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:1424
Name:2-propylpentanoic acid
Description:
Labels:Neutral
CAS:99-66-1
InChi Code:InChI=1/C8H16O2/c1-3-5-7(6-4-2)8(9)10/h7H,3-6H2,1-2H3,(H,9,10)/f/h9H

Properties

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

ValueSource or prediction
0.03

experimental value

0.01

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

-0.02

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

0.04

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

0.21

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

0.08

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

0.1

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

0.03

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

-0.02

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

0.03

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

0.18

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

0.03

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

0.07

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