Prediction of Metabolic Transformations using Cross Venn-ABERS Predictors
Proceedings of the Sixth Workshop on Conformal and Probabilistic Prediction and Applications, PMLR 60:118-131, 2017.
Prediction of drug metabolism is an important topic in the drug discovery process, and we here present a study using probabilistic predictions applying Cross Venn-ABERS Predictors (CVAPs) on data for site-of-metabolism. We used a dataset of 73599 biotransformations, applied SMIRKS to define biotransformations of interest and constructed five datasets where chemical structures were represented using signatures descriptors. The results show that CVAP produces well-calibrated predictions for all datasets with good predictive capability, making CVAP an interesting method for further exploration in drug discovery applications.