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:1950
Name:1-(4-hydroxyphenyl)-2-phenylethan-1-one
Description:
Labels:Neutral
CAS:2491-32-9
InChi Code:InChI=1/C14H12O2/c15-13-8-6-12(7-9-13)14(16)10-11-4-2-1-3-5-11/h1-9,15H,10H2

Properties

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

ValueSource or prediction
1.07

experimental value

1.12

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

1.23

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

1.06

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

1.05

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

1.15

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

1.02

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

1.11

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

1.31

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

1.05

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

1.09

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

1.06

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

1.11

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