Halogen Substitution Influences Ketamine Metabolism by Cytochrome P450 2B6: In Vitro and Computational Approaches

Article abstract of DOI:10.1021/acs.molpharmaceut.8b01214

Ketamine is analgesic at anesthetic and subanesthetic doses, and it has been used recently to treat depression. Biotransformation mediates ketamine effects, influencing both systemic elimination and bioactivation. CYP2B6 is the major catalyst of hepatic ketamine N-demethylation and metabolism at clinically relevant concentrations. Numerous CYP2B6 substrates contain halogens. CYP2B6 readily forms halogen-protein (particularly Cl-π) bonds, which influence substrate selectivity and active site orientation. Ketamine is chlorinated, but little is known about the metabolism of halogenated analogs. This investigation evaluated halogen substitution effects on CYP2B6-catalyzed ketamine analogs N-demethylation in vitro and modeled interactions with CYP2B6 using various computational approaches. Ortho phenyl ring halogen substituent changes caused substantial (18-fold) differences in K_m, on the order of Br (bromoketamine, 10 μM) < Cl < F < H (deschloroketamine, 184 μM). In contrast, V_max varied minimally (83-103 pmol/min/pmol CYP). Thus, apparent substrate binding affinity was the major consequence of halogen substitution and the major determinant of N-demethylation. Docking poses of ketamine and analogs were similar, sharing a π-stack with F297. Libdock scores were deschloroketamine < bromoketamine < ketamine < fluoroketamine. A Bayesian log K_m model generated with Assay Central had a ROC of 0.86. The probability of activity at 15 μM for ketamine and analogs was predicted with this model. Deschloroketamine scores corresponded to the experimental K_m, but the model was unable to predict activity with fluoroketamine. The binding pocket of CYP2B6 also suggested a hydrophobic component to substrate docking, on the basis of a strong linear correlation (R² = 0.92) between lipophilicity (AlogP) and metabolism (log K_m) of ketamine and analogs. This property may be the simplest design criteria to use when considering similar compounds and CYP2B6 affinity.

Full text of DOI:10.1021/acs.molpharmaceut.8b01214

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Article
Halogen Substitution Influences Ketamine Metabolism by
Cytochrome P450 2B6: In Vitro and Computational Approaches
Pan-Fen Wang, Alicia Neiner, Thomas R. Lane, Kimberly M. Zorn, Sean Ekins, and Evan D. Kharasch
Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.8b01214 • Publication Date (Web): 27 Dec 2018
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Halogen Substitution Influences Ketamine Metabolism by Cytochrome P450 2B6:
In Vitro and Computational Approaches
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Pan-Fen Wang1 Alicia Neiner,2 Thomas R. Lane,3 Kimberley M. Zorn,3 Sean Ekins3, Evan D. Kharasch1,*
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1Department of Anesthesiology, Duke University School of Medicine, Durham, NC
2Department of Anesthesiology, Washington University in St. Louis, St. Louis, MO
3Collaborations Pharmaceuticals, Inc., Main Campus Drive, Lab 3510, Raleigh, NC
panfen.wang@duke.edu, neinera@wustl.edu, evan.kharasch@duke.edu,
tom@collaborationspharma.com, kim@collaborationspharma.com, sean@collaborationspharma.com
Funding: Supported by National Institutes of Health grants R01DA14211, R43GM122196 and
R44GM122196, and by the Washington University in St. Louis Department of Anesthesiology Russel B
and Mary D Shelden fund
Word count:
Abbreviated Title: ketamine halogen analogs metabolism
Conflicts of interest: SE is an owner and SE, TRL and KMZ are employees of Collaborations
Pharmaceuticals, Inc. All other authors have no conflicts of interest.
*Address Correspondence to:
Dr. Evan Kharasch, Department of Anesthesiology, Duke University Box 3094, GSRB1 room 2031, 905
S. LaSalle St, Durham, NC 27710 Tel.: 919-613-1154, E-mail: evan.kharasch@duke.edu
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Ketamine is analgesic at anesthetic and subanesthetic doses, and used recently to treat depression.
Biotransformation mediates ketamine effects, influencing both systemic elimination and bioactivation.
CYP2B6 is the major catalyst of hepatic ketamine N-demethylation and metabolism at clinically relevant
concentrations. Numerous CYP2B6 substrates contain halogens. CYP2B6 readily forms halogen-protein
(particularly Cl-π) bonds, which influence substrate selectivity and active site orientation. Ketamine is
chlorinated, but little is known about metabolism of halogenated analogs. This investigation evaluated
halogen substitution effects on CYP2B6-catalyzed ketamine analogs N-demethylation in vitro, and
modeled interactions with CYP2B6 using various computational approaches. Ortho phenyl ring halogen
substituent changes caused substantial (18-fold) differences in Km, on the order Br (bromoketamine, 10
µM)< Cl <F <H (deschloroketamine, 184 µM). In contrast, Vmax varied minimally (83-103
pmol/min/pmol CYP). Thus apparent substrate binding affinity was the major consequence of halogen
substitution and the major determinant of N-demethylation. Docking poses of ketamine and analogs were
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similar,
sharing
a
π-stack
with
F297.
Libdock
scores
were
deschloroketamine<bromoketamine<ketamine<fluoroketamine. A Bayesian log Km model generated with
Assay Central had a ROC of 0.86. The probability of activity at 15µM for ketamine and analogs was
predicted with this model. Deschloroketamine scores corresponded to the experimental Km, but the model
was unable to predict activity with fluoroketamine. The binding pocket of CYP2B6 also suggested a
hydrophobic component to substrate docking, based on a strong linear correlation (R2=0.92) between
lipophilicity (AlogP) and metabolism (log Km) of ketamine and analogs. This property may be the
simplest design criteria to use when considering similar compounds and CYP2B6 affinity.
Keywords: ketamine, halogen, cytochrome P450, CYP2B6, substrate modeling
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Introduction
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Ketamine is a dissociative anesthetic, in clinical use since 1970, and is listed as a World Health
Organization Essential Medicine. Ketamine is analgesic at anesthetic and subanesthetic doses, and causes
hypnosis, amnesia and sedation with minimal respiratory system depression.1
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Ketamine was initially synthesized as
a derivative of phencyclidine (PCP, 1-(1-
phenylcyclohexyl)piperidine).2-4 Phencyclidine was developed in the 1950s by Parke Davis as a general
anesthetic,5 but was discontinued in 1965 due to undesirable side effects including hallucination and
neurotoxicity. A series of related arylcyclohexylamine compounds was synthesized in the search for a
safer alternative.3, 4 One of the compounds, 2-(2-chlorophenyl)-2-(methylamino)cyclohexan-1-one, was
an excellent anesthetic (scheme 1). It was named ketamine for its two functional groups (ketone and
amine). Ketamine has three structural differences compared to phencyclidine: the piperidino changed to a
methylamino group, the introduction of a ketone on the cyclohexyl ring, and chlorine addition to the
phenyl ring. Ketamine binds to the activated open ion channel of the N-methyl-D-aspartate receptor
(NMDAR), causing uncompetitive blockade.6 Therapeutic applications for ketamine have recently
expanded, to include severe and treatment-resistant major depression, with rapid and sustained response.7-
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Biotransformation plays a seminal role in the clinical effects of ketamine, influencing both
systemic elimination and bioactivation. Ketamine undergoes extensive hepatic N-demethylation to the
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predominant metabolite norketamine.1,
Norketamine and the other primary metabolite
hydroxyketamine are both further metabolized by hydroxylation and N-demethylation, respectively, to
hydroxynorketamine. Norketamine is also further metabolized to dehydronorketamine. Drug interactions
which alter hepatic ketamine metabolism greatly influence systemic ketamine concentrations.12-14 Oral
ketamine undergoes considerable first-pass metabolism, and is consequently only 15% bioavailable.1
Metabolism also influences the molecular pharmacology of ketamine.
Norketamine and
hydroxynorketamine are pharmacologically active and may contribute to the antidepressant and/or
analgesic effects of ketamine, possibly through NMDA or α-amino-3-hydroxy-5-methyl-4-isoxazole
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propionic acid (AMPA) receptors.15-18 Ketamine N-demethylation is catalyzed by both CYP2B6 and
CYP3A4, however these are high-affinity (low Km) and low-affinity (high Km) isoforms, respectively,
and CYP2B6 is the major catalyst in vitro of hepatic ketamine N-demethylation, norketamine
hydroxylation, and ketamine metabolism overall, at clinically relevant concentrations,19-24 as well as
clinically.13 Ketamine N-demethylation by CYP2B6 is also the first step in bioactivation to a putative
active metabolite, hydroxynorketamine.25
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Halogen substitution is strategically used in drug design and development, typically to improve
drug-target binding affinity and/or selectivity, as well as decrease metabolism.26, 27 The most common
organohalogen amongst marketed drugs is chlorine, because heavy organohalogens form hydrogen bonds
while organofluorines generally do not. Nevertheless, a recent survey found that in addition to
influencing receptor pharmacology, 19% of halogen-protein interactions involved those mediating
absorption, distribution, metabolism, and excretion, including P450-catalyzed metabolism and
detoxification.27 Indeed, halogenation was suggested as an underused strategy for tuning metabolism and
molecular optimization,27 particularly exploiting halogen-π interactions between ligand and protein.28
Because numerous CYP2B6 substrates contain halogens, and this enzyme readily forms halogen-protein
(particularly Cl-π) bonds,29 the role of halogen-π bonds in substrate selectivity and active site orientation
interactions was recently investigated, using the halogenated monoterpene bornyl bromide and the
nonhalogenated analog bornane. These results suggested that such interactions may be unique to the
CYP2B family of enzymes within the CYP2 family.28
The availability of halogenated and non-halogenated ketamine analogs (Scheme 2) afforded the
opportunity to investigate further the influence of halogen substitution on CYP2B6-catalyzed metabolism.
The purpose of the current investigation was to directly evaluate halogen substitution effects on ketamine
N-demethylation catalyzed by CYP2B6, and attempt to predict the interaction of these variously
halogenated analogs with CYP2B6 using various computational approaches.
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Materials and Methods
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Materials
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Formaldehyde, acetylacetone and S-ketamine were purchased from Sigma-Aldrich (St Louis,
MO). R-ketamine was purchased from Cayman Chemical (Ann Arbor, MI). Racemic RS-ketamine was
from Spectrum Chemical Corp (New Brunswick, NJ). Norketamine (d0 and d4) were from Cerilliant
(Round Rock, TX). Spodoptera frugiperda (Sf9) cells and Sf-900 III SFM culture media were purchased
from ThermoFisher (Waltham, MA). Trichoplusia ni (Tni) cells, ESF AF culture media, and BestBac 2.0
Baculovirus Cotransfection Kits were from Expression Systems (Davis, CA). BacPAK Baculovirus
Rapid Titer Kit was from Clontech (Mountain View, CA). Strata-X 33u (30 mg) solid-phase extraction
plates were from Phenomenex (Torrance, CA). Other reagents were from SigmaAldrich. Ketamine
analogs deschloroketamine (2-phenyl-2-(methylamino)cyclohexan-1-one), fluoroketamine (2-(2-
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fluorophenyl)-2-(methylamino)cyclohexan-1-one,
and
bromoketamine
(2-(2-bromophenyl)-2-
(methylamino)cyclohexan-1-one were synthesized using reported methods.
Generation of recombinant baculoviruses
Production of recombinant human proteins CYP2B6, P450 reductase (POR) and cytochrome b5
was performed as previously described.30 In brief, CYP2B6, POR and b5 genes were amplified from the
Human Liver Quick-Clone cDNA library (Clonetech), and inserted individually into the transfer vector
pVL1393 using the In-Fusion HD Cloning system (Clontech). Recombinant baculovirus was produced
with BestBac 2.0 Baculovirus Cotransfection Kit (Expression Systems). Sf9 insect cells were
cotransfected with BestBac linearized DNA and the plasmid DNA of transfer vector carrying the gene of
interest on a 6-well plate to produce p0 generation of recombinant baculovirus. Sf9 cells in suspension
culture were infected with p0 to make subsequent viral generation. Viral titers were determined using the
BacPAK Baculovirus Rapid Titer Kit (Clontech).
Expression of recombinant proteins in insect cells
Protein expression was performed as described previously.30 Briefly, Tni cells in suspension
culture in early log phase growth were infected with the recombinant baculoviruses carrying CYP2B6,
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POR and b5 genes, with multiplicities of infection of 4:2:1 (CYP2B6:POR:b5), in the presence of heme
precursors -aminolevulinic acid and ferric citrate. After 48 to 72 hr growth post infection, cells were
harvested by centrifugation, washed twice with phosphate-buffered saline, and resuspended in potassium
phosphate buffer pH 7.4 and stored frozen at -80ºC. Frozen cells were thawed and lysed on ice in a
Potter-Elvehjem tissue homogenizer and aliquots stored at -80 ºC. P450 content, b5 content and POR
activity were measured as described previously.30
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Ketamine demethylation measured by formaldehyde formation
Ketamine is converted to norketamine and formaldehyde in the primary metabolism step by
CYP2B6. The product formaldehyde was measured using Nash reagent for ketamine analog metabolism,
while both formaldehyde and norketamine were measured for metabolisms of R-, S-, and RS-ketamine.
All incubations were carried out in 96-well PCR plates with raised wells. Ketamine analogs and RS-
ketamine with concentrations of 0, 1, 2.5, 5, 12.5, 25, 50, 100, 200, 400, 700, and 1000 µM was mixed
with the enzyme CYP2B6/POR/b5, and preincubated at 37 ºC for 5 min. Substrate concentration range of
0-500 µM was used for enantiomers R- or S-ketamine. Final CYP2B6 concentration was 5 pmol/ml, and
total reaction volume was 200 µl in 100 mM potassium phosphate pH7.4. The reaction was initiated by
adding an NADPH regenerating system (final concentrations: 10 mM glucose 6-phosphate, 1 mM ß-
NADP, 1 U/ml glucose-6-phosphate dehydrogenase, and 5 mM magnesium chloride, preincubated at
37°C for 10 min). After incubation for 10 min, the reaction was quenched by adding 40 µl of 15% zinc
sulfate, and the plate was centrifuged at 2500 rpm for 5 min to remove precipitated proteins and zinc
hydroxide.
Formaldehyde was measured using a previously described method,31 with minor
modifications. A stock solution of 38.8 mM acetylacetone was prepared in 30% (W/V) ammonium
acetate. Reaction supernatant (160 µL) was transferred to a new plate, and mixed with 80 µL of 38.8 mM
acetylacetone, and incubated at 60 °C for 20 min. The plate was centrifuged at 2500 rpm for 5 min and
160 µL supernatant was transferred to a Corning 96-well black polystyrene plate with clear flat bottom,
and mixed with 20 µL of 6% (W/V) bovine serum albumin solution. After incubation for 5 minutes,
fluorescence intensity was measured at excitation and emission wavelength of 415nm, and 480 nm,
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respectively, using the Biotek Synergy MX Microplate Reader. For calculation of formaldehyde
concentrations, a standard curve was generated using standardized formaldehyde sample. A stock solution
of 33 mM formaldehyde was prepared from 37% formaldehyde solution (Sigma Aldrich) and
standardized by following a previously described procedure of pH titration,32 Formaldehyde was reacted
with excess sodium sulfite by adding 25 mL of 33 mM formaldehyde into 25 mL 0.1 M sodium sulfite,
and pH was recorded prior to and after addition of formaldehyde (sodium hydroxide released in the
reaction caused pH increase in the range of pH 9-11). Then the mixture was titrated back to the original
pH using 0.1 N HCl solution which was prepared from standard 1 N HCl solution (Fisher SA48-1), and
the volume of HCl consumption was used to calculate the standard formaldehyde concentration. A series
of formaldehyde solutions with concentrations 0.2, 0.5, 1, 2, 4, 6, 8 and 10 µM were prepared from the
standard stock solution. The standard solutions were transferred to the 96-well plate that also carries
samples after CYP2B6 incubation. Reaction with acetylacetone and fluorescence measurement were
carried out under same conditions as described above.
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Ketamine demethylation measured by norketamine formation
Norketamine formation from R-, S-, and RS-ketamine was measured by HPLC/MSMS.30
Substrate concentrations were 0.125 – 500 µM R- or S-ketamine, and 0.25 – 1000 µM RS-ketamine.
Incubations with CYP2B6 were carried out under the same conditions as described above, except that the
reactions were quenched by adding 40 µL 20% trichloroacetic acid containing internal standard
norketamine-d4 (final concentration 90 ng/ml). Norketamine concentrations were determined by
enantioselective HPLC tandem mass spectrometry using solid-phase extraction, as originally
implemented for plasma analysis.11, 30 Calibration standards contained 0, 2, 5, 10, 20, 50, 100, 200, 500,
1000 and 2000 ng/ml racemic norketamine and were processed identically to incubation samples.
Stereoselective HPLC-mass spectrometry analysis was performed using a ChiralPak AGP analytical
column (100 x 2.0mm, 5µm) and AGP guard column (10 x 2.0mm) (Chiral Technologies, West Chester,
PA), coupled to an API 4000 QTrap LC-MS/MS linear ion trap triple quadrupole tandem mass
spectrometer (Applied Biosystems/MDS Sciex, Foster City, CA), as described previously.30 Interday
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coefficients of variation were 5% or less at 5, 50, and 500 ng/ml norketamine, and accuracy was within
5%.
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Results are reported as the mean ± SD of triplicates. Product formation (formaldehyde or
norketamine) versus substrate concentration data were analyzed by nonlinear regression analysis
(SigmaPlot 12.5, Systat, San Jose, CA) using single enzyme Michaelis-Menten kinetics.
Docking
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Ketamine and all analogs were drawn in XMDS without stereochemistry. Ketamine and all
ketamine analogs were prepared using Discovery Studio (Biovia, San Diego, USA) using the default
settings. Two stereoisomers were created for each ligand as well as a charged and neutral variant. The
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crystal structure of cytochrome P4502B6 (3IBD) with inhibitor 4-(4-chlorophenyl)imidazole
was
prepared in Discovery Studio using the default settings (waters removed). A default sized binding pocket
was created by selecting the crystallized ligand 4-(4-chlorophenyl)imidazole as an initiation point and
creating an input site sphere of 23.6216, 13.8463, 25.7039, 15Å. The docking software Libdock within
Discovery Studio was then used to dock the ligands within these constraints. The highest scoring poses
were saved as .pdb files and visualized in pymol (Schrodinger,1.8.2.3, New York, NY).
CYP2B6 Bayesian model
We curated a total of 58 unique molecules from multiple sources and experimental groups with
log Km data for CYP2B6,34 and 4 additional compounds (efavirenz and 3 analogs 35) were added from
ChEMBL (www.ebi.ac.uk/chembl/). Of note is that this dataset contained both R- and S-ketamine with
calculated Km values of 74 and 44µM, respectively, obtained using human liver microsomes.20 This varies
significantly from the current data with Km values of 10-15µM. These compounds were therefore
removed from the model in order to reduce an activity bias for the ketamine analogs. A Bayesian model
was then built with Assay Central.36-38 The model was built with a threshold of 15µM using ECFP6
descriptors, which generated 11 active compounds. Model validation was performed by five-fold cross
validation, a standard and widely used method.36-39 In addition, using data from ChEMBL CYP2B6
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inhibitor models were built where the IC50/EC50 measurements (198 compounds, 78 actives) were
calculated with a threshold of 15.22 µM and the Ki (224 compounds, 83 actives) was calculated with a
threshold of 16.27 µM.40
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Enantioselective HPLC MS/MS methods have been developed for analysis of ketamine and
metabolites, using metabolite reference standards.11, 41 The method was used successfully for recent
investigation of stereoselective ketamine N-demethylation to norketamine by CYP2B6 genetic variants.30
However, for the present analysis of the metabolism of ketamine analogs, the reference standards bromo-
norketamine and fluoro-norketamine were not available. Therefore, in the current investigation a
formaldehyde assay was used as an alternative method to evaluate N-demethylation of ketamine analogs.
The single enantiomers, S- and R-ketamine, and racemic RS-ketamine were incubated with
CYP2B6 in the presence of POR and cytochrome b5. The two products of N-demethylation, norketamine
and formaldehyde, were measured by HPLC MS/MS and formaldehyde assay, respectively (Figure 1 and
Table 1). Apparent Km values from the formaldehyde analysis were somewhat higher than from the
norketamine analysis, Vmax values were generally in good agreement, and the in vitro intrinsic clearance
(Clint, Vmax / Km) values, particularly for the racemate, were in excellent agreement. Our previous studies
showed that conversion of norketamine to secondary metabolites was not detectable under the
experimental conditions used.30 Thus, formaldehyde formation was an acceptable surrogate for
norketamine formation from RS-ketamine.
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N-demethylation of ketamine analogs by CYP2B6 was evaluated by formaldehyde analysis
(Figure 2), and the kinetic parameters are provided in Table 2. With substituent changes at the ortho
position on the phenyl ring from hydrogen to fluorine, chlorine, and bromine, substantial (18-fold)
differences in Km values were observed, from 184 µM for deschloroketamine to 10 µM for
bromoketamine. In contrast, Vmax values showed relatively minor differences (range 83 to 103
pmol/min/pmol CYP).
Docking
To understand the influence of halogen substitution on ketamine metabolism by CYP2B6, we
carried out molecular docking simulations to study CYP2B6-ligand interactions in the active site and the
structural basis of ligand binding affinity and substrate selectivity associated with halogen substitution.
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For deschloroketamine, a docking pose was chosen not only based on a high score, but also based
on the logical positioning of the N-methyl group of the molecule in proximity to the P450 heme, because
of the substantial size of the CYP2B6 binding site. The docking poses of ketamine and all the analogs
were very similar, sharing a π-stack with F297. The libdock scores had the following relationship:
deschloroketamine < bromoketamine < ketamine < fluoroketamine (Figure S1).
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Bayesian models
The Bayesian Km model generated with literature data using Assay Central resulted in a 5-fold
cross validation ROC of 0.86 and other statistical measures (Figure 3) which were generally acceptable
for such a small training set. The probability of activity at 15µM for ketamine and analogs was predicted
based on this model to produce an output score and applicability value (Table 3). The deschloroketamine
score strongly suggested inactivity, which corresponded to the experimental Km value of 184µM (Tables
2 and 3). The model was unable to accurately predict the activity of fluoroketamine, which was predicted
to be active, (although the observed experimental Km, 40µM, was relatively high (Tables 2 and 3). This
was similar to the lack of accuracy of the docking scores. Surprisingly, when we expanded this model to
include the updated Km values for R- and S-ketamine of < 15µM, deschloroketamine was not well
predicted to be active as compared to the other analogs, suggesting the importance of the halogen for
predicted activity. We also scored the inhibitory potential of these ketamine analogs against Bayesian
models built from publically accessible Ki and EC50 or IC50 data for CYP2B6 from ChEMBL. The Ki
model had an ROC of 0.81 and the EC50 or IC50 model had an ROC of 0.84 (Figure S2). Each of the
ketamine compounds scored as probable inhibitors of CYP2B6 with a probability score of approximately
0.5 (Table 3).
Assessing the binding pocket of CYP2B6 suggests a hydrophobic component to substrate
docking. There are several hydrophobic residues, including I101, I114, L363, V367, and V477 in the
substrate binding pocket. Comparison of AlogP (calculated in Discovery Studio) and log Km of ketamine
and ketamine analogs showed a strong linear correlation (R2=0.92, Figure 4). This calculated chemical
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property successfully predicted the experimental log Km, with an increase in hydrophobicity correlating
with an increase in affinity.
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The main finding of this investigation was that the halogen substituent at the ortho position on the
phenyl ring of racemic ketamine analogs markedly influenced the rate of N-demethylation. Metabolism,
based on Clint, was on the order Br > Cl > F > H. Vmax values were relatively unchanged, while Km was
on the order Br < Cl < F < H. Thus, apparent substrate binding affinity was the major consequence of
halogen substitution on ketamine analogs, and the major determinant of N-demethylation.
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Incorporation of halogen atoms into a drug molecule can have profound pharmacological
implications. Halogen substitution has been investigated extensively in drug research for optimization of
drug adsorption, distribution, recognition and selectivity. It is estimated that approximately 20% of
approved drugs are halogenated, as are a similar portion in other stages of discovery and development.27
Halogen effects on interactions of small molecules with proteins can be mediated through classical
halogen properties of reactivity, lipophilicity, and electronegativity, and the newly characterized halogen
bond.42 Halogen bonding is analogous to hydrogen bonding, driving short, stabilizing electrostatic
interactions with electron-rich atoms, with the halogen serving as a halogen bond donor to an electron
rich acceptor – typically the carbonyl oxygen of the peptide bond in proteins.42 The strength of halogen
bonding correlates with polarizability of the halogen atoms and changes in the order of F<Cl<Br<I.26
Similarly, the hydrophobicity of halogenated substrates is also affected by polarizability, and lowest for
fluorine and highest for iodine.
Major determinants of substrate binding affinity to P450s depend on the specific isoform. In
general, determinants for binding include hydrophobic interactions and hydrogen bonding features, while
electronic factors determine reaction rates.43, 44 For CYP2B6 more specifically, halogen-π interactions
between substrates and phenylalanine side chains in the hydrophobic active site are considered to drive
substrate selectivity and affinity.28 There are however few systematic evaluations, of the effects on
metabolism or affinity more generally, of halogen substitution on a particular substrate scaffold.26
Based on the results of this investigation, the major determinant of halogen substituent effects on
ketamine analogs binding affinity to CYP2B6 is likely hydrophobicity. This conclusion is based on the
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excellent correlation between the calculated property AlogP and log Km (R2=0.92, Figure 4). Thus
hydrophobicity changes due to halogen substitution may be the simplest design criteria to use when
considering similar compounds and the affinity for CYP2B6. There is also species evidence that proposes
a hydrophobic element to CYP2B substrate selection, with variation in the hydrophobic active sites found
between orthologs.28 An unexpected truism is that halogens are generally hydrophobic atoms, with Br
having the same hydrophobic effect as a methyl group.45, 46 This has been shown experimentally, where
halogen substitutions had a drastic effect on the logP(octanol-water) of compounds and the larger the
halogen the more dramatic the effect.47 It has also been previously suggested that hydrophobic
interactions are a major contribution in the interface between human protein kinase CK2 and a series of
halogen-substituted benzotriazoles, and was directly linked with the hydrophobicity of the halogen
substituent.48 Inhibition increased as the electronegativity of the halide substituent decreased (IC50:
F<Cl<Br). Molecular modeling suggested that the substituted halogen forms direct interactions with
hydrophobic residues within the binding pocket in a similar fashion to those found in the crystal structure
of human pCDK2. These interactions are thought to stabilize the complex by protecting the hydrophobic
halogen atoms from solvent accessibility.
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The present results can be compared with some previous observations. Many other CYP2B6
substrates are also halogenated, including the drugs bupropion, efavirenz, ticlopidine, and amlodipine,
and various environmental chemicals.49 There has also been evidence that suggests halogen-
interactions may also play a role in CYP2B6-substrate interactions, with the crystal structure of CYP2B6
and its halogenated monoterpene bornyl bromide demonstrating bromine-π bonding with the aromatic
side chain of phenylalanine 108.28 Similar computational modeling of myrtenyl bromide suggested
bromine-π bonding to the aromatic side chain of phenylalanine 297.28 These results were interpreted to
suggest that halogen-π interactions may be unique to CYP2B enzymes, which possesses a sufficiently
malleable active site to enable halogen interactions with multiple phenylalanine residues.28 A kinetic
investigation probed the influence of halogenation of CYP2B6-catalyzed metabolism.50 Using a small
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series of 4-trifluoromethyl-7-ethoxycoumarins to probe metabolism (O-dealkylation) by CYP2B6, it was
found that 2-ethoxy chlorination, and more so bromination, moderately decreased the Km, while kcat was
markedly reduced (by more than 90%) by either bromination or chlorination, resulting in net reduction
(by 85-90%) in catalytic efficiency (kcat/Km).50 These turnover results are in contrast to the present results
with ketamine analogs. Nevertheless, together these combined observations may implicate the role of
halogen bonding in the selectivity of ligand binding to CYP2B enzymes.
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There is little other catalytic, and no clinical information, about metabolism of halogenated
ketamine analogs to our knowledge. It has been suggested, albeit without any accompanying data, that
deschloroketamine, a black market designer drug, be more potent and longer lasting than ketamine.51 The
results of the present study do suggest that slower metabolism of deschloroketamine might mean
diminished systemic clearance. This presents potential opportunities for deriving new analogs in the
future with improved pharmacokinetic properties. For example, analogs with reduced metabolism may
have improved oral availability and/or greater duration of effect. Avid ketamine metabolism and low
bioavailability may underlie the lack of analgesia of oral ketamine.52 Conversely, since ketamine
antidepressant effects have been attributed to one or more active metabolites, such as norketamine and
hydroxynorketamine,16, 17, 25 greater metabolite formation may enhance antidepressant effects. It is not
apparent how chloro- (or more generally halogen) substitution alone influences interactions between
ketamine and its drug targets.3
There are recognized limitations with the various computational approaches. The Libdock
program used for docking only considers halogen H-bonding/π-stacking and did not include a halogen
bond scoring function. Halogen bonding is very complex with many caveats, including directionality. The
anisotropic electron distribution of halogens coupled with an aromatic ring adds an additional level of
complexity, partially because it is impacted by the other electron withdrawing groups found on the ring.
The binding pocket of CYP2B6 is large relative to a small molecule like ketamine making the docking
very challenging. The Bayesian machine learning model is just one algorithm that has been widely used
elsewhere, and in this study it was used to predict Km. Future approaches could consider other algorithms
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as used previously for different proteins.36-39 Given the clinical effectiveness of ketamine in anesthesia,
pain, and depression, and the considerable interest in the synthesis and commercial development of
ketamine-inspired drugs,53 such approaches may be useful.
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CYP2B6 metabolizes 3-10% of therapeutic drugs, but is still less well characterized than many
other CYP isoforms.34, 54-58 Monoterpenes have also been suggested as ideal active site probes for
CYP2B6.28, 29, 59 The present results suggest that ketamine analogs may also be very useful probes,
particularly for representatives of drugs as well as environmental contaminants such as pesticides and
nerve agents and mitigating the toxicity of such molecules.60 These ketamine analogs suggest unmet
needs and opportunities to better understand substrate-CYP2B6 interactions and enable reliable future
computational predictions.
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Acknowledgments
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Dr. Alex Clark is gratefully acknowledged for his assistance with Assay Central. Biovia are kindly
acknowledged for providing Discovery Studio to SE
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Supporting Information Additional figures
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Table 1. Kinetic parameters for ketamine demethylation measured from norketamine and formaldehyde
formation
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Substrate
Product
Km
(µM)
Vmax
Clint
(pmol・min-1・pmol CYP-1)
(ml・min–1・nmol P450–1)
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S-ketamine
S-ketamine
R-ketamine
R-ketamine
RS-ketamine
RS-ketamine
RS-ketamine
S-norketamine
formaldehyde
R-norketamine
formaldehyde
S-norketamine
R-norketamine
formaldehyde
10 ± 1
15 ± 1
11 ± 1
15 ± 1
5 ± 1
106 ± 1
106 ± 1
65 ± 1
92 ± 2
45 ± 1
38 ± 1
98 ± 1
10.4
7.2
5.7
6.2
9.0
9.2
5.7
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11
12
13
14
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19
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22
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60
4 ± 1
17 ± 1
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Table 2. Kinetic parameters for demethylation of ketamine analogs measured by formaldehyde formation
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Ketamine analog
Halogen
substitution
Km
Vmax
Clint
(pmol・min-1・pmol CYP-1) (ml・min–1・nmol P450–1)
(µM)
9
RS-deschloroketamine
RS-fluoroketamine
RS-ketamine
H
F
184 ± 18
40 ± 3
17 ± 1
10 ± 1
83 ± 3
103 ± 2
98 ± 1
94 ± 2
0.45
2.6
5.7
9.6
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Cl
Br
RS-bromoketamine
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Table 3. Ketamine and analogs Assay Central Km, Ki, IC50/EC50 models with applicability scores and some molecular properties.
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Assay
Central
Probability Applicability
Score
(IC50/EC50
model)
Assay
Central
Assay
Central
Assay
Central
Assay
Central
Assay
Central
Molecular
Structure
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Molecule
MW
AlogP Probability Applicability Probability Applicability
Score
(IC50/EC50
model)
Score (Km
model)
Score (Km
model)
Score (Ki
model)
Score (Ki
model)
deschloroketamine
204.3
0.985
-3.614
0.579
0.527
0.474
0.595
0.553
fluoroketamine
ketamine
222.3
238.7
283.2
1.19
1.649
1.733
15.231
8.554
8.144
0.535
0.488
0.419
0.510
0.564
0.584
0.442
0.465
0.395
0.530
0.595
0.568
0.422
0.488
0.419
bromoketamine
Higher probability scores relate to increased affinity. Applicability scores address overlap of fragments of a molecule compared to the training set
for each model. The higher the score the more similar to compounds in the training set.
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