Prediction of pesticide acute toxicity using two-dimensional chemical descriptors and target species classification.

ABSTRACT: Previous modelling of the median lethal dose (oral rat LD₅₀) has indicated that local class-based models yield better correlations than global models. We evaluated the hypothesis that dividing the dataset by pesticidal mechanisms would improve prediction accuracy. A linear discriminant analysis (LDA) based-approach was utilized to assign indicators such as the pesticide target species, mode of action, or target species - mode of action combination. LDA models were able to predict these indicators with about 87% accuracy. Toxicity is predicted utilizing the QSAR model fit to chemicals with that indicator. Toxicity was also predicted using a global hierarchical clustering (HC) approach which divides data set into clusters based on molecular similarity. At a comparable prediction c

SUBMITTER: Martin TM 

PROVIDER: S-EPMC5796665 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature