A QSAR model is acceptable if the following conditions are met 104 : Thus, satisfying all the above conditions. Y-scrambling validation is a widely used technique to evaluate the robustness of QSAR models and to ensure that the developed models are not derived due to chance. In this test, the dependent variable (observed activity) randomly shuffles while keeping the independent variables (molecular descriptors) unchanged, and a new model is derived. This process is repeated several times and the values of R 2 test, and R 2 cross-validation are recorded. The values of R 2 test and R 2 cross-validation are expected to be low, ensuring the developed QSAR is robust and not derived due to chance. For the current study we run 10 Y-scrambling tests, and the results are presented on Table . All values of R 2 test and R 2 cross-validation are below 0.1 thus confirming that the regression model is not derived due to chance. The results for the predictions of the external test chemicals are presented in Table . The results obtained from all molecular descriptor sets and models in this investigation are available in the Supplementary information material (Figures S4-S24, and Tables ).