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IN SILICO AND IN VITRO SCREENING FOR INHIBITION OF CYTOCHROME P450 CYP3A4 BY COMEDICATIONS COMMONLY USED BY PATIENTS WITH CANCER

Manchester Interdisciplinary Biocentre, School of Chemical Engineering and Analytical Science, University of Manchester, Manchester, United Kingdom (J.-D.M., M.J.S.); Biomedical Research Centre, University of Dundee, Ninewells Hospital & Medical School, Dundee, United Kingdom (J.Y., S.B., I.K., E.M.R., C.R.W., M.J.I.P.); and Department of Biochemistry, University of Leicester, Leicester, United Kingdom (G.C.K.R.)

(Received September 29, 2005; accepted January 9, 2006)

	Abstract

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Cytochrome P450 3A4 (CYP3A4) is the major enzyme responsible for phase I drug metabolism of many anticancer agents. It is also a major route for metabolism of many drugs used by patients to treat the symptoms caused by cancer and its treatment as well as their other illnesses, for example, cardiovascular disease. To assess the ability to inhibit CYP3A4 of drugs most commonly used by our patients during cancer therapy, we have made in silico predictions based on the crystal structures of CYP3A4. From this set of 33 common comedicated drugs, 10 were predicted to be inhibitors of CYP3A4, with the antidiarrheal drug loperamide predicted to be the most potent. There was significant correlation (r² = 0.75–0.66) between predicted affinity and our measured IC₅₀ values, and loperamide was confirmed as a potent inhibitor (IC₅₀ of 0.050 ± 0.006 µM). Active site docking studies predicted an orientation of loperamide consistent with formation of the major (N-demethylated) metabolite, where it interacts with the phenylalanine cluster and Arg-212 and Glu-374; experimental evidence for the latter interaction comes from the 12-fold increase in K_M for loperamide observed for the Glu-374-Gln mutant. The commonly prescribed drugs loperamide, amitriptyline, diltiazem, domperidone, lansoprazole, omeprazole, and simvastatin were identified by our in silico and in vitro screens as relatively potent inhibitors of CYP3A4 that have the potential to interact with cytotoxic agents to cause adverse effects, highlighting the likelihood of drug-drug interactions affecting chemotherapy treatment.

In recent years, in silico methods have proved to be a useful tool for predicting the binding properties of ligands to mammalian cytochromes P450. Studies (for a review, see Ekins et al., 2003) based on quantitative structure-activity relationships and pharmacophore models have generated useful information on ligand binding of CYP3A substrates (Ekins et al., 1999b) and CYP3A4 inhibitors (Ekins et al., 1999a). These methods are relatively fast and have been useful in determining important features such as autoactivation of CYP3A4 (Ekins et al., 2003). We have used an integrated hypothesis-driven structure-based approach to study CYP2D6 and have been able to identify residues that play a key role in metabolism (Smith et al., 1998; Kirton et al., 2002; Paine et al., 2003; Flanagan et al., 2004), reproduced the binding orientation and affinity of ligands in the active site (Kemp et al., 2004), and discriminated between tightly and weakly binding compounds (Kemp et al., 2004).

In this article, we now describe the use of our structure-based in silico approach, which we have used effectively with CYP2D6, to identify likely drug interactions that would inhibit CYP3A4. We have screened the set of 33 drugs commonly used by our patients with cancer using two independently determined crystal structures of the enzyme (Williams et al., 2004; Yano et al., 2004). This approach correctly predicted that loperamide had the highest affinity for CYP3A4 of all the compounds we tested. This prompted us to investigate its mode of binding. Site-directed mutagenesis supported a predicted key interaction between loperamide and CYP3A4. The relative affinities predicted in silico correlated well with the experimental IC₅₀ values for the 15 comedication compounds in the set that significantly inhibited the enzyme. Such inhibition may have unwanted effects on the efficacy and toxicity of anticancer agents using the same pathway, and this merits further study.

	Materials and Methods

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Molecular Docking. We chose a set of 33 drugs based on an analysis of the medications taken by 100 newly diagnosed patients undergoing chemotherapy for their lung cancer (Table 1). Docking studies for these drugs were carried out as described previously (Kemp et al., 2004). In brief, the program GOLDv2.2 (Jones et al., 1997) was used with the ChemScore (Eldridge et al., 1997; Verdonk et al., 2003) fitness function to generate 10 solutions for each ligand, and the dockings were ranked according to the value of the ChemScore fitness function; only the best ranked solution for each ligand was included in further analysis. Dockings were performed into the two available crystal structures of ligand-free CYP3A4 [Protein Data Bank (Berman et al., 2000) accession codes 1w0e (Williams et al., 2004) and 1tqn (Yano et al., 2004)]. The two structures are closely similar with the exception of the region of SRS2 (Gotoh, 1992), where the side chain of Arg-212 is oriented either toward (1tqn) or away from (1w0e) the heme iron. To assess the utility of our approach over the use of relatively fast and simple ligand-based descriptors, we determined the Slog P value, number of hydrogen bond donors, number of hydrogen bond acceptors, and molecular weight using MOE (Chemical Computing Group, Montreal, QC, Canada).

Chemicals. The test compounds 5,5-diphenylhydantoin, allopurinol, amitriptyline, aspirin, atenolol, caffeine, cefuroxime, citalopram, dexamethasone, diclofenac, diltiazem, domperidone, fluoxetine, frusemide, gabapentin, glucosamine, ibuprofen, lansoprazole, loperamide, lorazepam, metformin, metoclopramide, metronidazole, omeprazole, ondansetron, oxazepam, paracetamol, prednisolone, ranitidine, simvastatin, theophylline, and R-warfarin were purchased from Sigma-Aldrich (Dorset, UK). Tramadol hydrochloride was purchased from Fluka BioChemika (Poole, UK). BFC was obtained from Ultrafine Chemicals (Manchester, UK). All other reagents used were of the highest available quality.

Mutagenesis and Coexpression of the P450s and P450 Reductase in Escherichia coli. The isolation of the cDNAs and construction of expression plasmids ompA CYP3A4(His₆) (pB84) and pJR7 [human NADPH cytochrome P450 oxidoreductase (CPR)] have been described elsewhere (Pritchard et al., 1997). Site-directed mutagenesis was performed using the single-stranded DNA template method (Kunkel et al., 1987), using pB84 as a template, the dut^– ung^– E. coli strain CJ236, and the oligonucleotide 5'-TTTGCAGACCCTCCTAAGTCTCATAGC-3' for E374Q. The presence of the desired mutations was confirmed by DNA sequencing. Coexpression of wild-type CYP3A4 or the E374Q mutant with CPR was carried out as previously described (Pritchard et al., 1997; Smith et al., 1998; Paine et al., 2003; Flanagan et al., 2004), where wild-type CYP3A4 and E374Q gave average yields of 250 and 150 nmol P450/l bacterial culture, respectively. CPR activity was estimated by NADPH-dependent cytochrome c reduction (Strobel and Dignam, 1978).

Single-Point Screen and IC₅₀ Determinations. Assays were performed in 96-well microtiter plates using the fluorogenic substrate BFC in a final volume of 200 µl. Compounds dissolved in methanol or H₂O (Table 1) were added to a final volume of 100 µl of 2x enzyme/substrate stock solution (0.1 pmol/µl P450 in 50 µM Hepes and 30 mM MgCl₂, pH 7.4, with 50 µM BFC). A solvent control was included to correct for any solvent effects across the dilution range. Plates were then preincubated for 3 min at 37°C, and the enzyme reaction was initiated by the addition of a 100-µl aliquot of prewarmed 2x NADPH-generating system (1.3 mM NADP⁺, 6.6 mM glucose 6-phosphate, 6.6 mM MgCl₂, and 0.8 U/ml glucose-6-phosphate dehydrogenase) in 50 mM Hepes buffer (pH 7.4)_. The reaction was maintained at 37°C, and production of the fluorescent metabolite 7-hydroxytrifluoromethyl coumarin measured using a Fluoroskan Ascent FL microtiter plate reader (_ex = 405, _em = 530 nm; Labsystems, Cambridge, UK). For the single-point screen, the inhibition of BFC hydroxylation was measured using 50 µM substrate (close to the K_M of 51 µM measured for BFC) in the presence of 100 µM of each comedication compound as described below. Results of the screening were expressed as the percentage activity in the presence of 100 µM comedication compound compared with activity of the appropriate solvent control. Those comedication compounds that inhibited enzyme activity to <70% of control activity in duplicate experiments were evaluated further by measuring the percentage of inhibition across a concentration range covering 0 to 100% inhibition of CYP3A4 activity, and IC₅₀ values were calculated using GraFit 5.0.4 (Erithacus Software Ltd., Surrey, UK).

Loperamide Kinetics. The K_Ms of loperamide as a substrate for wild-type CYP3A4 and the E374Q mutant were determined by high-performance liquid chromatography-tandem mass spectrometry. Loperamide (0–100 µM) was incubated with 20 pmol CYP3A4 or the E374Q mutant in 10 mM Hepes buffer (pH 7.4) containing 6 mM MgCl₂, and reactions were initiated by the addition of a 2x NADPH-regenerating system in a total volume of 200 µl. After incubation for 8 min at 37°C, the reaction was stopped by the addition of 200 µl of ice-cold methanol. After centrifugation at 16,000g and 5 min to remove particulate material, 10 µl of the reaction supernatant was injected into the high-performance liquid chromatography-tandem mass spectrometry system (Micromass Quattro Micro mass spectrometer; Waters, Hertfordshire, UK). The analytes were separated on a Hyperclone BDS C₁₈ column (3 µm; 50 x 2.0 mm) at a flow rate of 0.2 ml/min. A linear gradient was applied using 10 mM ammonium formate and 0.1% (v/v) formic acid (A) and acetonitrile (B). The gradient of the mobile phase ran from 25 to 90% B in 5 min followed by 90% B for 3 min before returning to the initial conditions. The total run time was 13 min. The major MS parameters were capillary voltage = 3.6 kV, sample cone voltage = 25 V, collision energy = 23 eV, desolvation temperature = 350°C, source temperature = 120°C, and the transition for the N-demethylated product was 463 252 m/z.

	Results

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CYP3A4 Affinities of Comedication Drugs. The 33 comedication drugs used in this study are shown in Table 1. All these compounds could be successfully docked into the active site of CYP3A4, using either of the two available crystal structures of ligand-free CYP3A4 (Williams et al., 2004; Yano et al., 2004). These dockings yielded ChemScore values ranging from –41.0 to –10.1 kJ/mol (Table 1; note that the more negative the value, the tighter the predicted binding). The ChemScore value for loperamide (<–40 kJ/mol) suggests that it binds tightly to CYP3A4, and this was confirmed by its experimentally determined IC₅₀ value of 0.050 ± 0.006 µM. Encouraged by this success with loperamide, we investigated the ability of our other 32 comedication compounds to inhibit CYP3A4. First, a single-point inhibition assay revealed that 18 of the compounds in the set were at best very weak inhibitors (<30% inhibition at 100 µM), consistent with the relatively poor scores for these compounds in our docking studies (ChemScore values > –29 kJ/mol; Table 1). The remaining 15 compounds were selected for IC₅₀ determination (Table 1). The ChemScore values for these 15 "binders" correlate significantly with the experimental log(IC₅₀) values, with r² = 0.75 (q² = 0.73) for docking into the CYP3A4 crystal structure 1tqn and r² = 0.66 (q² = 0.64) for docking into the CYP3A4 structure 1w0e. The difference between the results for the two structures should be treated with some caution because only three outliers (citalopram, lansoprazole, and omeprazole) led to the slightly poorer regression with 1w0e.

In our previous work on CYP2D6, we defined "tight binders" as those compounds with a ChemScore of <–30 kJ/mol and an IC₅₀ value of <10 µM (Kemp et al., 2004). Although these values are somewhat arbitrary, applying the same criteria here reveals that five of the seven compounds with an IC₅₀ value of <10 µM—loperamide, domperidone, simvastatin, diltiazem, and amitriptyline—are correctly predicted, by docking into both crystal structures, as tight binders. The other two compounds with IC₅₀ value <10 µM—omeprazole and lansoprazole—are predicted correctly using the 1tqn, but not the 1w0e, structure. Conversely, all compounds with an IC₅₀ value >100 µM—metoclopramide, dexamethasone, lorazepam, R-warfarin, and prednisolone—are correctly predicted to be weaker binders. The three remaining compounds—fluoxetine, ondansetron, and citalopram—with IC₅₀ values in the "gray" area between 10 and 100 µM are all predicted by docking to be tight binders.

View larger version (36K): [in this window] [in a new window]   FIG. 1. Predicted binding mode of loperamide in the active site of CYP3A4. A and B, different views of loperamide docked into crystal structure 1tqn (Yano et al., 2004), illustrating that this mode of binding is consistent with N-demethylation of the tertiary amide. To reflect the uncertainty in the position of Arg-212, its position in crystal structure 1w0e (Williams et al., 2004) is also illustrated (light gray for carbon and blue for nitrogen). Predicted hydrogen bonds are shown as dashed lines [generated using PyMol (DeLano, 2002)]. C, chemical structure of loperamide; the arrow depicts the major (N-demethylated) metabolite.

To confirm the predicted role of Glu-374 in loperamide binding, mutagenesis experiments were performed. When this negatively charged amino acid was replaced by the polar (uncharged) glutamine, the mutant produced an approximate 50% reduction in the yield of P450. We also noted a 3-fold increase in P420 content in the membranes relative to wild type, suggestive of some protein misfolding. We determined a K_M for wild-type CYP3A4 of 2.6 ± 0.3 µM for the production of the N-demethylated product, slightly lower than the value of 6.3 µM reported by Kim et al. (2004). The E374Q mutation has a significant effect on loperamide binding for N-demethylation, with a 12-fold increase in K_M to 31.4 ± 1.9 µM (i.e., weaker binding). These results indicate a functional role for Glu-374 in the binding of loperamide to CYP3A4 and that our in silico study has correctly identified a significant ligand binding interaction.

	Discussion

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In this study, we have shown that in silico screening, using GOLD with the ChemScore scoring function, allows rapid identification of compounds which bind tightly to CYP3A4. The use of two independently solved crystal structures of CYP3A4 leads to similar predictions (Table 1). The in silico screening correlates well with a single point in vitro experimental screen in identifying which compounds bind to CYP3A4 (Table 1). In addition, it identifies correctly most (seven of seven using structure 1tqn and five of seven using structure 1w0e) of the tightly binding (IC₅₀ < 10 µM) compounds in our comedication set. All the compounds predicted to bind weakly (ChemScore >–30 kJ/mol) are found experimentally to have IC₅₀ > 100 mM. The three compounds that are "false positives" ("best" ChemScore < –30 kJ/mol and IC₅₀ > 10 µM) all have IC₅₀ values in the "gray" area ranging from 10 to 100 µM. Significant correlation between theoretical and experimental binding affinities is observed, slightly better when using structure 1tqn (r² = 0.75; q² = 0.73) than structure 1w0e (r² = 0.66; q² = 0.64). This difference might seem surprising because in structure 1tqn, the side chain of Arg-212 occupies a position in the binding site above the heme, whereas in structure 1w0e, it is reoriented away from the binding site. The impact of Arg-212 on substrate binding and catalysis by CYP3A4 remains unclear (Harlow and Halpert, 1997; Yano et al., 2004), and we are currently investigating this further. The results we report here suggest that in many cases, the choice of CYP3A4 crystal structure is not a crucial factor; however, in most cases where there is a difference in the predicted ChemScore value between the two structures, the compounds are predicted to bind more tightly to structure 1tqn (Table 1).

The usefulness of relatively fast and simple ligand-based descriptors was investigated. The active site of CYP3A4 is generally regarded as large and hydrophobic, as borne out by a predominantly hydrophobic active site in the crystal structures (Williams et al., 2004; Yano et al., 2004). Therefore, a "null hypothesis" for ligands binding to CYP3A4 is that ligand binding in the active site of CYP3A4 is due to hydrophobic interactions (Smith et al., 1997). Setting a threshold Slog P value of 2.5 to define tight binders, we were able to correctly identify six of the seven tight bingers (IC₅₀ < 10 µM using BFC as a probe substrate). Although this simple filter worked well qualitatively, it performed badly quantitatively (r² = 0.37, q² = 0.32 versus log IC₅₀), suggesting (as expected) that additional factors over and above hydrophobicity come into play in the selectivity exhibited by 3A4. Using molecular weight (r² = 0.22, q² = 0.0.16 versus log IC₅₀), number of hydrogen bond acceptors (r² = 0.01, q² = 0.07 versus log IC₅₀), and number of hydrogen bond donors (r² = 0.06, q² = 0.02 versus log IC₅₀) as descriptors also resulted in poor quantitative results.

In this work, we have used a structure-based in silico screening approach [with a program consistently found to perform well (see Kellenberger et al., 2004; Kontoyianni et al., 2004)] in which the structure of the protein remains rigid and a single compound (ligand) is docked at a time. Such an approach might be considered inappropriate for CYP3A4 because of its relatively large active site (Yano et al., 2004), the high degree of flexibility within the active site (Anzenbacherova et al., 2000; Anzenbacher and Hudecek, 2001), and the ability of the enzyme to bind multiple ligands simultaneously (Kenworthy et al., 2001; Khan et al., 2002). Despite these concerns, the approach worked well with this set of comedication compounds, showing that screening for likely drug-drug interactions is possible using a simple approach without the need for the additional computational overhead and complexity incurred when protein flexibility is invoked.

We predicted (ChemScore –45.0 kJ/mol), and subsequently verified experimentally (IC₅₀ 0.05 µM), that the antidiarrheal drug loperamide binds tightly to CYP3A4, consistent with the observation that loperamide probably interacts with CYP3A4 (Tayrouz et al., 2001). In addition, the binding orientation predicted by our computational docking is consistent with the production of the major, N-demethylated, metabolite. Soon after we completed this aspect of the work, and consistent with our findings, the major enzymes responsible for the metabolism of loperamide in humans were identified as CYP3A4, CYP2C8, and CYP2B6, the major product of its metabolism by CYP3A4 being the N-demethylated compound (Kalgutkar and Nguyen, 2004; Kim et al., 2004).

A number of comedication drugs have been identified in this work as inhibitors of CYP3A4. Clearly, the most important factor in determining the likelihood of a cytochrome P450-mediated drug-drug interaction is the concentration of a compound to which the P450 enzyme is exposed relative to its inhibitory potency (Ito et al., 2004). It should be noted that the concentration in vivo of a compound is confounded both by intestinal presystemic metabolism by CYP3A4 and by the activity of efflux transporters in the intestine. In the case of loperamide, there appears to be potential to cause clinical problems because the therapeutic levels (C_max) of loperamide [0.04 µM (Kim et al., 2004)] are close to the IC₅₀ value of 0.05 µM. Indeed, coadministration of loperamide has been shown to reduce exposure to the human immunodeficiency virus protease inhibitor saquinavir (Mikus et al., 2004), which is a CYP3A4 substrate (Eagling et al., 2002). Irinotecan (CPT-11), used as a treatment for colorectal cancer, is converted by carboxylesterases to a potent inhibitor of topoisomerase I. Dose-limiting diarrhea during irinotecan treatment is commonly treated with loperamide—but irinotecan is a known substrate of CYP3A4 (Haaz et al, 1998a,b), and its metabolism has been shown to be inhibited by loperamide (Haaz et al., 1998a,b)—raising the possibility of significant drug-drug interactions, although the quantitative importance of this remains to be established. In a similar way, the evidence for potent CYP3A4 inhibition by loperamide raises the possibility of interactions with docetaxel, cyclophosphamide and a number of other cytotoxics that can cause troublesome diarrhea. Several other drugs are highlighted by this study with low IC₅₀ values (<10 µM; i.e., tight binders), including simvastatin, an HMG-CoA reductase inhibitor which is the agent most commonly prescribed in the UK for hypercholesterolemia, and omeprazole, a gastroprotectant often given to patients on steroids.

To summarize, we have shown that a relatively "simple" in silico method can be used to predict whether drugs commonly taken by patients with cancer as part of a comedication regime interact with CYP3A4. As validated by our subsequent experimental binding studies, which determined a self-consistent set of IC₅₀ values, six of seven tight binding compounds were identified correctly, and all the compounds predicted to be weak binders or nonbinders to CYP3A4 were correctly identified. The antidiarrheal drug loperamide was identified as a particularly tight binder to CYP3A4 and thus warrants attention for possible involvement in drug-drug interactions. Although detailed pharmacokinetic studies will always be required to assess the quantitative importance of such interactions, the work described here demonstrates that our in silico approach is a valuable screen for identification of comedication compounds that may present problems. There are alternatives to many of the agents we identified as having the potential to cause significant, troublesome interactions with anticancer agents. Knowledge of these interactions may lead to more personalized and more appropriate prescribing by oncologists.

	Footnotes

 
This work was supported by Cancer Research UK, the University of Manchester, and the Higher Education Reach-Out to Business and the Community Fund (HEROBC).

Article, publication date, and citation information can be found at http://dmd.aspetjournals.org.

doi:10.1124/dmd.105.007625.

ABBREVIATIONS: P450, cytochrome P450; CPR, cytochrome P450 oxidoreductase; BFC, 7-benzyloxy-4-trifluoromethylcoumarin; SRS, substrate recognition site.

Address correspondence to: Professor Michael J. Sutcliffe, School of Chemical Engineering and Analytical Science, University of Manchester, The Mill, PO Box 88, Manchester, M60 1QD, UK. E-mail: michael.sutcliffe{at}manchester.ac.uk

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