Prediction of Metabolic Transformations using Cross Venn-ABERS Predictors

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Published: 2017-05-23

Formatted citation

Arvidsson S, Carlsson L, Toccaceli P, and Spjuth O.. Prediction of Metabolic Transformations using Cross Venn-ABERS Predictors.
Proceedings of Machine Learning Research. 60, 1-14. (2017).

Abstract

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.