Predicting zebrafish (Danio rerio) embryo developmental toxicity through a non-conformational QSAR approach

Highlights: • 188 active chemicals in zebrafish embryo assay are predicted using freeware. • A QSAR model based on the ToxCast™ phase I chemical library has proposed suitably. • The present model accomplishes with the international OECD QSAR validation principles. • 94% of the whole molecular set has been predicted reliably by the QSAR model. • This non-conformational approach provides a tool for predicting AC₅₀ in new molecules. For many years, the frequent use of synthetic chemicals in the manufacture of veterinary drugs and plague control products has raised negative effects on human health and other non-target organisms, promoting the need to employ a practical and suitable methodology for early risk identification of several thousand commercial compounds. The zebrafish (Danio rerio) embryo has been emerged as one sustainable animal model for measuring developmental toxicity, an endpoint that is included in the regulatory procedures to approve chemicals, avoiding conventional and costly toxicity assays based on animal testing. In this context, the Quantitative Structure-Activity Relationships (QSAR) theory is applied to develop a predictive model based on a well-defined zebrafish embryo developmental toxicity database reported by the ToxCast™ Phase I chemical library of the Environmental Protection Agency (U.S. EPA). By means of four freely available softwares, a set with 28,038 non-conformational descriptors that encode the largest amount of permanent structural features are readily calculated. The Replacement Method (RM) variable subset selection technique provided the best regression models. Thereby, a linear QSAR model with proper statistical quality ($R_{\mathrm{train}}^2$ = 0.64, RMSE_train = 0.49) is established in agreement with the Organization for Economic Co-operation and Development principles, accomplishing each internal (loo, l15 % o, VIF and Y-randomization) and external ($R_{\mathrm{test}}^2$,$R_m^2$, $Q_{F1}^2$, $Q_{F2}^2$, $Q_{F3}^2$ and CCC) validation criterion. The present QSAR approach provides a useful computational tool to estimate zebrafish developmental toxicity of new, untasted or hypothetical compounds, and it can contribute to the general lack of QSAR models in the literature to predict this endpoint.