Meet StarDrop’s Metabolism module

Quickly identify metabolic pathways, potential metabolites and guide compound design to avoid metabolic liabilities. Have confidence in your results, with accurate, transferable predictions based on fundamental mechanistic understanding of Phase I and II enzyme family reactions.

With the Metabolism module, you can:

Try the Metabolism Module

Identify atomic sites vulnerable to metabolism

Guide compound design towards improved stability by identifying sites vulnerable to metabolism by a range of Phase I and II enzyme families.

See which enzymes or isoforms are most likely to metabolise your compound

Inform experimental prioritisation and reduce the risk of drug-drug interactions.

Predict metabolic pathways and metabolites with sensitivity and precision

You can map pathways in a clear, intuitive way with Card View®.

Compare cytochrome P450 regioselectivity between human and animal species

Identify the best preclinical species for testing with rat, mouse and dog cytochrome P450 models.

Tackle common questions around drug metabolism

Which enzymes will metabolise my compound?

Use the WhichEnzyme™ model to identify which of five key enzyme families involved in drug metabolism is most likely to be responsible for your compound’s metabolism in humans, covering:

  • Cytochrome P450s (CYPs)
  • Aldehyde oxidases (AOXs)
  • Flavin-containing monooxygenases (FMOs)
  • Uridine diphosphate glucuronosyltransferases (UGTs)
  • Sulfotransferases (SULTs)

Take this further to an isoform-specific level with the WhichP450™ model, identifying which of the seven major drug metabolising isoforms of human cytochrome P450 will be most likely to metabolise your compound.

Discover compounds with multiple routes of metabolism to avoid potential drug-drug interactions, and identify the most important enzymes to ensure coverage for during experimental testing.

Which metabolites will form? Will any be toxic or reactive?

With regioselectivity models, identify the sites at which metabolism is likely to occur and corresponding potential metabolites for a range of enzyme families, again spanning human CYPs, AOXs, FMOs, UGTs and SULTs, plus rat, mouse and dog CYP.

Predict metabolic pathways with good accuracy and precision, helping you identify the most likely experimentally observed metabolites. Use the findings of these models to help interpret metabolite ID experiments. Combine your predictions with StarDrop’s Derek Nexus module to identify toxic endpoints within your metabolites which might result in adverse side effects in patients.

How can I improve the metabolic stability of my compound?

Identify potential sites of metabolism using regioselectivity models to prioritise sites for further optimisation. Guide the redesign of your compounds to block potentially labile sites, whilst ensuring balance across important properties by using StarDrop’s core Probabilistic Scoring feature for multi-parameter optimisation.

How can I avoid drug-drug interactions?

Drug-drug interactions (DDIs) generally occur where co-administered drugs are predominantly metabolised by the same isoform. The drugs can interfere with the clearance of one another, leading to increased drug concentrations and potential toxicity. Therefore, in order to minimise potential DDIs, compounds generally need to be metabolised by more than one enzyme family or isoform. Identify compounds with multiple routes of clearance using the Metabolism module’s WhichEnzyme and WhichP450 models.

Which animal species should I use in preclinical toxicology studies?

Models for rat, mouse and dog cytochrome P450 allow comparison with human metabolite predictions to help identify the preclinical species likely to give the best match of metabolites in preclinical experiments.

Cutting-edge quantum mechanics and machine learning models

Based on fundamental mechanistic understanding, our models have greater accuracy and transferability than conventional QSAR methods. Regioselectivity models allow you to identify sites of metabolism for several key enzymes involved across human Phase I and II metabolism, including:

  • Cytochrome P450s (CYPs)
  • Flavin-containing monooxygenases (FMOs)
  • Aldehyde oxidases (AOXs)
  • Uridine diphosphate glucuronosyltransferases (UGTs)
  • Sulfotransferases (SULTs)

In addition, the module includes models for rat, dog and mouse CYPs, so you can identify the sites of metabolism for common preclinical species and compare to human predictions.

Alongside these regioselectivity models, our WhichEnzyme™ and WhichP450™ models help you predict the enzyme family or specific human CYP isoform which will be most likely overall to metabolise your compound.

Discover how our models work by browsing our peer-reviewed publications.

Browse publications

Metabolism Card View AOX
An example output from the Metabolism module in Card View.
The mechanism of metabolism by flavin-containing monooxgenases, one of the reactions we studied in developing our models

Map metabolic pathways

Generate multi-generational metabolic pathways, visualising the relationships between metabolites and the parent compound easily in Card View. Rigorously tested for sensitivity and precision to avoid metabolite overprediction, the resultant potential metabolites are prioritised to show which are most likely to actually be observed in vivo. This gives a more realistic representation of drug metabolism within the body, enabling users to best optimise their molecules for stability against the most relevant enzymes. Used in conjunction with our Derek Nexus module, you can also gain information on the toxicity of potential metabolites.

Dextromethorphan metabolite pathways

More metabolism resources

Try StarDrop’s Metabolism module

Interested in trying the StarDrop Metabolism module for yourself? Complete the form and a member of the team will get in touch to discuss your needs.