Publications and Presentations

Predicting Regioselectivity of Cytosolic SULT Metabolism for Drugs

Predicting SULT metabolism

This new peer-reviewed paper in the Journal of Chemical Information and Modeling describes a model to predict whether a particular site on a molecule will be metabolised by cytosolic sulfotransferase enzymes (SULTs). The paper builds on previous metabolism prediction research, developing the capabilities available in StarDrop.

Table of Contents image for SULT metabolism paper, showing most likely sites to be metabolised compared to experimental observations


Mario Öeren, Sylvia C. Kaempf, David J. Ponting, Peter A. Hunt, Matt D. Segall


During phase II drug metabolism, also known as the conjugation phase, compounds are conjugated to other polar compounds. The main enzymes involved are uridine 5′-diphospho-glucuronosyltransferases (UGTs), however another prominent family during this phase are cytosolic sulfotransferases (SULTs). These enzymes are responsible for the sulfation reactions. To discover how small molecules with be metabolised in this conjugation phase, it is crucial to see how the regioselectivity of SULTs differ from that of UGTs.

In this paper, the research team developed a general ligand-based model, to predict whether a site will be metabolized by SULTs. During the study, they found that the SULT binding site was the main influence on regioselectivity of metabolism, rather than any influence by the activation energy of the rate-limiting step of the catalysis. Therefore, they trained the model only on steric and orientation descriptors, to mimic the SULT binding pocket, generating a model with very good accuracy values.

Find out more

Read the full SULT metabolism paper on the journal webpage. If you would like to discover more of our metabolism research, take a look at our recent J. Med. Chem. paper, which describes how to predict the regioselectivity of AO, CYP, FMO and UGT metabolism, or watch our webinar, on the integrated prediction of phase I and II metabolism.



Understanding drug metabolism is crucial to avoid late-stage failure of drug candidates. Optibrium is working at the forefront of predictive modelling, constantly bringing out new research and product updates to help you get a better understanding of your compound’s metabolic stability.