Computational Modelling of Structures and Ligands of CYP2C9
Abstract: CYP2C9 is one of our major drug metabolising enzymes and belongs to the cytochrome P450 (CYP) super family. The aim of this thesis was to gain an understanding of the quantitative structure–activity relationships (QSAR) of CYP2C9 substrates and inhibitors. This information will be useful in predicting drug metabolism and the potential for drug–drug interactions. To achieve this, a well characterised data set of structurally diverse, competitive CYP2C9 inhibitors was identified in our laboratory. Several computational methodologies, many based on GRID molecular interaction fields, were applied or developed in order to handle issues such as compound alignment and bioactive conformer selection. First, a traditional 3D QSAR was carried out in GOLPE, generating a predictive model. In this model the selection of a bioactive conformer and alignment was based on docking in a homology model of CYP2C9. Secondly, we introduced the concept of alignment independent descriptors from ALMOND. These descriptors were used to generate quantitatively and qualitatively predictive models. We subsequently derived conformation independent descriptors from molecular interaction fields calculated in FlexGRID. This enabled the derivation of 3D QSAR models without taking into account the selection of an alignment or a bioactive conformer. A subsequent programming effort enabled the conversion of this model back to 3D aligned pharmacophores. Similar alignment independent descriptors were also used in the development of the software MetaSite® that predicts the site of metabolism for CYP2C9 ligands. Finally, as crystal information on this isoform emerged, the performance of molecular dynamics simulations and homology models and the flexibility of the protein were evaluated using statistical analyses.These modelling efforts have resulted in detailed knowledge of the structural characteristics in ligand interactions with the cytochrome P450 2C9 isoform.
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