StarDrop Modules
Metabolism
Precision modelling to determine Phase I and II metabolic routes, sites, products and lability
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:
- Identify atomic sites vulnerable to metabolism by multiple enzyme families to guide compound design towards improved stability.
- See which enzymes or isoforms are most likely to metabolise your compound to inform experiment prioritisation and reduce the risk of drug-drug interactions.
- Predict metabolic pathways and metabolites with sensitivity and precision, mapping these in a clear, intuitive way with Card View®.
- Compare cytochrome P450 regioselectivity between human and animal species to identify the best preclinical species for testing.
Tackle common questions around drug metabolism
Which enzymes will metabolise my compound?
- 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?
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?
How can I avoid drug-drug interactions?
Which animal species should I use in preclinical toxicology studies?
Cutting-edge quantum mechanics and machine learning models
- 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.
Map metabolic pathways