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Prediction of Drug-Like Molecular Properties

Modeling Cytochrome P450 Interactions
  • Mehran Jalaie
  • Rieko Arimoto
  • Eric Gifford
  • Sabine Schefzick
  • Chris L. Waller
Protocol
Part of the Methods in Molecular Biology™ book series (MIMB, volume 275)

Abstract

Preventing drug-drug interactions and reducing drug-related mortalities dictate cleaner and costlier medicines. The cost to bring a new drug to market has increased dramatically over the last 10 years, with post-discovery activities (preclinical and clinical) costs representing the majority of the spend. With the ever-increasing scrutiny that new drug candidates undergo in the post-discovery assessment phases, there is increasing pressure on discovery to deliver higher-quality drug candidates. Given that compound attrition in the early clinical stages can often be attributed to metabolic liabilities, it has been of great interest lately to implement predictive measures of metabolic stability/liability in the drug design stage of discovery. The solution to this issue is wrapped in understanding the basic of the cytochrome P450 (CYP) enzymes functions and structures. Recently, experimental information on the structure of a variety of cytochrome P450 enzymes, major contributors to phase I metabolism, has become readily available. This, coupled with the availability of experimental information on substrate specificities, has lead to the development of numerous computational models (macromolecular, pharmacophore, and structure-activity) for the rationalization and prediction of CYP liabilities. A comprehensive review of these models is presented in this chapter.

Key Words

CYP P450 cytochrome P450 docking structure-based drug discovery pharmacophore QSAR homology models databases computational models ADME/T 

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Copyright information

© Humana Press Inc. 2004

Authors and Affiliations

  • Mehran Jalaie
    • 1
  • Rieko Arimoto
    • 1
  • Eric Gifford
    • 1
  • Sabine Schefzick
    • 1
  • Chris L. Waller
    • 1
  1. 1.Discovery Technologies, Pfizer Global Research and DevelopmentAnn ArborUSA

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