Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.
Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.
Laboratory for Molecular Modeling, Division of Medicinal Chemistry and Natural Products, Carolina Environmental Bioinformatics Research Center, School of Pharmacy, University of North Carolina at Chapel Hill, North Carolina 27599-7568, USA.
Hao
H
Zhu
Todd M
TM
Martin
Lin
L
Ye
Alexander
A
Sedykh
Douglas M
DM
Young
Alexander
A
Tropsha
D000284:Administration, Oral; D000818:Animals; D007928:Lethal Dose 50; D008962:Models, Theoretical; D009930:Organic Chemicals / Q000737:chemistry / Q000633:toxicity; D021281:Quantitative Structure-Activity Relationship; D051381:Rats; D023382:Toxicity Tests, Acute
D009930:Organic Chemicals