.908]