Application of in silico approaches to predicting drug--drug interactions.
In an environment driven to find the next blockbuster drug, failure years into a project should not be an option. Recent studies have shown that poor absorption, distribution, metabolism, and excretion (ADME), and the related properties of toxicity and pharmacokinetics are responsible for a large proportion of failures. One way to understand and potentially predict molecules likely to be successful in humans as drugs from an ADME point of view is to use simulations. Such simulations may include simple rule-based approaches, structure--activity relationships, three-dimensional quantitative structure--activity relationships (3D-QSAR), and pharmacophores. All of these represent useful tools in understanding metabolism by the cytochromes P450, predicting drug--drug interactions (DDIs), and other pharmacokinetic parameters. The present paper briefly reviews the application of some computational tools applied to predicting DDIs and will provide the reader with an idea of their utility.
Ekins
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Lilly Research Laboratories, Lilly Corporate Center, Drop Code 1730, Indianapolis, IN 46285, USA. ekins_sean@lilly.com
Wrighton
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D003198:Computer Simulation; D003577:Cytochrome P-450 Enzyme System / Q000378:metabolism; D015195:Drug Design; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D008958:Models, Molecular; D008968:Molecular Conformation; D010599:Pharmacokinetics; D010600:Pharmacology / Q000379:methods*; D021281:Quantitative Structure-Activity Relationship
D003577:Cytochrome P-450 Enzyme System