In-Silico Drug-Drug Interaction Prediction: CYP Inhibition, Transporters and What Models Support

By BioDockify Computational Research Team · October 17, 2026 · Concepts

Predicting drug-drug interactions computationally: the CYP enzyme system, competitive inhibition and mechanism-based inactivation, what pkCSM/SwissADME-style models output, how DDI risk escalates from inhibition data, and honest limits for clinical claims.

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Key References

• Veith, H. et al. Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries. Nat. Biotechnol. 27, 1050-1055 (2009).
• Pires, D.E.V., Kaminskas, L.M., Ascher, D.B. et al. pkCSM. J. Med. Chem. 58, 4066-4072 (2015). DOI: 10.1021/acs.jmedchem.5b00104
• Daina, A., Michielin, O. & Zoete, V. SwissADME. J. Med. Chem. 60, 598-620 (2017). DOI: 10.1021/acs.jmedchem.6b01804
• US FDA. Clinical Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions. Guidance for Industry (2020).

Scope & Limitations

In-silico CYP outputs are screening signals, not diagnoses - clinical DDI risk depends on exposure, therapeutic index and concentration at the enzyme, which simple models do not integrate transporter-mediated and UGT interactions are far less predictable than CYP; model coverage there is thin