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Pharm Res. 2007 Mar;24(3):480-501.

Predicting the oxidative metabolism of statins: an application of the MetaSite algorithm.

Author information

1
Dipartimento di Scienza e Tecnologia del Farmaco, via Giuria 9, 10125 Torino, Italy. giulia.caron@unito.it

Abstract

PURPOSE:

This study was undertaken to examine the MetaSite algorithm by comparing its predictions with experimentally characterized metabolites of statins produced by cytochromes P450 (CYPs).

METHODS:

Seven statins were investigated, namely atorvastatin, cerivastatin, fluvastatin, pitavastatin and pravastatin which are (or were) used in their active hydroxy-acid form, and lovastatin and simvastatin which are used as the lactone prodrug. But given the fast lactone-hydroxy-acid equilibrium undergone by statins, both forms were investigated for each of the seven drugs. The MetaSite version 2.5.3 used here contains the homology 3D-models of CYP1A2, CYP2C19, CYP2C9, CYP2D6 and CYP3A4. In addition, we also used the crystallographic 3D-structure of human CYP2C9 and CYP3A4. To allow a better interpretation of results, the probability function PsMi calculated by MetaSite (namely the probability of atom i to be a site of metabolism) was explicitly decomposed into its two components, namely a recognition score Ei (the accessibility of atom i) and the chemical reactivity Ri of atom i toward oxidation reactions.

RESULTS:

The current version of MetaSite is known to work best with prior experimental knowledge of the cytochrome(s) P450 involved. And indeed, experimentally confirmed sites of oxidation were correctly given a high priority by MetaSite. In particular 77% of correct predictions (including false positive but, as discussed, this is not necessarily a shortcoming) were obtained when considering the first five metabolites indicated by MetaSite.

CONCLUSION:

To the best of our knowledge, this is the first independent report on the software. It is expected to contribute to the development of improved versions, but above all it demonstrates that the usefulness of such softwares critically depends on human experts.

PMID:
17253156
DOI:
10.1007/s11095-006-9199-7
[Indexed for MEDLINE]
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