Is regression through origin useful in external validation of QSAR models?

The external validation of QSAR models is crucial to ensure their reliability for assessing new chemicals. The most widely used criteria for external validations, which has been applied in hundreds of more recent QSAR studies are the Golbraikh–Tropsha and Roy methods which these criteria are based on the regression through origin (RTO). In this study, the calculations of the deviation parameters such as absolute errors are used for ascertaining the difference between training and test sets to evaluate the prediction capability of the models. However, these results were not in a good agreement with the proposed criteria for external validation and there is an inconsistency in the definition and calculation of r2 of RTO and therefore the constructed criteria based on RTO is not optimal. Instead, the calculation of model errors for training and test sets and compare them, provide a possible reliable method to external validation of QSAR models.

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