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:1988
Name:2-bromo-1-(pyren-1-yl)ethan-1-one
Description:
Labels:Neutral
CAS:80480-15-5
InChi Code:InChI=1/C18H11BrO/c19-10-16(20)14-8-6-13-5-4-11-2-1-3-12-7-9-15(14)18(13)17(11)12/h1-9H,10H2

Properties

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

ValueSource or prediction
2.39

experimental value
2.36

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
2.35

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
2.38

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
1.22

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
2.48

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
2.25

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
2.4

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
2.56

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
2.52

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
3.43

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
2.36

DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
3.01

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