10967/264 - QDB Compounds

QsarDB Repository

Belfield, S. J.; Cronin, M. T. D.; Enoch, S. J.; Firman, J. W. Guidance for Good Practice in the Application of Machine Learning in Development of Toxicological Quantitative Structure-Activity Relationships (QSARs). PLOS ONE, 2023, 18, e0282924.

Compound

ID:228
Name:3,5-dichloro-2,6-difluoropyridin-4-amine
Description:
Labels:Neutral
CAS:2840-00-8
InChi Code:InChI=1/C5H2Cl2F2N2/c6-1-3(10)2(7)5(9)11-4(1)8/h(H2,10,11)/f/h10H2

Properties

pIGC50: 40-h Tetrahymena toxicity as log(1/IGC50) [log(L/mmol)] i

ValueSource or prediction
0.6

experimental value

0.83

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)

1.06

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)

0.59

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)

0.61

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)

0.67

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)

1.07

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)

0.63

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)

0.72

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)

0.61

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)

0.77

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)

0.47

DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)

0.58

DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)