Discovery of a novel binding pocket for CYP 2C9 inhibitors: crystallography, pharmacophore modelling and inhibitor SAR

CYP 2C9 co-crystal structures of compound1(green) in binding mode 1 (CYP 2C9 in green) and compound2(yellow) in binding mode 2 (CYP 2C9 in yellow).

Functional characterization of 12 allelic variants of CYP2C8 by assessment of paclitaxel 6α-hydroxylation and amodiaquine N-deethylation

Cytochrome P450 2C8 (CYP2C8) is one of the enzymes primarily responsible for the metabolism of many drugs, including paclitaxel and amodiaquine. CYP2C8 genetic variants contribute to interindividual variations in the therapeutic efficacy and toxicity of paclitaxel. Although it is difficult to investigate the enzymatic function of most CYP2C8 variants in vivo, this can be investigated in vitro using recombinant CYP2C8 protein variants. The present study used paclitaxel to evaluate 6α-hydroxylase activity and amodiaquine for the N-deethylase activity of wild-type and 11 CYP2C8 variants resulting in amino acid substitutions in vitro. The wild-type and variant CYP2C8 proteins were heterologously expressed in COS-7 cells. Paclitaxel 6α-hydroxylation and amodiaquine N-deethylation activities were determined by measuring the concentrations of 6α-hydroxypaclitaxel and N-desethylamodiaquine, respectively, and the kinetic parameters were calculated. Compared to the wild-type enzyme (CYP2C8.1), CYP2C8.11 and CYP2C8.14 showed little or no activity with either substrate. In addition, the intrinsic clearance values of CYP2C8.8 and CYP2C8.13 for paclitaxel were 68% and 67% that of CYP2C8.1, respectively. In contrast, the CLint values of CYP2C8.2 and CYP2C8.12 were 1.4 and 1.9 times higher than that of CYP2C8.1. These comprehensive findings could inform for further genotype-phenotype studies on interindividual differences in CYP2C8-mediated drug metabolism.

Pocket-space maps to identify novel binding-site conformations in proteins

The identification of novel binding-site conformations can greatly assist the progress of structure-based ligand design projects. Diverse pocket shapes drive medicinal chemistry to explore a broader chemical space and thus present additional opportunities to overcome key drug discovery issues such as potency, selectivity, toxicity, and pharmacokinetics. We report a new automated approach to diverse pocket selection, PocketAnalyzer(PCA), which applies principal component analysis and clustering to the output of a grid-based pocket detection algorithm. Since the approach works directly with pocket shape descriptors, it is free from some of the problems hampering methods that are based on proxy shape descriptors, e.g. a set of atomic positional coordinates. The approach is technically straightforward and allows simultaneous analysis of mutants, isoforms, and protein structures derived from multiple sources with different residue numbering schemes. The PocketAnalyzer(PCA) approach is illustrated by the compilation of diverse sets of pocket shapes for aldose reductase and viral neuraminidase. In both cases this allows identification of novel computationally derived binding-site conformations that are yet to be observed crystallographically. Indeed, known inhibitors capable of exploiting these novel binding-site conformations are subsequently identified, thereby demonstrating the utility of PocketAnalyzer(PCA) for rationalizing and improving the understanding of the molecular basis of protein-ligand interaction and bioactivity. A Python program implementing the PocketAnalyzer(PCA) approach is available for download under an open-source license ( http://sourceforge.net/projects/papca/ or http://cpclab.uni-duesseldorf.de/downloads ).

Exploration of Enzyme−Ligand Interactions in CYP2D6 & 3A4 Homology Models and Crystal Structures Using a Novel Computational Approach

New crystal structures of human CYP2D6 and CYP3A4 have recently been reported, and in this study, we wanted to compare them with previously used homology models with respect to predictions of site of metabolism and ligand-enzyme interactions. The data set consisted of a family of synthetic opioid analgesics with the aim to cover both CYP2D6 and CYP3A4, as most of these compounds are metabolized by both isoforms. The program MetaSite was used for the site of metabolism predictions, and the results were validated by experimental assessment of the major metabolites formed with recombinant CYP450s. This was made on a selection of 14 compounds in the data set. The prediction rates for MetaSite were 79-100% except for the CYP3A4 homology model, which picked the correct site in half of the cases. Despite differences in orientation of some important amino acids in the active sites, the MetaSite-predicted sites were the same for the different structures, with the exception of the CYP3A4 homology model. Further exploration of interactions with ligands was done by docking substrates/inhibitors in the different structures with the docking program GLUE. To address the challenge in interpreting patterns of enzyme-ligand interactions for the large number of different docking poses, a new computational tool to handle the results from the dockings was developed, in which the output highlights the relative importance of amino acids in CYP450-substrate/inhibitor interactions. The method is based on calculations of the interaction energies for each pose with the surrounding amino acids. For the CYP3A4 structures, this method was compared with consensus principal component analysis (CPCA), a commonly used method for structural comparison to evaluate the usefulness of the new method. The results from the two methods were comparable with each other, and the highlighted amino acids resemble those that were identified to have a different orientation in the compared structures. The new method has clear advantages over CPCA in that it is far simpler to interpret and there is no need for protein alignment. The methodology enables structural comparison but also gives insights on important amino acid substrate/inhibitor interactions and can therefore be very useful when suggesting modifications of new chemical entities to improve their metabolic profiles.

Multiple molecular dynamics simulations of human p450 monooxygenase CYP2C9: The molecular basis of substrate binding and regioselectivity toward warfarin

To examine the molecular basis of activity and regioselectivity of the clinically important human microsomal cytochrome P450 (CYP) monooxygenase 2C9 toward its substrate warfarin, 22 molecular dynamics simulations (3-5 ns each) were performed in the presence and absence of warfarin. The resulting trajectories revealed a stable protein core and mobile surface elements. This mobility leads to the formation of two surface channels in the region between F-G loop, B' helix/B-B' loop, beta(1)-sheet, and between helices F and I and the turn in the C-terminal antiparallel beta-sheet in the presence of warfarin. Besides the nonproductive state of the CYP2C9 warfarin complex captured in the crystal structure, three additional states were observed. These states differ in the shape of the substrate binding cavity and the position of the warfarin molecule relative to heme. In one of these states, the 7- and 6-positions of warfarin contact the heme with a marked geometrical preference for position 7 over position 6. This modeling result is consistent with experimentally determined regioselectivity (71 and 22% hydroxylation in positions 7 and 6, respectively). Access to the heme group is limited by the core amino acids Ala297, Leu362, Leu366, and Thr301, which therefore are expected to have a major impact on regioselectivity. In addition, modeling predicts that autoactivation of warfarin is sterically hindered. Our study demonstrates how the combination of mobile surface and rigid core leads to interesting properties: a broad substrate profile and simultaneously a high regioselectivity.