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Chemical composition and biological effects of kratom (Mitragyna speciosa): In vitro studies with implications for efficacy and drug interactions


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The safety and efficacy of kratom (Mitragyna speciosa) for treatment of pain is highly controversial. Kratom produces more than 40 structurally related alkaloids, but most studies have focused on just two of these, mitragynine and 7-hydroxymitragynine. Here, we profiled 53 commercial kratom products using untargeted LC-MS metabolomics, revealing two distinct chemotypes that contain different levels of the alkaloid speciofoline. Both chemotypes were confirmed with DNA barcoding to be M. speciosa. To evaluate the biological relevance of variable speciofoline levels in kratom, we compared the opioid receptor binding activity of speciofoline, mitragynine, and 7-hydroxymitragynine. Mitragynine and 7-hydroxymitragynine function as partial agonists of the human µ-opioid receptor, while speciofoline does not exhibit measurable binding affinity at the µ-, δ-or ƙ-opioid receptors. Importantly, mitragynine and 7-hydroxymitragynine demonstrate functional selectivity for G-protein signaling, with no measurable recruitment of β-arrestin. Overall, the study demonstrates the unique binding and functional profiles of the kratom alkaloids, suggesting potential utility for managing pain, but further studies are needed to follow up on these in vitro findings. All three kratom alkaloids tested inhibited select cytochrome P450 enzymes, suggesting a potential risk for adverse interactions when kratom is co-consumed with drugs metabolized by these enzymes.
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Scientic Reports | (2020) 10:19158 | 
Chemical composition
and biological eects of kratom
(Mitragyna speciosa): In vitro
studies with implications
for ecacy and drug interactions
D. A. Todd1, J. J. Kellogg1,2, E. D. Wallace1,3, M. Khin1, L. Flores‑Bocanegra1, R. S. Tanna4,
S. McIntosh5, H. A. Raja1, T. N. Graf1, S. E. Hemby5, M. F. Paine4, N. H. Oberlies1 &
N. B. Cech1*
The safety and ecacy of kratom (Mitragyna speciosa) for treatment of pain is highly controversial.
Kratom produces more than 40 structurally related alkaloids, but most studies have focused
on just two of these, mitragynine and 7‑hydroxymitragynine. Here, we proled 53 commercial
kratom products using untargeted LC–MS metabolomics, revealing two distinct chemotypes that
contain dierent levels of the alkaloid speciofoline. Both chemotypes were conrmed with DNA
barcoding to be M. speciosa. To evaluate the biological relevance of variable speciofoline levels
in kratom, we compared the opioid receptor binding activity of speciofoline, mitragynine, and
7‑hydroxymitragynine. Mitragynine and 7‑hydroxymitragynine function as partial agonists of the
human µ‑opioid receptor, while speciofoline does not exhibit measurable binding anity at the µ‑,
δ‑ or ƙ‑opioid receptors. Importantly, mitragynine and 7‑hydroxymitragynine demonstrate functional
selectivity for G‑protein signaling, with no measurable recruitment of β‑arrestin. Overall, the study
demonstrates the unique binding and functional proles of the kratom alkaloids, suggesting potential
utility for managing pain, but further studies are needed to follow up on these in vitro ndings. All
three kratom alkaloids tested inhibited select cytochrome P450 enzymes, suggesting a potential risk
for adverse interactions when kratom is co‑consumed with drugs metabolized by these enzymes.
According to the US Department of Health and Human Services, opioids were responsible for more than 42,000
deaths in the US in 2016, the highest in recorded history1. More than 40% of these deaths involved a prescription
opioid. Some individuals who suer from chronic pain are turning to other options, one of which is the plant
known as kratom [Mitragyna speciosa (Korth.) Havil. (Rubiaceae)], a tropical tree native to peninsular ailand,
Myanmar, Malaysia and other countries in Southeast Asia1,2. Kratom has skyrocketed in popularity in western
countries in the past decade; current estimates are that as many as 5 million individuals in the US use kratom on
a regular basis3. ere has been considerable controversy over the safety and ecacy of kratom use by US con-
sumers. Citing safety concerns (one study reports that kratom has been implicated as at least partially involved
in 91 deaths)4, the United States Department of Agriculture (USDA) has made it their practice to conscate ship-
ments of kratom into the US. e US Drug Enforcement Administration (DEA) threatened to assign kratom as a
schedule 1 controlled substance, which would make possession of kratom illegal. e DEA then suspended that
decision in response to a backlash from some US consumers5, who claim that it is a safer alternative to opioids
for treatment of pain and/or opioid addiction6. e eectiveness of kratom for these purposes continues to be a
hotly debated and politically charged topic, and one that requires rigorous scientic investigation.
    Department of Chemistry, The University of North Carolina Chapel
            
 *
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Widespread kratom use is a relatively new phenomenon in the US6. However, the medicinal use of kratom
in southeast Asia has a long history. Kratom was rst documented in the scientic literature in 18367, in a paper
that described use of kratom leaves by the Malays as a substitute for opium. e isolation of mitragynine was
reported in 1921 by Ellen Field8, who ended the introduction of her paper with the following statements, “Accord-
ing to Redley………..Mitragyne [sic] speciosa is used in Perak against the opium habit, whilst, according to Dr. P.P.
Laidlaw, mitragynine is a local anaesthetic [sic]…” us, controversy over the use and eectiveness of kratom
was documented nearly 100years ago. It is a controversy that continues today.
Consistent with the claim that kratom can be eective in the treatment of pain, extracts from this plant dem-
onstrated opioid-receptor mediated analgesic eects in mouse model studies9. is activity has generally been
attributed to alkaloids that the plant produces, of which mitragynine (1) and 7-hydroxymitragynine (2) (Fig.1)
have been the focus of multiple pharmacological investigations1013. Mitragynine and 7-hydroxymitragynine
both bind to the human µ-opioid and ƙ-opioid receptors (hMOR, hKOR) with nanomolar anity, and func-
tion as partial agonists at the µ-opioid receptor and weak antagonists at ƙ-opioid and δ-opioid receptors14,15.
7-Hydroxymitragynine exhibits approximately vefold greater anity at the μ-opioid receptor compared to
mitragynine. Upon receptor activation, mitragynine and 7-hydroxymitragynine exhibit functional selectivity
for G-protein signaling, with no measurable recruitment of β-arrestin14. In antinociception assays, 7-hydroxymi-
tragynine exhibits 40-fold greater potency than mitragynine and tenfold greater potency than morphine16,17,
whereas mitragynine is less potent than morphine in antinociceptive assays18. Combined administration of
mitragynine with morphine increases antinociception compared with morphine alone and prevents the devel-
opment of morphine tolerance19. In contrast to mitragynine, repeated administration of 7-hydroxymitragynine
produces antinociceptive tolerance as well as cross-tolerance to morphine’s antinociceptive action and induces
physical dependence13. Furthermore, mitragynine does not exhibit abuse liability and decreases the reinforcing
eects of morphine whereas 7-hyroxymitragynine demonstrates abuse liability and increased morphine self-
administration in rats10. Interestingly, a recent study by Kruegel etal.12 shows that mitragynine can be converted
to 7-hydroxymitragynine both invitro and in a mouse model, therefore, some of the invitro activity attributed
to mitragynine may in fact be due to the action of it metabolite 7-hydroxymitragynine.
Collectively, the scientic data on mitragynine and 7-hydroxymitragynine suggest that kratom tea might
indeed be an eective alternative to opioids against pain. However, kratom products are sold to consumers under
a variety of trade names with no data regarding the chemical composition of plant material being consumed.
Kratom has been documented to produce variable levels of its more than 40 alkaloids, depending on genetic
variation and dierences in growth and processing conditions6,2022. What are the potential health implications
of the variability in chemical content of kratom preparations? As of yet, this question has been dicult to answer
because mechanistic studies of kratom alkaloids have focused largely on isolated alkaloids without consideration
of how these alkaloids are represented in kratom materials used medicinally. Herein, we sought to connect the
dots between investigations of pure alkaloids and their relevance to medicinally used kratom. Towards this goal,
we employed untargeted metabolomics to determine which alkaloids vary in content across commercial kratom
products. We then isolated these relevant alkaloids and compared their biological eects invitro, including
activity at the µ-opioid receptors and inhibitory eects on CYP isoforms involved in the metabolism of opioids
and other drugs. Our ultimate objective with this study was to capture the variability of commercial kratom
products being employed by US consumers and to evaluate (based on vitro studies) the potential implications
of this variability in terms of safety and ecacy.
Commercial kratom products can be divided into two chemotypes with diering alkaloid pro‑
les. We conducted untargeted metabolomics analysis of more than 50 commercial available kratom prod-
ucts (TableS1) to obtain a global comparison of chemical composition. A principal component analysis (PCA)
plot of the resulting data (Fig.2) reveals what appear to be two dierent groupings of the data. It was of interest
to determine which chemical constituent(s) were responsible for these dierences. To do so, we examined load-
ings and volcano plots (Fig.3) and determined that the peak area of a constituent with m/z of 401.2064 and
retention time of 2.70 varied across the two groups. is constituent was isolated and identied as the known
kratom oxindole alkaloid speciofoline (3, Fig.1) ([M + H]+ = 401.2071, Δ = 1.7ppm) based on comparison of
NMR, ECD, and mass spectrometry data with literature values2326 (TableS2, FigureS1 and S2). Several other
Figure1. Structures of select alkaloids present in kratom (Mitragyna speciosa), mitragynine (1),
7-hydroxymitragynine (2) and speciofoline (3).
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ions were also observed to vary in content across the samples (Fig.3), and based on their similar mass defect to
indole alkaloids27, are likely other more minor alkaloids of kratom. Structures of these other putative alkaloids
were not determined in this study.
Based on the chemical data (Fig.3), it appears that the commercial kratom products studied herein can be
grouped into separate “high-speciofoline” and “low-speciofoline” chemotypes. To demonstrate this further, a
comparison is shown of chromatographic peak area across all samples for the ions corresponding to mitragy-
nine and speciofoline (Fig.4). e mitragynine content in the commercial samples varied by fourfold, while the
speciofoline content varied by more than 90-fold, with a minority of samples appearing as “high-speciofoline”
outliers (Fig.4).
To further explore the phenomenon of variable speciofoline levels in kratom samples, we utilized the isolated
speciofoline to conduct quantitative analysis for representative high and low-speciofoline materials (Table1). A
limitation of working with commercial kratom samples is that morphological information that could be used to
identify the plants is lost when they are powdered. To address this limitation, we obtained a young, living plant
from a supplier in Ohio, which appeared based on morphological characteristics to be authentic M. speciosa.
is sample was coded as K55 and was included in the quantitative analysis.
As expected, the quantities of alkaloids dier in the two commercial kratom products subjected to quantita-
tive analysis (K51 and K52). Sample K51 contained mitragynine at a level of 11.45 ± 0.74mg/g (1.145 ± 0.074%),
and 7-hydroxymitragynine at a level of 0.056 ± 0.019 (0.0056 ± 0.002%). ese values are consistent with prior
literature28, which found that mitragynine was detected in commercial kratom products at a concentration
range between 1 and 6% of leaf content and that 7-hydroxymitragynine levels ranged from 0.01 to 0.04% of
leaf content. In contrast, sample K52 contains lower levels of mitragynine (8.13 ± 0.95mg/g) but, as expected
based on the data in Fig.4, has a much higher content of speciofoline (Table1) than sample K51. Interestingly,
the kratom plant used for morphological identication (K55) showed much lower abundance of mitragynine
and 7-hydroxymitragynine than either of the commercial kratom samples (K51 and K52). e reason for this
dierence cannot be ascertained with the experimental design employed for this study, but may be related to
dierences in plant age and/or growing conditions for K55 as compared to the commercial kratom products.
Because of the markedly low alkaloid levels (Table1), the K55 kratom sample was employed only for genetic
studies and was not further evaluated for pharmacological activity.
Genetic dierences do not appear to explain the observed chemotypes in commercial kratom
samples. ere are 10 related species within the Mitragyna genus6, including Mitragyna speciosa (Korth.)
Havil., Mitragyna diversifolia (Wall. ex G. Don) Havil., Mitragyna hirsuta Havil., and Mitragyna rotundifolia
(Roxb.) Kuntze. While these species can be distinguished by morphological characteristics in raw plant material,
contamination or misidentication could occur during collection and could not be distinguished in powdered
material such as that used in this study. e dramatic dierences in alkaloid quantity in various kratom samples
Figure2. Principal component analysis (PCA) scores plot generated based on LC–MS metabolomics traces of
kratom (Mitragyna speciosa) samples in Table1. Each data point represents the average peak areas of triplicate
extractions prepared for each sample. Samples selected for in-depth analysis herein (K50–K52) are highlighted
in orange. Two groupings were evident from the initial analysis (indicated here with separate Hotelling’s T2 95%
condence intervals). e underlying cause for these apparent dierences in the data was further explored with
loadings plot and volcano plot data (Fig.3).
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Figure3. Plots of signicant features based upon the PCA analysis. (A) Loadings plot, where the spatial
arrangement of the features (uniquem/z-RT pairings) corresponds to the distribution of the samples (i.e., scores
plot, Fig.2). Speciofoline (3) appears to be a feature that is responsible for discriminating between the two
sample groupings along the y-axis (PC2). (B) Volcano plot, highlighting signicant features of the metabolites
based on statistical testing (p value < 0.05, fold change > 2 or < 0.5) between the two groupings, with the further
a feature’s position away from the origin (0, 0), the more signicant the feature is. e speciofoline-rich group
(red circles) yielded 120 signicant features, while 19 features were signicantly distinct in the non-speciofoline-
rich grouping of commercial samples (purple circles). Speciofoline (3) was found to be a metabolite that diered
signicantly across sample groups, while mitragynine (1) and 7-hydroxymitragynine (2) were not signicantly
dierent between the two groups (orange circles). Other features predicted to be alkaloids based on mass defect
(open circles). Labels on plot refer to the compound number and the type of ion observed (i.e.[3 + H]+ refers to
the protonated molecule of speciofoline).
Figure4. Comparison of mitragyine and speciofoline levels across samples of M. speciosa. e x-axis represents
arbitrary codes assigned to the samples, as described in TableS1, and the y-axis represents the log of the peak
area for the relevant selected ion trace in LC–MS analysis.
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demonstrated in Table1 and Fig.4 led us to ask whether the samples reported to be Mitragyna speciosa might be
dierent species or strains of Mitragyna. To address this question, we extracted DNA from three kratom samples
with varying speciofoline content (K51, K52 and K55 in Table1), and used the resulting data for DNA barcod-
ing via BLAST search of rbcL + matK (core plant barcoding markers) and performed maximum likelihood and
Bayesian phylogenetic analysis, of the combined matK + trnH-psbA and the separate nrDNA ITS regions. ese
regions were selected because they are designated as the ocial DNA barcodes for the plant kingdom2937.
Molecular identication of plant samples using a BLAST search of core plant loci (rbcL + matK) using the
BOLDSYSTEMS database (version 4) showed that samples K51, K52 and K55 had ≥ 99% sequence similarity with
M. speciosa (FiguresS4–S6). Based on uncorrected p distances calculated for trnH-psbA, there was ≥ 99–100%
sequence similarity with sequences of published M. speciosa. is means that samples K51, K52 and K55 were
more similar to sequences of M. speciosa and more dissimilar to sequences of M. diversifolia, M. hirsuta, M.
rotundifolia, and M. parvifolia (TableS5a and b). Maximum likelihood analysis of the partial matK + trnH-psbA
fragments placed all three samples in a strongly supported clade (100% RAxML bootstrap support, 78% PhyML
bootstrap and ≥ 95% Bayesian posterior probability support) with the published sequences for M. speciosa (Fig-
ureS7). Notably, this analysis included a partial matK sequence from a recently sequenced genome of M. speciosa
(BioProject: PRJNA325670). Finally, phylogenetic analysis using the nrDNA ITS region also placed K51 and K52
in a strongly supported clade (≥ 84% PhyML bootstrap and ≥ 95% Bayesian posterior probability support) with
M. speciosa sequences (FigureS8). However, the ITS analysis showed that K55 does not group with M. speciosa,
but rather formed a cluster with other Mitragyna spp., albeit without any signicant bootstrap support and/or
Bayesian posterior probability support (FigureS8).
e results of DNA barcoding and phylogenetic analyses classify all three kratom products as Mitragyna
speciosa, based on comparison with the published sequences for this species, except for the ITS analysis, which
showed a conicting outcome for sample K55. us, it appears that the observed dierences in speciofoline
content among the various kratom samples is not due to misidentication of species or substitution of a dierent
Mitragyna species for M. speciosa. Notably, a number of other factors including plant age, growing conditions,
and processing methods could all contribute to the observed dierences in alkaloid level in the various kratom
samples. Exploring these dierences would require a dierent experimental design and could be the subject of
future studies. For the purpose of the current investigation, the important nding is that dramatic dierences in
alkaloid content can be observed among dierent samples of what appear to be authentic (based on molecular
data) M. speciosa. Such dierences in alkaloid prole could have implications for biological activity, a possibility
that we explore in the next sections.
Dierences in alkaloid prole in kratom plant material is expected to have implications for
opioid receptor‑mediated activity. e alkaloid speciofoline is an oxindole, while the more commonly
studied alkaloids mitragynine and 7-hydroxymitragynine are indoles (Scheme1). us, we hypothesized that
there might be biological implications to the observed variability in speciofoline levels across kratom extracts
(Table1). To explore this hypothesis, we tested mitragynine (1), 7-hydroxymitragynine (2) and speciofoline (3)
for µ-opioid receptor inhibition of forskolin-stimulated cyclic-AMP (cAMP) accumulation and for their ability
to recruit β-arrestin-2 in CHO-K1 cells stably expressing the µ-opioid receptor. Results indicate that DAMGO
and morphine fully inhibit cAMP accumulation, mitragynine and 7-hydroxymitragynine partially inhibit cAMP
accumulation, whereas speciofoline has no eect in this assay (Fig.5A). Furthermore, DAMGO and morphine
eectively recruit β-arrestin-2 in CHO cells (Fig.5B), while mitragynine, 7-hydroxymitragynine, and speciofo-
line fail to recruit β-arrestin-2 at concentrations as high as 10mM.
To further characterize the pharmacology of the kratom alkaloids, competitive radioligand binding assays
were conducted with HEK293 cells stably expressing µ-, ƙ- and δ-opioid receptors to assess the anity of the
alkaloids at these receptors (Table2). Mitragynine exhibited moderate anity at µ- and ƙ-opioid receptors
whereas 7-hydroxymitragynine showed strong anity at the µ- opioid receptor (14X greater than mitragynine)
and moderate anity at the ƙ- and δ-opioid receptors (4X and 70X greater than mitragynine). In contrast,
speciofoline did not exhibit appreciable anity for any of the opioid receptors. Results for mitragynine and
7-hydroxymitragynine are consistent with previous literature reports14,15; however, this is the rst published
assessment of receptor binding of speciofoline at opioid receptors.
Table 1. Alkaloid quantity in Kratom products. Samples K50, K51 and K52 are commercial kratom products
that were purchased for this study. Sample K55 is a young cultivated kratom plant. Quantities were calculated
by preparing methanolic extracts in triplicate and analyzing by LC–MS. a Quantity is denoted as mg of
compound per g of dried kratom plant material. b Uncertainty calculated using standard deviation of triplicate
extractions, each analyzed separately. c Limit of quantitation (LOQ) for speciofoline is 4.9ng/mL (TableS3) and
this sample contained speciofoline below that level. d LOQ for 7-hydroxymitragynine is 0.49ng/mL (TableS3)
and this sample contained 7-hydroxymitragynine below that level.
Sample code Mitragynine (mg/g)b7-Hydroxymitragynine (mg/g)bSpeciofoline (mg/g)b
K50 11.37 ± 0.83 0.053 ± 0.014 < LOQc
K51 11.45 ± 0.74 0.056 ± 0.019 < LOQc
K52 8.13 ± 0.95 0.0349 ± 0.0030 4.13 ± 0.45
K55 0.75 ± 0.14 < LOQd < LOQ c
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e dierential binding anity of mitragynine and 7-hydroxymitragynine at opioid receptors (Table2) is con-
sistent with previous literature14,15. Also consistent with literature reports14,15 both mitragynine and 7-hydroxymi-
tragynine function as partial agonists at the µ-opioid receptors and are functionally selective for G protein versus
β-arrestin-2 signaling (Fig.5). ese eects are quite dierent from the binding and activity of typical opioids
such as morphine (Fig.5). e failure of mitragynine or 7-hydroxymitragynine to recruit β-arrestin-2 may be an
important factor separating the analgesic eect from the adverse eects of typical opiates such as abuse liability,
respiratory depression and constipation. However, 7-hydroxymitgraynine, but not mitragynine, exhibits abuse
liability in rodent models of human drug-taking18, suggesting that β-arrestin-2 signaling may not be a signicant
contributing factor to the addictive properties of opiates. In contrast, speciofoline does not bind at the opioid
receptors and does not exhibit functional activity via the µ-opioid receptor. Future studies are warranted to
characterize speciofoline and determine if the ligand may induce antinociception or other activities through
non-opioid receptor systems, and to further characterize the pharmacological eects of kratom extracts and
their isolated alkaloids invivo.
Figure5. Kratom alkaloid mediated inhibition of forskolin-stimulated cAMP accumulation and β-arrestin
recruitment. (A) CHO-K1 cells stably expressing hMOR were incubated with the indicated concentrations
of compounds as described in Methods. Data are expressed as the percent of forskolin-stimulated cAMP
accumulation and represent mean ± SEM of 3–4 experiments. (B) β-arrestin-2 recruitment. CHO-K1 cells stably
expressing the µ-opioid receptor and β-galactosidase linked β-arrestin-2 were incubated with the indicated
concentrations of compounds as described in Methods. Data are expressed as the percent of maximal DAMGO
mediated response and represent mean ± SEM of 3–4 experiments. Emax and EC50 values for cAMP accumulation
and β-arrestin2 recruitment are listed in the table.
Table 2. Opioid receptor anities for kratom alkaloids. Competitive binding studies were performed against
3H-DAMGO, 3H-U69-593 and 3H-deltorphin for µ-, ƙ-,and δ-opioid receptors respectively. Results are
presented as nM ± SEM from a minimum of three replicates.
Receptor binding anity (Ki ± SEM, nM)
µ-opioid ƙ-opioid δ-opioid
Mitragynine 238 ± 28 482 ± 29 > 10,000
7-Hydroxymitragynine 16 ± 1 113 ± 37 137 ± 21
Speciofoline > 10,000 > 10,000 > 10,000
Morphine 1.50 ± 0.04 48.9 ± 5.0 > 10,000
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High‑speciofoline and low‑speciofoline kratom extracts have similar inhibitory eects on
three major CYPs in vitro. e cytochromes P450 (CYPs) constitute a superfamily of oxidative enzymes
that mediate the metabolism of approximately 50% of the top 200 most prescribed drugs38. Inhibition of these
enzymes by xenobiotics, including drugs and botanical products (precipitants), can lead to increased systemic
exposure to the object drug and potential adverse or toxic eects. Kratom extracts39 and mitragynine11,40 have
been tested as inhibitors of several CYPs, including CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4.
Tested extracts and mitragynine were generally stronger inhibitors of CYP2D6 activity relative to the other
Mitragynine has been reported to inhibit several cytochrome P450s (CYPs)11,3941, which could lead to
increased systemic exposure to co-consumed drugs, including opioids, and potential adverse eects. We evalu-
ated whether the observed variability in alkaloid prole for kratom extracts results in altered inhibitory eects
on three major CYPs, specically CYP2C9 (Fig.6A), CYP2D6 (Fig.6B), and CYP3A (Fig.6C). All three kratom
extracts tested showed concentration-dependent inhibition of each CYP, with stronger eects on CYP2D6 com-
pared to CYP2C9 and CYP3A. Eects on each CYP were similar between the high speciofoline (K52) and low
speciofoline (K50 and K51) kratom samples (Fig.6). Mitragynine and speciofoline showed similar inhibitory
Figure6. Kratom extracts (K50, K51, and K52), mitragynine, 7-hydroxymitragynine (7-HMG), and
speciofoline showed concentration-dependent inhibition of cytochrome P450 (CYP) enzymes in human
liver microsomes. Diclofenac 4-hydroxylation (A), dextromethorphan O-demethylation (B), and midazolam
1-hydroxylation (C) were used as measures of CYP2C9, CYP2D6, and CYP3A activity, respectively. Extracts
were tested at 2, 10, and 20µg/mL; alkaloids were tested at 1, 10, and 100µM. Positive control inhibitors
included sulfaphenazole (1µM), quinidine (2µM), and ketoconazole (0.1µM) for CYP2C9, CYP2D6, and
CYP3A activity, respectively. Control activities averaged 220, 70, and 1270pmol/min/mg, respectively. Bars and
error bars denote means and standard deviations, respectively, of triplicate incubations.
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eects towards CYP2C9 and CYP3A activity, whereas mitragynine showed stronger inhibition than speciofoline
against CYP2D6 activity. Relative to mitragynine and speciofoline, 7-hydroxymitragynine was a weak inhibitor
of CYP2C9 and CYP3A activity and a moderate inhibitor of CYP2D6 activity (i.e., inhibitory eects via mitragy-
nine > 7-hydroxymitragynine > speciofoline).e concentration of mitragynine in the kratom extracts tested at
20µg/mL was ~ 1µM. e stronger inhibitory eects of the extracts compared to an equimolar concentration
of isolated mitragynine indicated additional CYP inhibitors are present in the extracts. If the concentration of
mitragynine in the liver upon kratom consumption nears the IC50 values estimated from the screening assay
(~ 1µM for CYP2D6; 10–100µM for CYP2C9 and CYP3A), a CYP-mediated kratom-drug interaction is possible.
In addition, because CYP3A is also expressed in the intestine, mitragynine concentrations in the intestine could
well exceed 10µM, increasing the possibility of CYP3A-mediated kratom-drug interactions. A comprehensive
clinical pharmacokinetic study with a well-characterized kratom product is needed to determine the systemic
exposure to mitragynine and other kratom alkaloids, as well as additional mechanistic invitro studies, to ascer-
tain the likelihood of pharmacokinetic kratom-drug interactions.
Collectively, our chemical and invitro studies support previous studies suggesting that the purported ecacy
of kratom against pain is mediated at least in part by kratom alkaloids that function as biased ligands of the
µ-opioid receptors. ese ndings further highlight the value of pursuing mitragynine and related alkaloids as
an alternative strategy to treat pain, as, consistent with previous literature, our ndings suggest that they have
less abuse liability than classic opiates such as morphine. Future invivo studies are necessary to further explore
this possibility.
Our results also demonstrate that the identity and abundance of major alkaloids is highly variable in geneti-
cally similar kratom plant material, with some kratom products being dominated by the indole alkaloid mitragy-
nine and others containing high levels of both mitragynine and the oxindole alkaloid speciofoline. On the basis
of our studies, it is reasonable to predict that individuals who self-administer kratom tea to treat pain, addiction,
or depression might achieve very dierent results depending on the alkaloid prole of the product that they
use. Such dierences in activity would be dicult to predict for consumers, given that the variability in alka-
loid content is in no way reected in the product labeling. Additional studies are warranted to understand the
underlying causes for variability in alkaloid content in kratom plant material, and to evaluate the therapeutic
implications of this variability.
Consistent with previous literature, our results raise concern about potential drug interactions that may occur
when kratom is consumed concurrently with opiates or other drugs metabolized by the cytochrome P450s. Fol-
lowing up on these ndings, future clinical studies to evaluate the safety and ecacy of kratom and its alkaloids
would be of great benet to the public that may employ this botanical for the treatment of pain, currently or
in the future. In such studies, it would be useful to consider the potential dierences in activity that would be
observed by complex M. speciosa preparations as compared to their isolated alkaloids, and to account for potential
dierences in alkaloid prole in dierent kratom materials. Chemical proling of samples prior to evaluating
their biological activity is clearly crucial, and it is important that the biological studies be informed by the results
of the chemical analyses. is study demonstrates how untargeted mass spectrometry metabolomics followed
by targeted mass spectrometric quantitation can be eectively employed to generate chemical data valuable to
inform biological evaluation. As such, our approach can serve as a model for the design of future studies.
General. DAMGO, quinidine, ketoconazole, morphine sulfate, and alprazolam were purchased from Mil-
liporeSigma (St Louis, MO). Mitragynine, 7-hydroxymitragynine, midazolam, 1-hydroxymidazolam, sul-
faphenazole, and NADPH were obtained from Cayman Chemical Company (Ann Arbor, MI). Diclofenac,
4-hydroxydiclofenac, dextromethorphan, and dextrorphan were obtained from Toronto Research Chemicals,
Inc. (Toronto, Canada). Potassium phosphate buer salts were obtained from Fisher Scientic (Fair Lawn, NJ).
Human liver microsomes were obtained from XenoTech, LLC (H0604, mixed gender, pool from 15 donors, lot
no. 1010191; Kansas City, KS). All other chemicals and reagents used were analytical grade.
Acquisition of Kratom plant material. Fiy commercial products labeled as kratom were obtained from
vendors within the US. A table with details about these products is available in the supporting information
(TableS1). e commercial kratom products were obtained as dried powders and were various shades of grey-
green, with the exception of product K49, which was obtained as a cut leaf. All plant material was stored dry at
room temperature until time of analysis.
A cultivated plant of kratom (Mitragyna speciosa) (coded as K55) was generously donated to the project by
Shon Lenzo. e plant was grown from the cutting of a 7-year-old tree from a strain labeled as “rifat.” Prior to
shipping to the University of North Carolina Greensboro, the cutting was grown indoors in a greenhouse under
a 1000W high pressure sodium (HPS) LED light for 6months. Upon receipt, the plant was repotted and trans-
ferred to an outdoor location near the University of North Carolina Greensboro, where it was grown for several
summer months. Leaves were cut from this plant, dried at room temperature and powdered for extraction using
a Wiley Mill Standard Model No. 3 (Arthur omas Company). A sample of leaves from this plant, harvested at
the coordinates 36°453.616 N 79°476.18 W, was pressed and submitted to the University of North Carolina
Herbarium, with accession #670043 ( catalog number NCU00433756).
Isolation of speciofoline. Kratom plant material (K52, 1kg) was extracted exhaustively with 2 L of CHCl3/
CH3OH (1:1) and 50mL of KOH (10%) by maceration over 24h at room temperature. e mixture was ltered,
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and the solvent was evaporated under reduced pressure. e dried extract was reconstituted in 1N HCl solu-
tion and hexanes (1:1), transferred to a separatory funnel, and shaken vigorously. Aer removal of the hexanes
phase, the pH of the aqueous phase was adjusted to 9.0 with concentrated NH4OH solution. e basic phase was
exhaustively extracted with CHCl3, and the organic phase was evaporated to dryness to yield 1.0g of the dried
extract. Fractionation of the extract was conducted with normal phase ash chromatography using a silica col-
umn (24g) and a gradient solvent system of hexane–acetone-CH3OH over 52min at a ow rate of 35mL/min.
In total, thirteen pooled fractions were obtained. Fraction 4 was subjected to preparative reversed phase HPLC
over a Luna PFP(2) (pentauorophenyl) column (Phenomenex, 250mm × 21.2mm, 5µm) using a gradient of
70:30 to 100:0 CH3OH–H2O (10mM of ammonium acetate in both phases) over 20min at a ow rate of 20mL/
min. is process yielded 25.0mg of speciofoline (95% purity based on UPLC-UV), the structure of which was
solved by comparison of the calculated ([M + H]+ C22H29N2O5, 401.2076) and measured (401.2067) m/z values
and by comparison of key 1H-NMR signals (FigureS1 and TableS2) and the ECD spectra (FigureS2) with those
reported in the literature25.
Extraction for metabolomics proling. For each extraction of powdered kratom sample, 50mg of dried
kratom plant material was extracted with 5.0mL of methanol in a 25mL scintillation vial. Extracts were shaken
at 150rpm for 12h and the powder was allowed to settle. e extracts were decanted into clean scintillation
vials and dried under nitrogen. Extracts were resuspended in methanol containing 0.125µg/mL of mitragynine-
D3 (MilliporeSigma, St. Louis, MO, USA) for analysis. All diluted extracts contained mitragynine-D3 at a nal
concentration of 0.125µg/mL as an internal standard to monitor the consistency of the instrument performance.
Ultraperformance liquid chromatography–mass spectrometry (UPLC‑MS) analysis of Kratom
extracts. Untargeted metabolomics analyses were conducted using an Acquity Ultra-Performance Liq-
uid Chromatography system (Waters, Milford, MA, USA) coupled to a Q Exactive Plus Hybrid Quadrupole-
Orbitrap mass spectrometer (ermo Fisher Scientic, Waltham, MA). A Kinetex F5 column (Phenomenex,
50mm × 1mm, 2.6µm) was employed with a ow rate of 0.6mL/min and a column temperature of 40°C. e
starting conditions were 65% A, optima grade water with 0.1% formic acid and 2mM ammonium formate, and
35% B, optima grade methanol with 0.1% formic acid and 2mM ammonium formate. e gradient is as follows:
a slight decrease to 55% A at 0.5min which is held until 3.0min, followed by a linear decrease to 20% A at 10min
down to 0% A at 11.0min. e gradient returns to starting conditions at 12min and that is held for 1min. A 5µL
injection was employed for all samples using a 5µL sample loop.
Mass spectrometry analysis utilized a heated electrospray ionization (HESI) source: spray voltage 3.5kV,
capillary temperature 275°C, sheath gas 55 arbitrary units, auxiliary gas 15 arbitrary units, sweep gas 3 arbitrary
units, heater temperature 450°C, and an RF level of 50. A scan range of 150–900m/z was employed in positive
mode with a resolving power of 70,000 and an AGC target of 3E6. MS/MS data were collected on the standards
using a normalized collision energy (NCE) of 35V.
Metabolomics data processing. e UPLC-MS data were analyzed, aligned, and ltered using MZmine
2.28 soware (https ://mzmin e.githu with a slightly modied version of a previously reported method42.
e following parameters were used for peak detection of the data: noise level (absolute value), 1 × 105 counts;
minimum peak duration 0.5min; tolerance for m/z intensity variation, 20%. Peak list ltering and retention time
alignment algorithms were performed to rene peak detection. e join algorithm was used to integrate all the
chromatograms into a single data matrix using the following parameters: the balance between m/z and retention
time was set at 10.0 each, m/z tolerance was set at 0.001 or 5ppm, and retention time tolerance was dened as
0.5min. Once an aligned peak list was created, features (m/z and retention time pairs) present in the rst blank
sample of the run were deleted as a means of blank ltering. e peak areas for individual ions detected in the
process replicates and analytical replicates were exported from the data matrix for further analysis. e peak
list from MZmine was exported into Excel (Microso, Redmond, WA) for further ltering based on relative
standard deviation between analytical replicates. Analytical replicates would be expected to have comparable
proles, and similar peak areas for each feature. Ions detected within the analytical replicates with disparate
peak areas (based on an RSD cuto of 25%) were assigned as artefacts of the instrument and excluded from the
metabolomics analysis43.
Principal component analysis (PCA) was performed using Sirius version 10.0 (Pattern Recognition Systems
AS, Bergen, Norway). e 95% condence intervals were calculated using Hotelling’s T2 with the R package ‘car’44
using an R script available from https ://githu ellog g/Compo site-score .
Identication and quantitative analysis of alkaloids in kratom plant material. Standard solu-
tions of mitragynine and 7-hydroxymitragynine were purchased from MilliporeSigma (St. Louis, MO, USA) and
supplied as methanolic solutions at a concentration of 100µg/mL. An analytical standard for speciofoline was
unavailable for purchase, therefore an aliquot of puried speciofoline isolated as part of this study was dissolved
in methanol at a concentration of 100µg/mL. A 100 µL aliquot of each standard solution was combined with 600
µL of methanol and 100 µL of water to make a stock solution containing 10µg/mL of each alkaloid of interest.
A standard calibration curve was prepared using the stock solution in two-fold dilutions from 5000ng/mL to
4.9ng/mL followed by a single 1:10 dilution of the lowest concentration in methanol. All samples were analyzed
using the UPLC-MS method previously described. e selected-ion chromatograms for the calculated m/z val-
ues of the alkaloids of interest (mitragynine, [M + H]+ = 399.2284; 7-hydroxymitragynine, [M + H]+ = 415.2233;
speciofoline, [M + H]+ = 401.2076) within a mass error of 5ppm were plotted, and a calibration curve was con-
structed as area of these chromatograms versus concentrations. Calibration parameters are provided in TableS3.
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Identity of the alkaloids in the M. speciosa plant material was conrmed by matching retention time and m/z
value with that of the standards. e alkaloid concentrations in the kratom extracts were determined using linear
regression of these calibration curves. Peak areas were calculated using the ermo Xcalibur QuanBrowser ver-
sion 3.0.63 and statistical analysis was performed using RStudio version 1.2.1335.
Authentication of plant material. Authentication (assignment of genus and species) of kratom products
K51, K52 (powdered material), and K55 (vouchered plant specimen) was accomplished using DNA barcod-
ing and maximum likelihood phylogenetic analysis. e most widely recommended loci, the plastid intergenic
spacer trnH-psbA, rbcL, matK, and the nuclear ribosomal internal transcribed spacers (ITS) were employed.
ese regions have been designated as the ocial DNA barcodes for the plant kingdom29,30.
For DNA extraction from the plant material (K55), a whole leaf sample was ground to a ne powder with
a sterile mortar and pestle using liquid nitrogen. Approximately 5mg of plant powder from the plant (K55) or
from commercial sources (K51, K52) was transferred to a bashing bead tube with DNA lysis buer provided by
Zymo Research Quick-DNA plant/seed miniprep DNA extraction kit. e powder in the bashing bead tube was
further disrupted and homogenized in a Qiagen TissueLyser LT beadmill for ve minutes. For K51 and K52, the
samples were separately ground in bashing bead tubes, without treatment with liquid nitrogen. Genomic DNA
was then extracted according to kit instructions.
Detailed methods for DNA extraction, PCR amplication, and Sanger sequencing are outlined previously45.
e partial rbcL region was amplied and sequenced using primers rbcLa-F and rbcLa-R30,46. Details of PCR
primers and thermocycler parameters for all fragments amplied are outlined in Supplementary TableS4.
For identication of kratom plant material via DNA Barcoding, two plastid regions (rbcL + matK) sequences
were utilized in a combined analysis for plant identication by BLAST searching against the BOLDSYSTEMS
Uncorrected p-distances were calculated in Geneious, a bioinformatics desktop soware package (https ://
www.bioma tters .com) for sequences obtained from the trnH-psbA plastid region, which is considered as one
of the most variable regions of angiosperm plants4750. Comparisons were made using published sequence data
from NCBI GenBank for Mitragyna spp., including M. speciosa and the newly obtained sequences in this study
(Supplementary TableS5). e p-distances were obtained by dividing the number of nucleotide dierences by
the total number of nucleotides being compared. A cut o proxy of ≥ 98–100% was applied as a criterion to desig-
nate similar species; therefore, to be considered the same species based on trnH-psbA sequence comparison, the
taxa being compared should have ≥ 98% sequence similarity (with 1–2% intraspecic variation or dierences).
Maximum likelihood and Bayesian analysis was performed separately for both the combined analysis using
matK + trnH-psbA, and the nrDNA ITS region to place the kratom samples (K51, K52, and K55) into a phylo-
genetic framework with authentic published sequences of M. speciosa4852 using methods outlined previously53
(see Supplementary for details).
Nauclea ocinalis (Rubiaceae) was used as an outgroup taxon in both matK + trnH-psbA and ITS region
analysis, respectively. e sequence data obtained from samples K51, K52, and K55 are deposited in GenBank
and accession numbers are provided in TableS6.
Cytochrome P450 (CYP) inhibition assay. Mitragynine and 7-hydroxymitragynine (purchased), speci-
ofoline (the isolated alkaloid), and three methanolic kratom extracts (prepared from commercial products K50,
K51, and K52; Table1), were tested as inhibitors of CYP2C9, CYP2D6, and CYP3A activities using a cocktail
approach54. Diclofenac (4µM), dextromethorphan (4µM), and midazolam (2µM) were used as probe substrates
for CYP2C9, CYP2D6, and CYP3A activities, respectively. Kratom extract (2, 10, 20µg/mL) or alkaloid (1, 10,
100µM) was incubated with human liver microsomes (0.05mg/mL) in 100mM potassium phosphate buer,
pH 7.4. Positive control inhibitors included sulfaphenazole (1µM; CYP2C9), quinidine (2µM; CYP2D6), and
ketoconazole (0.1µM; CYP3A). Final organic solvent (methanol) concentration in each incubation was limited
to 0.8% v/v. Aer equilibrating the mixtures for 5min at 37°C, the reaction was initiated by addition of NADPH
(1mM nal concentration) and incubated for 10min (CYP2C9 and CYP2D6 activities) or 2min (CYP3A activ-
ity) at 37°C. Reactions were quenched with 2 volumes of cold methanol containing internal standard (alpra-
zolam, 0.1µM). e quenched mixtures were centrifuged at 2270 × g for 10min, and the supernatants were
subjected to UPLC-MS/MS analysis for quantication of 4-hydroxydiclofenac, dextrorphan, and 1-hydroxy-
midazolam. e percent of CYP inhibition in the presence of the test article was calculated relative to solvent
e CYP-mediated metabolites (4-hydroxydiclofenac, dextrorphan, and 1-hydroxymidazolam) were quanti-
ed using a QTRAP system (AB Sciex, Framingham, MA), operating in positive electrospray ionization mode,
coupled to a Shimadzu Nexera X2 UHPLC (Shimadzu Corporation, Tokyo, Japan). Chromatographic separation
was achieved using an Acquity C18 column (3µm, 50 × 2.1mm, ermo Scientic, Waltham, MA) with a guard
column, heated to 40°C, and a binary gradient at a ow rate of 0.5mL/min. e mobile phase consisted of 0.1%
formic acid in water (A) and 0.1% formic acid in methanol (B). e following gradient was applied: 0–0.4min,
10% B; 0.4–1.0min, 10–95% B; 1.0–2.0min, 95% B; 2.0–2.1min, 95%-10% B; and 2.1–3.0min, 10% B. e
following multiple reaction monitoring transitions were used: m/z 312.0 231.0 (4-hydroxydiclofenac), m/z
258.2 157.2 (dextrorphan), m/z 342.0 324.0 (1-hydroxymidazolam), and m/z 309.1 281.0 (alprazolam).
All analyte concentrations were quantied using MultiQuant soware (version 2.1.1; AB Sciex; https ://sciex
.com/produ cts/sow are/multi quant -sow are) by interpolation from calibration curves prepared from relevant
matrix-matched standards over a range of concentrations (1.37–1000nM).
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cAMP accumulation assay. e cAMP Hunter eXpress OPRM1 CHO-K1 GPCR assay (Eurons Discov-
erX Corporation, St. Charles, MO, USA) was performed according to manufacturer’s instructions. Briey, cells
were seeded in 100µL cell plating reagent in 96 well plates and allowed to incubate at 37°C (5% CO2, 95% rela-
tive humidity) for 24h. Medium was removed from cells, and cells were washed with 30μL of cell assay buer.
Each compound was assessed using an 11 point vefold serial dilution with a starting concentration of 10μM.
Aliquots of compound/forskolin solution were added to cells (nal concentrations were 20μM forskolin, and
0.4% DMSO) and incubated at 37°C and 5% CO2for 30min. Next, cAMP antibody reagent detection solution
was added to each well according to manufacturer’s instructions at room temperature and protected from light
for 1h. Next, enzyme acceptor solution was added and the solution allowed to incubate at room temperature
and protected from light for 3h. Luminescence was quantied using a SpectraMax iD5 multi-mode microplate
reader with SoMax Pro soware (version 7.1, Molecular Devices, San Jose, CA, https ://www.molec ulard evice cts/micro plate -reade rs/acqui sitio n-and-analy sis-sow are/som ax-pro-sow are). Data were nor-
malized to vehicle and forskolin only control values and analyzed using nonlinear regression with Prism 8.4
(Graphpad, San Diego, CA).
β‑arrestin recruitment assay. e PathHunter eXpress OPRM1 CHO-K1 β-Arrestin GPCR assay (Euro-
ns DiscoverX Corporation) was performed according to the manufacturer’s protocol. Briey, cells were seeded
in 100 µL cell plating reagent in 96 well plates and allowed to incubate at 37°C (5% CO2, 95% relative humidity)
for 48h. Each compound was assessed using an 11 point vefold serial dilution with a starting concentration
of 10µM. Aliquots of compound solution were added to cells (nal concentrations were 20μM forskolin, and
0.4% DMSO) and incubated at 37°C and 5% CO2for 30min. Detection solution was then added to cells and
incubated at room temperature protected from light for 1h. Luminescence was quantied using a SpectraMax
iD5 multi-mode microplate reader with SoMax Pro soware (Molecular Devices, San Jose, CA). Data were
normalized to control values and analyzed using nonlinear regression to determine maximal and EC50 values
(Prism 8.4 for Mac; Graphpad San Diego, CA).
Binding anity to µ‑opioid receptors. HEK293 cells expressing human µ, δ- or κ-opioid receptors
were washed in ice cold PBS and scraped from cell culture plates in cold 50mM Tris–HCl buer, pH 7.4. Cells
were pelleted at 5200 × g for 10min at 4°C. Supernatant was discarded and the pellet was washed with more
Tris–HCl buer, sonicated, and centrifuged at 24,000 × g for 40min at 4°C. e pellet was re-suspended in Tris–
HCl buer, sonicated, and aliquoted for storage at 80°C until use. A Pierce BCA Protein Assay was utilized
to determine protein concentration in the membrane, according to manufacturer’s instructions. Membranes
were evaluated in saturation experiments to determine the optimal concentration for radioligand binding and
functional assays. A competitive binding assay was utilized to determine the Ki of each compound similar to
previous reports55,56. For this, 25μg of cell membrane was diluted in 50mM Tris–HCl, pH 7.4 and pipetted into
a 96 well plate. Test compounds were reconstituted in DMSO and added to the reaction plate.[3H]-DAMGO,
[3H]-U69-593 or [3H]-deltorphin (for µ-, ƙ-, and δ-opioid receptors respectively) was then added at a nal
concentration of 2–4nM (Perkin Elmer, Waltham, MA, USA). e reaction was incubated for 1h at room tem-
perature prior to transfer onto GF/B lter plates (Perkin Elmer). e plates were washed 10 × with cold buer
and dried for 15min at 50°C. MicroScint20 was then added to each well, the plates were sealed, and the counts
per minute were quantied on the TopCount NXT Microplate Scintillation counter (Perkin Elmer). e percent
displacement of the radiolabeled compound was calculated as described57. Unlabeled DAMGO was used to
determine non-specic binding control counts, while vehicle (DMSO) was added to determine total radioligand
binding on each plate. A series of three-fold dilutions were used for each test compound starting at 10μM. A
control curve of naloxonewas included on each plate for internal control.
Data availability
Raw mass spectrometric data have been made publicly available through MassIVE (MassIVE ID: MSV000086288,
https :// /C59V0 X). All other data are available by request to the corresponding author.
Received: 19 June 2020; Accepted: 22 October 2020
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We are grateful to Shon Lenzo and Richard A. (Richo) Cech for expertise in the cultivation of Mitragyna speciosa
plants and for providing cultivated M. speciosa samples. Research reported in this publication was supported in
part by the National Center for Complementary and Integrative Health, U.S. National Institutes of Health under
award numbers F32 AT009816 (fellowship to JJK) and U54 AT008909 (Center of Excellence for Natural Product
Drug Interaction Research) and by a supplement to U54 AT008909 provided by the NIH Oce of Dietary Sup-
plements. Mass spectrometry data were collected in the Triad Mass Spectrometry Facility at the University of
North Carolina at Greensboro. e Neuropharmacology Core Facility at the University of Mississippi School of
Pharmacy conducted the receptor binding experiments. e Core is funded by NIH P30GM122733. We thank
Ali Shahbandi and Zoie Bunch for technical assistance.
Author contributions
D.A.T., J.J.K., N.B.C., L.F.B., R.S.T., H.A.R., S.H.E., M.F.P., N.H.O. and N.B.C. wrote and edited the manuscript,
D.A.T. coordinated the experimental work and prepared gures, J.J.K. and E.D.W. conducted the extractions
and metabolomics analysis, M.K. performed quantitative analysis, L.F.B. performed isolation experiments, R.S.T.
conducted the C.Y.P. inhibition assays, S.M. and S.E.H. evaluated receptor binding, T.N.G. provided experimental
support for extract analysis and sample acquisition, HAR conducted genetic analysis, M.F.P., N.H.O., N.B.C.
secured project funding, analyzed data, and supervised the experimental work.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https :// 8-020-76119 -w.
Correspondence and requests for materials should be addressed to N.B.C.
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... Fig. 1a) to validate our hypothesis. M. speciosa produces various monoterpene indole alkaloids (MIAs) with great pharmaceutical potential as opioid agonists 11 and biased analgesics 12 . ...
Full-text available
Discovering natural product biosynthetic pathways from medicinal plants is challenging and laborious, largely due to the complexity of the transcriptomics-driven pathway prediction process. Here we developed a novel approach that captures the protein-level connections between enzymes for pathway discovery with improved accuracy. We proved that heterologous protein-protein interaction screening in yeast enabled the efficient discovery of both dynamic plant enzyme complexes and the pathways they organize. This approach discovered complexes and pathways in the monoterpene indole alkaloid metabolism of a medicinal plant, kratom with high success rate. Screening using a strictosidine β-D-glucosidase (MsSGD1) against 19 medium-chain dehydrogenase/reductases (MsMDRs) identified five MsSGD1-MsMDR complexes. Three out of the five interacting MsMDRs were then proven functional, while the remaining 14 non-interacting candidates did not show obvious activities. The work discovered three branched pathways by combining transcriptomics, metabolomics, and heterologous PPI screening and demonstrated a new plant pathway discovery strategy.
... This compound was predicted to be permeant through the brain-blood barrier. This result agreed that mitragynine from kratom could be used as an opioid and bind to µopioid and ƙ-opioid receptors [22]. ...
Full-text available
The study aims to identify the most responsible compound for the antiinflammation activity from Mitragyna speciosa leaves. Seventeen compounds previously reported to have been isolated from the leave were virtually screened against human 5-lipoxygenase protein and analyzed according to their binding energies. The native ligand used was arachidonic acid, and mitragynine was found to be the strongest binding compound (Pubchem ID: 3034396). In addition, ADMET profiling shows that mitragynine was not violating Lipinski’s rule of five and was not toxic.
... Mitragynine, an alkaloid from M. speciosa has been studied widely in chemistry, pharmacology, and clinical aspects. Several studies have documented the benefit of mitragynine as an anti-analgesic, suggesting a potential treatment for managing pain [8][9][10]. According to Metastasio et al. [7], mitragynine improved the health condition of COVID-2019 patients, including muscle pain and lethargy, and did not appear to cause side effects when M. speciosa was stopped after a brief duration of administration. ...
Full-text available
The ongoing coronavirus disease-2019 (COVID-19) catastrophe calls for the development of therapeutic approaches to combat the disease. Therefore, an in silico study was conducted to evaluate druggability capacity of mitragynine, a natural indole alkaloid compound, using adsorption, distribution, metabolism, and excretion (ADME) prediction and molecular docking simulation to the region binding domain of severe acute respiratory coronavirus 2 (SARS-CoV-2 RBD). The pharmacodynamics of mitragynine were evaluated for its druggability using SwissADME software, and molecular docking simulation was performed using using AutoDock software, using SARS-CoV-2 RBD (PDB ID: 6M0J) as the protein target retrieved from Protein Data Bank (PDB). ADME predicted that this compound has excellent druggability, transport properties, and pharmacokinetics, following Lipinski’s rule of five. Mitragynine is also nonmutagenic based on the AMES toxicity test. No PAINS alert was observed and synthetic acceptability score was 4.49, suggesting a moderately synthesised compound. Through the molecular docking approach, mitragynine successfully docked the binding site of SARS-CoV-2 RBD with a binding energy of -6.3kcal/mol and formed hydrogen bonds with the residue N501, which is one of the residues at the binding site of RBD. These findings, together with other therapeutic qualities of mitragynine warrant for more research into molecular dynamics, in vitro, and in vivo studies in COVID-19 therapy.
... We first identified where these alkaloids accumulate in planta by analyzing methanolic extracts of M. speciosa root, stem, bark and leaf tissue at a variety of developmental stages using targeted metabolomics ( Fig. 1c; Supplementary Fig. S1-S6). Consistent with literature reports 11,12 the alkaloid content in the leaves was higher than other organs, with mitragynine (1), paynantheine (6), speciogynine (3) and speciocilliatine (7) being the dominant products. Low levels of 7OH-mitragynine (2), (20S)-corynantheidine (5a) and strictosidine (8) were also observed. ...
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Mitragyna speciosa (Kratom) is used as a natural remedy for pain and management of opioid dependence. The pharmacological properties of Kratom have been linked to a complex mixture of monoterpene indole alkaloids, most notably mitragynine. Here, we report the central biosynthetic steps responsible for the scaffold formation of mitragynine and related corynanthe-type alkaloids. We illuminate the mechanistic basis by which the key stereogenic centre of this scaffold is formed. These discoveries were leveraged for the enzymatic production of mitragynine, the C-20 epimer speciogynine, and a series of fluorinated analogues.
... Several studies administered mitragynine to mice and dogs in experimental models with behaviorally functioning animals in conditioned place preference, self-administration, and intracranial self-stimulation models, reviewed recently by Henningfield et al. (2022), Ramanathan and McCurdy (2020), WHO ECDD (2021). None of these studies reported life-threatening effects of mitragynine of 20-56 mg/kg and higher (e.g., Avery et al. 2019;Behnood-Rod et al. 2020;Maxwell et al. 2020;Obeng et al. 2021;Gutridge et al. 2020;Hassan et al. 2021;Kamble et al. 2021;Suhaimi et al. 2021;Todd et al. 2020). For example, a pharmacokinetics and safety study in beagle dogs reported a "mild transient sedation" lasting about 2-4 h after 5 mg/kg oral mitragynine but without clinically significant effects on vital signs (Maxwell et al. 2020). ...
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Rationale Kratom derives from Mitragyna speciosa (Korth.), a tropical tree in the genus Mitragyna (Rubiaceae) that also includes the coffee tree. Kratom leaf powders, tea-like decoctions, and commercial extracts are taken orally, primarily for health and well-being by millions of people globally. Others take kratom to eliminate opioid use for analgesia and manage opioid withdrawal and use disorder. There is debate over the possible respiratory depressant overdose risk of the primary active alkaloid, mitragynine, a partial μ-opioid receptor agonist, that does not signal through ß-arrestin, the primary opioid respiratory depressant pathway. Objectives Compare the respiratory effects of oral mitragynine to oral oxycodone in rats with the study design previously published by US Food and Drug Administration (FDA) scientists for evaluating the respiratory effects of opioids (Xu et al., Toxicol Rep 7:188–197, 2020). Methods Blood gases, observable signs, and mitragynine pharmacokinetics were assessed for 12 h after 20, 40, 80, 240, and 400 mg/kg oral mitragynine isolate and 6.75, 60, and 150 mg/kg oral oxycodone hydrochloride. Findings Oxycodone administration produced significant dose-related respiratory depressant effects and pronounced sedation with one death each at 60 and 150 mg/kg. Mitragynine did not yield significant dose-related respiratory depressant or life-threatening effects. Sedative-like effects, milder than produced by oxycodone, were evident at the highest mitragynine dose. Maximum oxycodone and mitragynine plasma concentrations were dose related. Conclusions Consistent with mitragynine’s pharmacology that includes partial µ-opioid receptor agonism with little recruitment of the respiratory depressant activating β-arrestin pathway, mitragynine produced no evidence of respiratory depression at doses many times higher than known to be taken by humans.
... Kikura-Hanajiri et al. (2009) reported that MG content available in the commercial kratom products in the U.S. ranged between 1 -6%, while in our study, it was between 1.1 -2.2%. Also, an invitro study reported a similar range in commercial products sold in the U.S., between 8.13 -11.45 mg g -1 (7.5 -26.6 mg g -1 in the present study) (Todd et al., 2020). Moreover, the MG content in kratom grown in Malaysia was also within a similar range between 9.38 -18.85 mg g -1 . ...
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We analyzed the content of mitragynine (MG) found in kratom leaves (Mitragyna speciosa) and the influence of different environmental conditions (air and soil variables) on the yield in various regions of Thailand. The content of MG in kratom leaves ranged from 7.5 – 26.6 mg g-1 of dry leaf weight. Canonical correspondence analysis showed that the most significant environmental variables affecting the MG content among the various regions were light intensity, relative humidity, soil volumetric water content (VW), soil pH, and calcium. This study is a first step towards providing information about environmental conditions suitable to maximize the quality and quantity of bioactive alkaloids in kratom. Future studies should focus on leaf collection and the post-harvest processes in order to assure the desired alkaloidal content in finished products, when produced under suitable environmental conditions identified in this study.
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Background: Consumption of kratom (Mitragyna speciosa), an herbal substance, can result in adverse health effects. We characterized kratom-associated adverse events in Wisconsin to provide pertinent recommendations for clinicians and public health practitioners. Methods: Using Wisconsin Poison Center (WPC) data, we searched for and summarized all records associated with exposure to 'kratom', 'electronic delivery device containing kratom', or 'mitragyna' during January 1, 2010 through September 1, 2022. Results: Kratom-associated exposure calls to WPC increased 3.75 times from 2010 to 2020. Among all 59 calls, 26 (44.1%) reported concomitant use of another substance, agitation was the most common symptom reported (23, 39%), and 7 persons required critical care. Three unintentional ingestions were reported in children aged <2 years. Discussion: Kratom-associated exposure calls to WPC have been generally increasing in frequency since 2011. Wisconsinites who choose to use kratom might benefit from education regarding health risks and safe storage practices to avoid unintentional pediatric exposure.
Untargeted mass spectrometry (MS) metabolomics is an increasingly popular approach for characterizing complex mixtures. Recent studies have highlighted the impact of data preprocessing for determining the quality of metabolomics data analysis. The first step in data processing with untargeted metabolomics requires that signal thresholds be selected for which features (detected ions) are included in the dataset. Analysts face the challenge of knowing where to set these thresholds; setting them too high could mean missing relevant features, but setting them too low could result in a complex and unwieldy dataset. This study compared data interpretation for an example metabolomics dataset when intensity thresholds were set at a range of feature heights. The main observations were that low signal thresholds (1) improved the limit of detection, (2) increased the number of features detected with an associated isotope pattern and/or an MS-MS fragmentation spectrum, and (3) increased the number of in-source clusters and fragments detected for known analytes of interest. When the settings of parameters differing in intensities were applied on a set of 39 samples to discriminate the samples through principal component analyses (PCA), similar results were obtained with both low- and high-intensity thresholds. We conclude that the most information-rich datasets can be obtained by setting low-intensity thresholds. However, in the cases where only a qualitative comparison of samples with PCA is to be performed, it may be sufficient to set high thresholds and thereby reduce the complexity of the data processing and amount of computational time required.
Kratom, a non-federally regulated botanical herb, is widely growing in popularity as a naturopathic alternative for mood, anxiety, and attention deficit symptoms, along with legal recreational use as a psychoactive agent. It is predominantly sold without restriction and easily accessible over the counter at naturopathic, specialty “vape” or “smoke shops” and on the internet. Kratom's most abundant alkaloids, Mytraginine (MG) and 7-hydroxymitragynine (7-MG), have demonstrated multi-mechanistic properties via dopamine, serotonin, adrenergic, and mu-opioid-type receptors interaction in a dose-dependent manner. Given the reported association between Kratom consumption and its mood-altering and stimulant-like effects, we considered its role in the exacerbation of those predisposed to or with certain preexisting mental health disorders. In addition, Kratom's psychoactive compound derivatives are not detected in routine urine toxicology screens, which may pose a diagnostic obstacle when suspecting its use in critical settings such as acute mania or bipolar disorder with psychotic features. Considering its growing availability, potential for addiction, and withdrawal, the authors aim to highlight the need for further research on the potential effects of Kratom and its use as a crucial consideration during assessment, as well as the association between Kratom use and the exacerbation of those predisposed to or with certain preexisting mental health disorders. We concluded that, on balance, there was sufficient evidence to justify the plausibility of the association between Kratom ingestion in exceeding doses and the exacerbation of certain psychiatric manifestations such as psychosis.
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Two separate commercial products of kratom [Mitragyna speciosa (Korth.) Havil. Rubiaceae] were used to generate reference standards of its indole and oxindole alkaloids. While kratom has been studied for over a century, the characterization data in the literature for many of the alkaloids are either incomplete or inconsistent with modern standards. As such, full ¹H and ¹³C NMR spectra, along with HRESIMS and ECD data, are reported for alkaloids 1–19. Of these, four new alkaloids (7, 11, 17, and 18) were characterized using 2D NMR data, and the absolute configurations of 7, 17, and 18 were established by comparison of experimental and calculated ECD spectra. The absolute configuration for the N(4)-oxide (11) was established by comparison of NMR and ECD spectra of its reduced product with those for compound 7. In total, 19 alkaloids were characterized, including the indole alkaloid mitragynine (1) and its diastereoisomers speciociliatine (2), speciogynine (3), and mitraciliatine (4); the indole alkaloid paynantheine (5) and its diastereoisomers isopaynantheine (6) and epiallo-isopaynantheine (7); the N(4)-oxides mitragynine-N(4)-oxide (8), speciociliatine-N(4)-oxide (9), isopaynantheine-N(4)-oxide (10), and epiallo-isopaynantheine-N(4)-oxide (11); the 9-hydroxylated oxindole alkaloids speciofoline (12), isorotundifoleine (13), and isospeciofoleine (14); and the 9-unsubstituted oxindoles corynoxine A (15), corynoxine B (16), 3-epirhynchophylline (17), 3-epicorynoxine B (18), and corynoxeine (19). With the ability to analyze the spectroscopic data of all of these compounds concomitantly, a decision tree was developed to differentiate these kratom alkaloids based on a few key chemical shifts in the ¹H and/or ¹³C NMR spectra.
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The leaves from the tree Mitragyna speciosa, commonly known as Kratom, in the coffee plant family (Rubiaceae) are commonly used in their native habitat of Southeast Asia as a stimulant to sustain energy during hard day labor and as an opioid-like analgesic and sedative. Traditional and modern uses overlap based on the effects of the leaf extract which has also gained popularity in the United States and Europe in the last two decades. Kratom has and is being used for the mitigation of opioid withdrawal symptoms and as a harm reduction agent with a minority of users subsequently developing a dependence on the extract. The respective demographic use patterns of Kratom differ between Southeast Asia and the Western world. While pure Kratom is primarily used by day laborers and misused in conjunction with cough medicine by youth in Southeast Asia, a majority of users in the United States is middle-aged, has at least middle income, private health insurance, and completed some college. Deaths attributed to the use of Kratom have been reported in Europe and the United States but not in Southeast Asia. Although Kratom was detected as the alkaloid mitragynine in the blood of the decedents, causality could not be established in almost all cases because of poly-drug exposures. It is notable that Kratom can cause herb-drug interactions, especially with other central nervous system -active substances. Given the mostly unregulated market for Kratom products in Western countries, consumers may be exposed to adulterated or contaminated products, especially if purchased through websites or the darknet. A number of countries have scheduled Kratom because of its stimulant- and opioid-like effects and the established interaction of the alkaloid mitragynine with opioid receptors.
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Background Enzyme-mediated biotransformation of pharmacological agents is a crucial step in xenobiotic detoxification and drug disposition. Herein, we investigated the metabolism and physicochemical properties of the top 200 most prescribed drugs (established) as well as drugs approved by the US Food and Drug Administration (FDA) between 2005 and 2016 (newly approved). Objective Our objective was to capture the changing trends in the routes of administration, physicochemical properties, and prodrug medications, as well as the contributions of drug-metabolizing enzymes and transporters to drug clearance. Methods The University of Washington Drug Interaction Database (DIDB®) as well as other online resources (e.g.,,,, and was used to collect and stratify the dataset required for exploring the above-mentioned trends. Results Analyses revealed that ~ 90% of all drugs in the established and newly approved drug lists were administered systemically (oral or intravenous). Meanwhile, the portion of biologics (molecular weight > 1 kDa) was 15 times greater in the newly approved list than established drugs. Additionally, there was a 4.5-fold increase in the number of compounds with a high calculated partition coefficient (cLogP > 3) and a high total polar surface area (> 75 Ų) in the newly approved drug vs. the established category. Further, prodrugs in established or newly approved lists were found to be converted to active compounds via hydrolysis, demethylases, and kinases. The contribution of cytochrome P450 (CYP) 3A4, as the major biotransformation pathway, has increased from 40% in the established drug list to 64% in the newly approved drug list. Moreover, the role of CYP1A2, CYP2C19, and CYP2D6 were decreased as major metabolizing enzymes among the newly approved medications. Among non-CYP major metabolizers, the contribution of alcohol dehydrogenases/aldehyde dehydrogenases (ADH/ALDH) and sulfotransferases decreased in the newly approved drugs compared with the established list. Furthermore, the highest contribution among uptake and efflux transporters was found for Organic Anion Transporting Polypeptide 1B1 (OATP1B1) and P-glycoprotein (P-gp), respectively. Conclusions The higher portion of biologics in the newly approved drugs compared with the established list confirmed the growing demands for protein- and antibody-based therapies. Moreover, the larger number of hydrophilic drugs found in the newly approved list suggests that the probability of toxicity is likely to decrease. With regard to CYP-mediated major metabolism, CYP3A5 showed an increased involvement owing to the identification of unique probe substrates to differentiate CYP3As. Furthermore, the contribution of OATP1B1 and P-gp did not show a significant shift in the newly approved drugs as compared to the established list because of their broad substrate specificity.
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Southern Chinese Medicine (SCM) is an important sect of Traditional Chinese Medicine (TCM) with its own special cultural style. Species identification is essential for TCM quality control because authentic herbs are possibly substituted with adulterants that would threaten the health of the public or even cause death. Here, we provided the first local reference DNA barcode library based on the second internal transcribed spacer (ITS2) for the molecular identification of SCM. A total of 1512 specimens of southern herbs representing 359 species were collected under the instructions and identification of taxonomic experts. Genomic DNA was extracted, and the PCR reaction proceeded according to standard procedures. After Sanger sequencing, sequence assembling and annotation, a reliable ITS2 barcode library with 1276 sequences from 309 species of Southern herbs was constructed. The PCR efficiency of the whole samples was 84.39%. Characteristics of the ITS2 barcode were analyzed, including sequence lengths and GC contents in different taxa. Neighbor-joining trees based on Kimura 2-Parameter (K2P) genetic distances showed a 67.56% successful rate of species identification with ITS2 barcode. In addition, 96.57% of species could be successfully identified at the genus level by the BLAST method. Eleven plant species were discovered to be cryptic. In addition, we found that there is an incorrect sequence existing in the public database, making a reliable local DNA barcode reference more meaningful. ITS2 barcodes exhibit advantages in TCM identification. This DNA barcode reference library could be used in Southern Chinese Medicine quality control, thus contributing to protecting public health.
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Current estimates report that approximately 25% of U.S. adults use dietary supplements for medicinal purposes. Yet, regulation and transparency within the dietary supplement industry remains a challenge, and economic incentives encourage adulteration or augmentation of botanical dietary supplement products. Undisclosed changes to the dietary supplement composition could impact safety and efficacy; thus, there is a continued need to monitor possible botanical adulteration or mis-identification. Goldenseal, Hydrastis canadensis L. (Ranunculaceae), is a well-known botanical used to combat bacterial infections and digestive problems and is widely available as a dietary supplement. The goal of this study was to evaluate potential adulteration in commercial botanical products using untargeted metabolomics, with H. canadensis supplements serving as a test case. An untargeted ultraperformance liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis was performed on 35 H. canadensis commercial products. Visual inspection of the chemometric data via principal component analysis (PCA) revealed several products that were distinct from the main groupings of samples, and subsequent evaluation of contributing metabolites led to their confirmation of the outliers as originating from a non-goldenseal species or a mixture of plant materials. The obtained results demonstrate the potential for untargeted metabolomics to discriminate between multiple unknown products and predict possible adulteration.
In vitro cytochrome P450 inhibition of major kratom alkaloids: mitragynine (MTG), speciogynine (SPG), speciocilliatine (SPC), corynantheidine (COR), 7-hydroxymitragynine (7HMG) and paynantheine (PAY) was evaluated using human liver microsomes (HLMs) to understand their drug-drug interaction potential. CYP450 isoform-specific substrates of CYP1A2, 2C8, 2C9, 2C19, 2D6, and 3A4/5 were incubated in HLMs with or without alkaloids. Preliminary CYP450 inhibition (IC50) data were generated for each of these isoforms. In addition, the type of inhibition and estimation of the inhibition constants (Ki) of MTG and COR were determined. Among the tested alkaloids, MTG and COR were potent inhibitors of CYP2D6 (IC50, 2.2 and 4.2 µM, respectively). Both MTG and COR exhibited competitive inhibition of CYP2D6 activity and the Ki were found to be 1.1 and 2.8 µM, respectively. SPG and PAY showed moderate inhibition of CYP2D6 activity. Additionally, moderate inhibitory effects by SPC, MTG, and SPG were observed on CYP2C19 activity. Interestingly, inhibition of only midazolam hydroxylase CYP3A4/5 activity by COR, PAY, and MTG was observed while no inhibitory effect was observed when testosterone was used as a probe substrate. In conclusion, MTG and COR may lead to clinically significant adverse drug interactions upon coadministration of drugs that are substantially metabolized by CYP2D6.
Mitragyna speciosa, more commonly known as kratom, is a plant native to Southeast Asia, the leaves of which have been used traditionally as a stimulant, analgesic, and treatment for opioid addiction. Recently, growing use of the plant in the United States and concerns that kratom represents an uncontrolled drug with potential abuse liability, have highlighted the need for more careful study of its pharmacological activity. The major active alkaloid found in kratom, mitragynine, has been reported to have opioid agonist and analgesic activity in vitro and in animal models, consistent with the purported effects of kratom leaf in humans. However, preliminary research has provided some evidence that mitragynine and related compounds may act as atypical opioid agonists, inducing therapeutic effects such as analgesia, while limiting the negative side effects typical of classical opioids. Here we report evidence that an active metabolite plays an important role in mediating the analgesic effects of mitragynine. We find that mitragynine is converted in vitro in both mouse and human liver preparations to the much more potent mu-opioid receptor agonist 7-hydroxymitragynine and that this conversion is mediated by cytochrome P450 3A isoforms. Further, we show that 7-hydroxymitragynine is formed from mitragynine in mice and that brain concentrations of this metabolite are sufficient to explain most or all of the opioid-receptor-mediated analgesic activity of mitragynine. At the same time, mitragynine is found in the brains of mice at very high concentrations relative to its opioid receptor binding affinity, suggesting that it does not directly activate opioid receptors. The results presented here provide a metabolism-dependent mechanism for the analgesic effects of mitragynine and clarify the importance of route of administration for determining the activity of this compound. Further, they raise important questions about the interpretation of existing data on mitragynine and highlight critical areas for further research in animals and humans.
1. Mitragynine is the major indole-based alkaloid of Mitragyna speciosa (kratom). Decoctions (teas) of the plant leaves have been used traditionally for cough, diarrhoea, pain, hypertension, and for the treatment of opioid addiction. In the West, kratom has become increasingly utilized for mood elevation, pain treatment, and as a means of self-treating opioid addiction. 2. Metabolic pathways of mitragynine were identified in human liver microsomes (HLM) and S9 fractions. A total of thirteen metabolites were identified, four oxidative metabolites and a metabolite formed by demethylation at the 9-methoxy group were the major metabolites of mitragynine. 3. The cytochrome P450 enzymes involved in the metabolism of mitragynine were identified using selective chemical inhibitors of HLM and recombinant cytochrome P450. The metabolism of mitragynine was predominantly carried out through the CYP3A4 with minor contributions by CYP2D6 and CYP2C9. The formation of five oxidative metabolites (Met2, Met4, Met6 Met8 and Met11) was catalyzed by the CYP3A4. 4. In summary, mitragynine was extensively metabolized in HLM primarily to O-demethylated and monooxidative metabolites. The CYP3A4 enzyme plays a predominant role in the metabolic clearance of mitragynine and also in the formation of 7-hydroxymitragynine (Met2), a known active minor alkaloid identified in the leaf material.