Modeling the effects of commonly used drugs on human metabolism

Metabolism contributes significantly to the pharmacokinetics and pharmacodynamics of a drug. In addition, diet and genetics have a profound effect on cellular metabolism with respect to both health and disease. In the present study, we assembled a comprehensive, literature-based drug metabolic reconstruction of the 18 most highly prescribed drug groups, including statins, anti-hypertensives, immunosuppressants and analgesics. This reconstruction captures in detail our current understanding of their absorption, intracellular distribution, metabolism and elimination. We combined this drug module with the most comprehensive reconstruction of human metabolism, Recon 2, yielding Recon2-DM1796, which accounts for 2803 metabolites and 8161 reactions. By defining 50 specific drug objectives that captured the overall drug metabolism of these compounds, we investigated the effects of dietary composition and inherited metabolic disorders on drug metabolism and drug-drug interactions. Our main findings include: (a) a shift in dietary patterns significantly affects statins and acetaminophen metabolism; (b) disturbed statin metabolism contributes to the clinical phenotype of mitochondrial energy disorders; and (c) the interaction between statins and cyclosporine can be explained by several common metabolic and transport pathways other than the previously established CYP3A4 connection. This work holds the potential for studying adverse drug reactions and designing patient-specific therapies. Metabolism contributes significantly to drug interactions. Drug metabolism in turn is affected by diet and genetics. To investigate such effects, a metabolic reconstruction of 18 most highly prescribed drug groups was assembled and combined with the most comprehensive reconstruction of human metabolism, Recon 2. The combined model was used to simulate in silico the effect of dietary shifts and inherited metabolic disorders on drug metabolism. This work holds potential for studying adverse drug reactions and designing patient-specific therapies.