Metabolism, Pharmacogenetics, and Metabolic Drug–Drug Interactions of Antipsychotic Drugs

1. Antipsychotic drugs are extensively metabolised by cytochrome P450 (CYP) enzymes.2. Dispositions of a number of antipsychotic drugs have been shown to cosegregate with polymorphism of CYP2D6.3. Metabolic drug–drug interactions have frequently been observed when antipsychotics are coadministered with other drugs.4. Many antipsychotic drugs are converted to active metabolites which can contribute to the therapeutic or side effects of the parent drug.5. Information concerning the individual CYP isoenzymes involved in the metabolism of antipsychotic drugs is important for the safe clinical use of this group of drugs.     

The formation of carbamazepine epoxide by rat liver microsomes: an investigation of the biphasic kinetic profile

A biphasic profile has been found for the rat hepatic microsomal formation of carbamazepine 10, 11 -epoxide from varying concentrations of carbamazepine (CBZ). The two optima for epoxide formation appeared at substrate concentrations of about 0.3 mM and 1.0 mM CBZ, respectively, with a nadir occuring at 0.4 – 0.6 mM CBZ. The biphasic nature of the velocity-substrate profile was not due to metabolism or disappearance of the epoxide. Pretreatment of rats with phenobarbital or CBZ produced an increase in the epoxide formation at both low and high CBZ concentrations, whereas phenytoin (DPH) pretreatment increased epoxide only at low CBZ concentrations. 3-Methylcholanthrene treatment did not increase epoxide formation at either low or high CBZ concentrations. High and low affinity processes for epoxide formation developed in parallel in young rats. DPH added $\text{in}$$\text{vitro}$ inhibited only the epoxide formation at high CBZ concentrations. This inhibitory effect increased with age of the rats. These findings indicate that CBZ 10, 11 -epoxide formation in rat liver microsomes proceeds by two metabolic pathways distinguished by substrate affinity and inhibition. Analysis of data from previous clinical studies reveals a biphasic pattern for plasma levels of CBZ, and its 10, 11 -epoxide.     

Direct interaction between substrates and endogenous steroids in the active site may change the activity of cytochrome P450 3A4

CYP3A4 exhibits unusual kinetic characteristics that result from the metabolism of multiple substrate including endogenous steroids and some drugs that coexist at the active site. To clarify the mechanism of the effect of endogenous steroids on the drug metabolism, the interaction between substrates, nevirapine (NVP) and carbamazepine (CBZ), and endogenous steroids was investigated by theoretical calculations. When the activities of NVP 2-hydroxylation and CBZ 10,11-epoxidation by expressed CYP3A4 were measured in the presence of steroids, NVP 2-hydroxylation was found to be remarkably increased by aldosterone and inhibited by estradiol. CBZ 10,11-epoxidation was increased by androstenedione. Three-dimensional computer modeling has shown that the active site of CYP3A4 is especially large, permitting access of two substrate molecules. The interactions between NVP and aldosterone and between CBZ and androstenedione were estimated by theoretical calculations assuming the substrate and steroids to be present in the active site at the same time. It was shown that NVP or CBZ would be stably fixed close to the oxygen atom at the sixth ligand of heme by interaction with steroids, suggesting that NVP and CBZ may be hydroxylated more easily due to the interaction with steroids. Estradiol was also expected to interact with NVP via a pi/pi interaction between a benzene ring, in which the NVP hydroxylation site is located, and a benzene ring of estradiol, suggested to inhibit the reaction. From these results, interactions between the substrate and endogenous steroids in the active site may change the activity of CYP3A4.     

Machine learning-driven identification of drugs inhibiting cytochrome P450 2C9

Cytochrome P450 2C9 (CYP2C9) is a major drug-metabolizing enzyme that represents 20% of the hepatic CYPs and is responsible for the metabolism of 15% of drugs. A general concern in drug discovery is to avoid the inhibition of CYP leading to toxic drug accumulation and adverse drug–drug interactions. However, the prediction of CYP inhibition remains challenging due to its complexity. We developed an original machine learning approach for the prediction of drug-like molecules inhibiting CYP2C9. We created new predictive models by integrating CYP2C9 protein structure and dynamics knowledge, an original selection of physicochemical properties of CYP2C9 inhibitors, and machine learning modeling. We tested the machine learning models on publicly available data and demonstrated that our models successfully predicted CYP2C9 inhibitors with an accuracy, sensitivity and specificity of approximately 80%. We experimentally validated the developed approach and provided the first identification of the drugs vatalanib, piriqualone, ticagrelor and cloperidone as strong inhibitors of CYP2C9 with IC values <18 μM and sertindole, asapiprant, duvelisib and dasatinib as moderate inhibitors with IC50 values between 40 and 85 μM. Vatalanib was identified as the strongest inhibitor with an IC50 value of 0.067 μM. Metabolism assays allowed the characterization of specific metabolites of abemaciclib, cloperidone, vatalanib and tarafenacin produced by CYP2C9. The obtained results demonstrate that such a strategy could improve the prediction of drug-drug interactions in clinical practice and could be utilized to prioritize drug candidates in drug discovery pipelines.     

Metabolism of carbamazepine by CYP3A6: a model for in vitro drug interactions studies

Carbamazepine (CBZ) is widely used in the treatment of epilepsy. The drug is principally metabolized by CYPs to 10, 11-epoxy carbamazepine (CBZ-E) but this metabolite more toxic than the parent drug, does possess anticonvulsant properties. In humans, CYP3A4, CYP2C8 and CYP1A2 have been shown to be implicated in CBZ biotransformation. Our purpose was to establish an experimental model to determine the interaction of CBZ with other antiepileptic drugs. We first identified the CYP isoforms that metabolized CBZ in rabbit. We used liver microsomes from rabbit treated with various compounds known to induce principally some CYPs subfamilies. Having tested all the compounds we demonstrated that only the animals treated with CYP3A inducers were able to metabolize CBZ strongly. The CBZ biotransformation was inhibited by anti CYP3A antibodies. All the CYP3A subfamily substrates specifically decrease CBZ-E formation. In our experiment we did not observe any inhibition with CYP2C substrate. These data provide evidence that in rabbit the CYP3A subfamily is primarily involved in CBZ metabolism. Using this model we investigated the interaction of CBZ with phenobarbital, phenytoin, ethosuccimide, primidone, progabide, vigabatrin and lamotrigine.     

Effects of anticonvulsants and gamma-aminobutyric acid (GABA)-mimetic drugs on immunoreactive somatostatin and GABA contents in the rat brain

Immunoreactive somatostatin (IR-SRIF) and gamma-aminobutyric acid (GABA) contents in the rat brain were investigated to study chronic effects of the treatment with anticonvulsants, carbamazepine (CBZ), valproic acid (VPA) and phenytoin (PHT). Decreased IR-SRIF levels were found in several brain regions after chronic treatment with VPA and CBZ. GABA concentrations were found to be increased significantly in chronic CBZ and VPA treatment in the rat brain, especially in limbic structures. PHT had no effect on both IR-SRIF and GABA contents in the rat brain. Effects of several GABA-mimetic drugs also were studied on IR-SRIF contents in the rat brain. Aminooxyacetic acid an inhibitor of GABA transaminase, induced a decrease in IR-SRIF concentration in the pyriform and entorhinal cortex, whereas ethanolamine-o-sulfate, another GABA-transaminase inhibitor and muscimol, a GABA receptor agonist had no effect on brain IR-SRIF after acute administration. The present results suggest that endogenous somatostatin has an important role for anticonvulsant properties of CBZ and VPA, but not of PHT. The relationship between the changes in IR-SRIF and the GABA transmitter system in the anticonvulsant action of CBZ and VPA remains to be clarified.     

Metabolism and Pharmacokinetics of Selective Serotonin Reuptake Inhibitors

1. Five drugs with the predominant pharmacologic effect of inhibiting the neuronal reuptake of serotonin are available worldwide for clinical use. This class of psychoactive drugs, known as selective serotonin reuptake inhibitors (SSRIs), is comprised of fluoxetine, sertraline, paroxetine, fluvoxamine, and citalopram.2. The SSRIs appear to share similar pharmacodynamic properties which translate to efficacy in the treatment of depression and anxiety syndromes. The drugs are differentiated by their pharmacokinetic properties with regard to stereochemistry, metabolism, inhibition of cytochrome enzymes, and participation in drug–drug interactions. Studies focusing on the relationship of plasma drug concentration to therapeutic and adverse effects have not confirmed the value of plasma concentration monitoring.3. This review summarizes the metabolism and relevant pharmacokinetic properties of the SSRIs.     

Metabolism of Anxiolytics and Hypnotics: Benzodiazepines, Buspirone, Zoplicone, and Zolpidem

1. The benzodiazepines are among the most frequently prescribed of all drugs and have been used for their anxiolytic, anticonvulsant, and sedative/hypnotic properties. Since absorption rates, volumes of distribution, and elimination rates differ greatly among the benzodiazepine derivatives, each benzodiazepine has a unique plasma concentration curve. Although the time to peak plasma levels provides a rough guide, it is not equivalent to the time to clinical onset of effect. The importance of and half-lives in the actions of benzodiazepines is discussed.2. The role of cytochrome P450 isozymes in the metabolism of benzodiazepines and in potential pharmacokinetic interactions between the benzodiazepines and other coadministered drugs is discussed.3. Buspirone, an anxiolytic with minimal sedative effects, undergoes extensive metabolism, with hydroxylation and dealkylation being the major pathways. Pharmacokinetic interactions of buspirone with other coadministered drugs seem to be minimal.4. Zopiclone and zolpidem are used primarily as hypnotics. Both are extensively metabolized; N-demethylation, N-oxidation, and decarboxylation of zopiclone occur, and zolpidem undergoes oxidation of methyl groups and hydroxylation of a position on the imidazolepyridine ring system. Zopiclone has a chiral centre, and demonstrates stereoselective pharmacokinetics. Metabolic drug–drug interactions have been reported with zopiclone and erythromycin, trimipramine, and carbamazepine. Reports to date indicate minimal interactions of zolpidem with coadministered drugs; however, it has been reported to affect the C _max and clearance of chlorpromazepine and to decrease metabolism of the antiviral agent ritonavin. Since CYP3A4 has been reported to play an important role in metabolism of zolpidem, possible interactions with drugs which are substrates and/or inhibitors of that CYP isozyme should be considered.     

Metabolism of Some “Second”– and “Fourth”–Generation Antidepressants: Iprindole, Viloxazine, Bupropion, Mianserin, Maprotiline, Trazodone, Nefazodone, and Venlafaxine

1. This review summarizes the major known aspects of the metabolism of second-generation (iprindole, viloxazine, bupropion, mianserin, maprotiline, and trazodone) and fourth-generation (nefazodone and venlafaxine) antidepressants.2. Discussions about specific enzymes involved and about possible pharmacokinetic drug–drug interactions, particularly as they relate to cytochrome P450 enzymes, are provided.     

Clinical Validation and Implications of Dried Blood Spot Sampling of Carbamazepine,Valproic Acid and Phenytoin in Patients with Epilepsy

To facilitate therapeutic monitoring of antiepileptic drugs (AEDs) by healthcare professionals for patients with epilepsy (PWE), we applied a GC-MS assay to measure three AEDs: carbamazepine (CBZ), phenytoin (PHT) and valproic acid (VPA) levels concurrently in one dried blood spot (DBS), and validated the DBS-measured levels to their plasma levels. 169 PWE on either mono- or polytherapy of CBZ, PHT or/and VPA were included. One DBS, containing ∼15 µL of blood, was acquired for the simultaneous measurement of the drug levels using GC-MS. Simple Deming regressions were performed to correlate the DBS levels with the plasma levels determined by the conventional immunoturbimetric assay in clinical practice. Statistical analyses of the results were done using MedCalc Version 12.6.1.0 and SPSS 21. DBS concentrations (C_dbs) were well-correlated to the plasma concentrations (C_plasma): r = 0.8381, 0.9305 and 0.8531 for CBZ, PHT and VPA respectively, The conversion formulas from C_dbs to plasma concentrations were [0.89×C_dbsCBZ+1.00]µg/mL, [1.11×C_dbsPHT−1.00]µg/mL and [0.92×C_dbsVPA+12.48]µg/mL respectively. Inclusion of the red blood cells (RBC)/plasma partition ratio (K) and the individual hematocrit levels in the estimation of the theoretical C_plasma from C_dbs of PHT and VPA further improved the identity between the observed and the estimated theoretical C_plasma. Bland-Altman plots indicated that the theoretical and observed C_plasma of PHT and VPA agreed well, and >93.0% of concentrations was within 95% CI (±2SD); and similar agreement (1∶1) was also found between the observed C_dbs and C_plasma of CBZ. As the C_plasma of CBZ, PHT and VPA can be accurately estimated from their C_dbs, DBS can therefore be used for drug monitoring in PWE on any of these AEDs.     

The use of transgenic cell lines for evaluating toxic metabolites of carbamazepine

Human lymphoblastoid cell lines transgenic for human CYP450s were evaluated for the identification of toxic metabolites of the anticonvulsant drug carbamazepine (CBZ). Human CYP450 isoforms expressed by these cell lines included 1A1, 1A2, 2E1, 2A6 and 3A4. A dose-dependent inhibition of population growth from 50–200 g/ml CBZ was detected by measuring cell number and respiration. The inhibition increased with the growth rate of the various lines, which correlated inversely with the presence of CYP450s, and may have been caused by CBZ itself. Cytotoxicity was observed only at the highest dose and in the line lacking transfected CYP450s. Microsomal preparations from hCYP3A4/OR cells converted CBZ into its principal oxidative metabolite, carbamazepine-10,11-epoxide (CBZ-E), at a rate of 630 pmol/min per mg protein, confirming a major role of CYP3A4 in this reaction. However, no CBZ-E (or any metabolite) was recovered from any whole-cell incubation even though hCYP3A4 cells readily converted testosterone to 6ß-hydroxytestosterone. This suggests that differences exist between whole-cell and microsomal preparations of lymphoblastoid cells in their ability to metabolize CBZ.Abbreviations BSTFA N,O-bis(trimethylsilyl)trifluoroacetamide - CBZ carbamazepine - CBZ-E carbamazepine-10, 11-epoxide - CYP450 cytochrome P450 - CYP3A4 cytochrome P450, isoform 3A4 - DMSO dimethyl sulfoxide - GC-MS gas chromatography-mass spectrometry - HPLC high-performance liquid chromatography - MTT (3-[4,5-dimethylthiazol-2-y1]-2,5-diphenyl)tetrazolium - SIM selected-ion monitoring - TMS trimethylsilyl     

An epoxidation mechanism of carbamazepine by CYP3A4

Human CYP3A4 catalyzes the 10,11-epoxidation of carbamazepine (CBZ). However, the epoxide is less stable in terms of potential energy than hydroxides of the six-membered aromatic ring. To clarify the reason why CYP3A4 produces such an energetically unfavorable compound, the mechanism of epoxidation of CBZ by CYP3A4 was investigated by theoretical calculations. The reaction consisted of two elementary processes in which two C–O bonds were generated stepwise. The rate-determining step was the first one and the activation energy was 21.3 kcal/mol at the DFT (B3LYP/6-31G^**) level. The activation energy level of the first step of the 10,11-epoxidation was lower than that of the hydroxylation of the aromatic ring. For this reason, 10,11-epoxidation is more probable than hydroxylation of the aromatic ring, and only 10,11-epoxide is formed.     

Structural Characterization of CYP51 from Trypanosoma cruzi and Trypanosoma brucei Bound to the Antifungal Drugs Posaconazole and Fluconazole

Background

Chagas Disease is the leading cause of heart failure in Latin America. Current drug therapy is limited by issues of both efficacy and severe side effects. Trypansoma cruzi, the protozoan agent of Chagas Disease, is closely related to two other major global pathogens, Leishmania spp., responsible for leishmaniasis, and Trypansoma brucei, the causative agent of African Sleeping Sickness. Both T. cruzi and Leishmania parasites have an essential requirement for ergosterol, and are thus vulnerable to inhibitors of sterol 14α-demethylase (CYP51), which catalyzes the conversion of lanosterol to ergosterol. Clinically employed anti-fungal azoles inhibit ergosterol biosynthesis in fungi, and specific azoles are also effective against both Trypanosoma and Leishmania parasites. However, modification of azoles to enhance efficacy and circumvent potential drug resistance has been problematic for both parasitic and fungal infections due to the lack of structural insights into drug binding.

Methodology/Principal Findings

We have determined the crystal structures for CYP51 from T. cruzi (resolutions of 2.35 Å and 2.27 Å), and from the related pathogen T. brucei (resolutions of 2.7 Å and 2.6 Å), co-crystallized with the antifungal drugs fluconazole and posaconazole. Remarkably, both drugs adopt multiple conformations when binding the target. The fluconazole 2,4-difluorophenyl ring flips 180° depending on the H-bonding interactions with the BC-loop. The terminus of the long functional tail group of posaconazole is bound loosely in the mouth of the hydrophobic substrate binding tunnel, suggesting that the major contribution of the tail to drug efficacy is for pharmacokinetics rather than in interactions with the target.

Conclusions/Significance

The structures provide new insights into binding of azoles to CYP51 and mechanisms of potential drug resistance. Our studies define in structural detail the CYP51 therapeutic target in T. cruzi, and offer a starting point for rationally designed anti-Chagasic drugs with improved efficacy and reduced toxicity.     

Combination of docking,molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone

In modern drug discovery process, ADME/Tox properties should be determined as early as possible in the test cascade to allow a timely assessment of their property profiles. To help medicinal chemists in designing new compounds with improved pharmacokinetics, the knowledge of the soft spot position or the site of metabolism (SOM) is needed. In silico methods based on docking, molecular dynamics and quantum chemical calculations can bring us closer to understand drug metabolism and predict drug–drug interactions. We report herein on a combined methodology to explore the site of metabolism prediction of a new cardioactive drug prototype, LASSBio-294 (1), using MetaPrint2D to predict the most likely metabolites, combined with structure-based tools using docking, molecular dynamics and quantum mechanical calculations to predict the binding of the substrate to CYP2C9 enzyme, to estimate the binding free energy and to study the energy profiles for the oxidation of (1). Additionally, the computational study was correlated with a metabolic fingerprint profiling using LC-MS analysis. The results obtained using the computational methods gave valuable information about the probable metabolites of (1) (qualitatively) and also about the important interactions of this lead compound with the amino acid residues of the active site of CYP2C9. Moreover, using a combination of different levels of theory sheds light on the understanding of (1) metabolism by CYP2C9 and its mechanisms. The metabolic fingerprint profiling of (1) has shown that the metabolites founded in highest concentration in different species were metabolites M1, M2 and M3, whereas M8 was found to be a minor metabolite. Therefore, our computational study allowed a qualitative prediction for the metabolism of (1). The approach presented here has afforded new opportunities to improve metabolite identification strategies, mediated by not only CYP2C9 but also other CYP450 family enzymes.     

Unravelling the complex drug–drug interactions of the cardiovascular drugs,verapamil and digoxin,with P-glycoprotein

Drug–drug interactions (DDIs) and associated toxicity from cardiovascular drugs represents a major problem for effective co-administration of cardiovascular therapeutics. A significant amount of drug toxicity from DDIs occurs because of drug interactions and multiple cardiovascular drug binding to the efflux transporter P-glycoprotein (Pgp), which is particularly problematic for cardiovascular drugs because of their relatively low therapeutic indexes. The calcium channel antagonist, verapamil and the cardiac glycoside, digoxin, exhibit DDIs with Pgp through non-competitive inhibition of digoxin transport, which leads to elevated digoxin plasma concentrations and digoxin toxicity. In the present study, verapamil-induced ATPase activation kinetics were biphasic implying at least two verapamil-binding sites on Pgp, whereas monophasic digoxin activation of Pgp-coupled ATPase kinetics suggested a single digoxin-binding site. Using intrinsic protein fluorescence and the saturation transfer double difference (STDD) NMR techniques to probe drug–Pgp interactions, verapamil was found to have little effect on digoxin–Pgp interactions at low concentrations of verapamil, which is consistent with simultaneous binding of the drugs and non-competitive inhibition. Higher concentrations of verapamil caused significant disruption of digoxin–Pgp interactions that suggested overlapping and competing drug-binding sites. These interactions correlated to drug-induced conformational changes deduced from acrylamide quenching of Pgp tryptophan fluorescence. Also, Pgp-coupled ATPase activity kinetics measured with a range of verapamil and digoxin concentrations fit well to a DDI model encompassing non-competitive and competitive inhibition of digoxin by verapamil. The results and previous transport studies were combined into a comprehensive model of verapamil–digoxin DDIs encompassing drug binding, ATP hydrolysis, transport and conformational changes.     

Polymorphic Variants of SCN1A and EPHX1 Influence Plasma Carbamazepine Concentration,Metabolism and Pharmacoresistance in a Population of Kosovar Albanian Epileptic Patients

Aim

The present study aimed to evaluate the effects of gene variants in key genes influencing pharmacokinetic and pharmacodynamic of carbamazepine (CBZ) on the response in patients with epilepsy.

Materials & Methods

Five SNPs in two candidate genes influencing CBZ transport and metabolism, namely ABCB1 or EPHX1, and CBZ response SCN1A (sodium channel) were genotyped in 145 epileptic patients treated with CBZ as monotherapy and 100 age and sex matched healthy controls. Plasma concentrations of CBZ, carbamazepine-10,11-epoxide (CBZE) and carbamazepine-10,11-trans dihydrodiol (CBZD) were determined by HPLC-UV-DAD and adjusted for CBZ dosage/kg of body weight.

Results

The presence of the SCN1A IVS5-91G>A variant allele is associated with increased epilepsy susceptibility. Furthermore, carriers of the SCN1A IVS5-91G>A variant or of EPHX1 c.337T>C variant presented significantly lower levels of plasma CBZ compared to carriers of the common alleles (0.71±0.28 vs 1.11±0.69 μg/mL per mg/Kg for SCN1A IVS5-91 AA vs GG and 0.76±0.16 vs 0.94±0.49 μg/mL per mg/Kg for EPHX1 c.337 CC vs TT; P<0.05 for both). Carriers of the EPHX1 c.416A>G showed a reduced microsomal epoxide hydrolase activity as reflected by a significantly decreased ratio of CBZD to CBZ (0.13±0.08 to 0.26±0.17, p<0.05) also of CBZD to CBZE (1.74±1.06 to 3.08±2.90; P<0.05) and CDR_CBZD (0.13±0.08 vs 0.24±0.19 μg/mL per mg/Kg; P<0.05). ABCB1 3455C>T SNP and SCN1A 3148A>G variants were not associated with significant changes in CBZ pharmacokinetic. Patients resistant to CBZ treatment showed increased dosage of CBZ (657±285 vs 489±231 mg/day; P<0.001) but also increased plasma levels of CBZ (9.84±4.37 vs 7.41±3.43 μg/mL; P<0.001) compared to patients responsive to CBZ treatment. CBZ resistance was not related to any of the SNPs investigated.

Conclusions

The SCN1A IVS5-91G>A SNP is associated with susceptibility to epilepsy. SNPs in EPHX1 gene are influencing CBZ metabolism and disposition. CBZ plasma levels are not an indicator of resistance to the therapy.     

Considerations and recommendations for assessment of plasma protein binding and drug–drug interactions for siRNA therapeutics

At the time of writing, although siRNA therapeutics are approved for human use, no official regulatory guidance specific to this modality is available. In the absence of guidance, preclinical development for siRNA followed a hybrid of the small molecule and biologics guidance documents. However, siRNA differs significantly from small molecules and protein-based biologics in its physicochemical, absorption, distribution, metabolism and excretion properties, and its mechanism of action. Consequently, certain reports typically included in filing packages for small molecule or biologics may benefit from adaption, or even omission, from an siRNA filing. In this white paper, members of the ‘siRNA working group’ in the IQ Consortium compile a list of reports included in approved siRNA filing packages and discuss the relevance of two in vitro reports—the plasma protein binding evaluation and the drug–drug interaction risk assessment—to support siRNA regulatory filings. Publicly available siRNA approval packages and the literature were systematically reviewed to examine the role of siRNA plasma protein binding and drug–drug interactions in understanding pharmacokinetic/pharmacodynamic relationships, safety and translation. The findings are summarized into two decision trees to help guide industry decide when in vitro siRNA plasma protein binding and drug–drug interaction studies are warranted.     

Effect of Ethanol on the Metabolic Characteristics of HIV-1 Integrase Inhibitor Elvitegravir and Elvitegravir/Cobicistat with CYP3A: An Analysis Using a Newly Developed LC-MS/MS Method

Elvitegravir (EVG), an integrase inhibitor for the treatment HIV infection, is increasingly becoming the part of first-line antiretroviral therapy (ART) regimen. EVG is mainly metabolized through cytochrome P450 (CYP) 3A4. Previously, we have shown that ethanol alters ART-CYP3A4 interactions with protease inhibitors thereby altering their metabolisms. However, as EVG is a fairly new class of drug, its kinetic characteristics and the effect of ethanol on EVG-CYPP3A4 interaction is poorly understood. In this study, we characterized EVG and cobicistat (COBI)-boosted EVG metabolism in human microsomes followed by ethanol-EVG, ethanol-COBI-EVG interaction with CYP3A. First, we developed and validated a simple, sensitive, and robust liquid chromatography–tandem mass spectrometry (LC-MS/MS) method for the quantification of EVG in the human liver microsomes. The lower limit of quantification for the drug was at 0.003 μM (1.34ng/ml). Extraction yield, matrix effects, drug stability, and calibration curves for the proposed method were validated according to the FDA guidelines. Time dependent kinetics data showed that 20mM ethanol decreases the apparent half-life of EVG degradation by ~50% compared to EVG alone. Our substrate kinetic results revealed that ethanol mildly decreases the catalytic efficiency for EVG metabolism. Inhibition studies demonstrated that EVG inhibits CYP3A4, and 20 mM ethanol causes a decrease in the IC₅₀ of EVG. However, in the presence of COBI we were unable to determine these parameters effectively because COBI, being a strong inhibitor of CYP3A4, blocked the EVG/ethanol-CYP3A4 interactions. Docking studies predicted a shift of EVG or COBI binding to the active site of CYP3A4 in the presence of ethanol. Taken together, these results suggest that ethanol interacts with microsomal CYP3A and alters EVG-CYP3A4 interaction thereby altering EVG metabolism and inhibition of CYP3A4 by EVG. This finding has clinical significance because alcohol use is highly prevalent in HIV population, and there are no separate guidelines for these patients while they are on ART medication.     

Prediction of sites of metabolism in a substrate molecule, instanced by carbamazepine oxidation by CYP3A4

In drug discovery process, improvement of ADME/Tox properties of lead compounds including metabolic stability is critically important. Cytochrome P450 (CYP) is one of the major metabolizing enzymes and the prediction of sites of metabolism (SOM) on the given lead compounds is key information to modify the compounds to be more stable against metabolism. There are two factors essentially important in SOM prediction. First is accessibility of each substrate atom to the oxygenated Fe atom of heme in a CYP protein, and the other is the oxidative reactivity of each substrate atom. To predict accessibility of substrate atoms to the heme iron, conventional protein-rigid docking simulations have been applied. However, the docking simulations without consideration of protein flexibility often lead to incorrect answers in the case of very flexible proteins such as CYP3A4. In this study, we demonstrated an approach utilizing molecular dynamics (MD) simulation for SOM prediction in which multiple MD runs were executed using different initial structures. We applied this strategy to CYP3A4 and carbamazepine (CBZ) complex. Through 10 ns MD simulations started from five different CYP3A4-CBZ complex models, our approach correctly predicted SOM observed in experiments. The experimentally known epoxidized sites of CBZ by CYP3A4 were successfully predicted as the most accessible sites to the heme iron that was judged from a numerical analysis of calculated ΔG(binding) and the frequency of appearance. In contrast, the predictions using protein-rigid docking methods hardly provided the correct SOM due to protein flexibility or inaccuracy of the scoring functions. Our strategy using MD simulation with multiple initial structures will be one of the reliable methods for SOM prediction.