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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


M. Öeren, S. C. Kaempf, D. J. Ponting, P. A. Hunt, M. D. Segall


Cytosolic sulfotransferases (SULTs) are a family of enzymes responsible for the sulfation of small endogenous and exogenous compounds. SULTs contribute to the conjugation phase of metabolism and share substrates with the Uridine 5′-diphospho-glucuronosyltransferase (UGT) family of enzymes. UGTs are considered to be the most important enzymes in the conjugation phase, and SULTs are an auxiliary enzyme system to them. Understanding how the regioselectivity of SULTs differs from that of UGTs is essential from the perspective of developing novel drug candidates.

We present a general ligand-based SULT model trained and tested using high-quality experimental regioselectivity data. The current study suggests that, unlike other metabolic enzymes in the modification and conjugation phases, SULT regioselectivity is not strongly influenced by the activation energy of the rate-limiting step of the catalysis. Instead,  substrate binding site of SULT plays the prominent role. Thus, the model is trained only on steric and orientation descriptors, which mimic the binding pocket of SULT. The resulting classification model, which predicts whether a site is metabolized, achieved a Cohen’s kappa of 0.65.

Find out more

Download the preprint of this SULT metabolism paper via the button below or find the final publication 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.


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. Register your interest now to be first to know about our latest metabolism prediction research, development and product updates.