Cytochrome P450 enzymes metabolize most small-molecule drugs, and CYP inhibition is a leading cause of drug-drug interactions. As part of our In Silico ADMET Prediction Service, we predict reversible and time-dependent inhibition, map metabolic soft spots, and estimate DDI risk so chemistry teams can optimize clearance and safety together.
Score compounds against the major drug-metabolizing CYP isoforms using classification and regression models.
Identify mechanism-based inactivation risk with structural alerts and kinetic models.
Predict the atoms and bonds most likely to undergo CYP-mediated biotransformation.
Translate in silico metabolic liability into expected clearance and half-life trends.
Combine inhibition potency with projected exposure to flag victim and perpetrator liabilities.
Connect CYP results with hERG, solubility/permeability, and off-target predictions for a unified view.
CYP assessment becomes actionable when it separates binding, inactivation, biotransformation, and exposure consequences. This metabolic-fate board keeps those mechanisms distinct before results feed into pharmacokinetic and PBPK workflows.
The workflow distinguishes reversible inhibition from time-dependent inactivation and keeps metabolism, clearance, and DDI risk in the same decision frame.
Request a Project ScopeCollect isoform-specific inhibition data, TDI labels, and metabolic stability measurements when available.
Use QSAR, multitask deep learning, or structure-based docking depending on data richness and the decision.
Score compounds across CYP isoforms, flag TDI alerts, and map likely sites of metabolism.
Combine potency with projected exposure to estimate DDI magnitude and clearance consequences.
Provide substitution strategies, control analogs, and a focused in vitro assay plan.
CYP inhibition is not a single endpoint. Each isoform has different structural preferences, and time-dependent inactivation follows distinct chemistry. We report isoform-resolved scores, highlight the difference between reversible and irreversible risk, and keep model uncertainty visible.
Output groups compounds by the nature and severity of CYP liability, separating clean profiles from those needing redesign or confirmatory kinetics.
Isoform-resolved IC50 class probabilities, pIC50 estimates, and confidence notes.
Atom-level soft spots, predicted metabolites, and CYP isoform preferences.
Perpetrator/victim classification and exposure-adjusted DDI risk.
Substitution strategies, control analogs, and in vitro follow-up plan.
The authors screened more than 17,000 compounds against five recombinant CYP isoforms. The resulting dataset exposed isoform-specific SAR trends and provided a foundation for ligand-based CYP inhibition models used throughout the field.
The study developed (Q)SAR models for reversible and time-dependent CYP inhibition. It highlighted the importance of separating these mechanisms during data curation and showed that structural alerts and kinetic features improve TDI prediction.
A strong CYP project starts with the metabolic decision that matters most for your series.
We routinely model 1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A4/5. Additional isoforms can be addressed on a project basis.
We provide site-of-metabolism predictions and likely metabolite proposals. Exact metabolite identification still benefits from LC-MS confirmation.
TDI is mechanism-based enzyme inactivation. It causes a longer-lasting DDI than reversible inhibition and is therefore a higher-priority liability to flag early.
We combine in vitro or predicted inhibition potency with projected unbound plasma concentration to estimate AUC changes and perpetrator/victim risk.
CYP outputs can feed static DDI calculations or be exported for PBPK modeling through our pharmacokinetic prediction services.
Share your structures, any CYP data, and the exposure or DDI question your team is trying to answer. CD ComputaBio will scope a focused analysis and recommend the right follow-up assays. Explore related services: hERG Liability Prediction Service, Solubility and Permeability Prediction Service, Off-Target Risk Prediction Service.
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