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Predictive Capability of QSAR Models Based on the CompTox Zebrafish Embryo Assays: An Imbalanced Classification Problem
- Source :
- Molecules, Volume 26, Issue 6, Molecules, Vol 26, Iss 1617, p 1617 (2021)
- Publication Year :
- 2021
-
Abstract
- The CompTox Chemistry Dashboard (ToxCast) contains one of the largest public databases on Zebrafish (Danio rerio) developmental toxicity. The data consists of 19 toxicological endpoints on unique 1018 compounds measured in relatively low concentration ranges. The endpoints are related to developmental effects occurring in dechorionated zebrafish embryos for 120 hours post fertilization and monitored via gross malformations and mortality. We report the predictive capability of 209 quantitative structure–activity relationship (QSAR) models developed by machine learning methods using penalization techniques and diverse model quality metrics to cope with the imbalanced endpoints. All these QSAR models were generated to test how the imbalanced classification (toxic or non-toxic) endpoints could be predicted regardless which of three algorithms is used: logistic regression, multi-layer perceptron, or random forests. Additionally, QSAR toxicity models are developed starting from sets of classical molecular descriptors, structural fingerprints and their combinations. Only 8 out of 209 models passed the 0.20 Matthew’s correlation coefficient value defined a priori as a threshold for acceptable model quality on the test sets. The best models were obtained for endpoints mortality (MORT), ActivityScore and JAW (deformation). The low predictability of the QSAR model developed from the zebrafish embryotoxicity data in the database is mainly due to a higher sensitivity of 19 measurements of endpoints carried out on dechorionated embryos at low concentrations.
- Subjects :
- Quantitative structure–activity relationship
Embryo, Nonmammalian
Correlation coefficient
Developmental toxicity
Pharmaceutical Science
Quantitative Structure-Activity Relationship
Computational biology
010501 environmental sciences
Logistic regression
01 natural sciences
Article
Analytical Chemistry
structural descriptors
lcsh:QD241-441
03 medical and health sciences
lcsh:Organic chemistry
Molecular descriptor
Drug Discovery
Animals
rdkit
zebrafish embryo
aquatic toxicology
Physical and Theoretical Chemistry
Biology
Zebrafish
030304 developmental biology
0105 earth and related environmental sciences
0303 health sciences
imbalanced classification
Organic Chemistry
toxicity
predictive QSAR
ToxCast
structural fingerprints
machine learning
Perceptron
Random forest
Chemistry (miscellaneous)
Zebrafish embryo
Molecular Medicine
Biological Assay
Algorithms
Water Pollutants, Chemical
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Molecules, Volume 26, Issue 6, Molecules, Vol 26, Iss 1617, p 1617 (2021)
- Accession number :
- edsair.doi.dedup.....88e51329b982db3f3b8806aa2280f7a4