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:1699
Name:1,3-diethyl 2-(propan-2-ylidene)propanedioate
Description:
Labels:Neutral
CAS:6802-75-1
InChi Code:InChI=1/C10H16O4/c1-5-13-9(11)8(7(3)4)10(12)14-6-2/h5-6H2,1-4H3

Properties

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

ValueSource or prediction
-0.07

experimental value

0.12

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

0.43

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

-0.06

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

1.4

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

0.27

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

0.28

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

0.01

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

0.5

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

0.17

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

0.79

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

-0.07

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

0.74

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