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:761
Name:2-bromohexanoic acid
Description:
Labels:Neutral
CAS:616-05-7
InChi Code:InChI=1/C6H11BrO2/c1-2-3-4-5(7)6(8)9/h5H,2-4H2,1H3,(H,8,9)/t5?/f/h8H

Properties

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

ValueSource or prediction
0.45

experimental value

0.33

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

0.13

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

0.44

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

0.12

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

0.07

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

-0.07

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

0.35

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

-0.01

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

0.39

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

0.29

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

0.44

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

0.13

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