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

Abstract

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.

Figure 1

Structures of select alkaloids present in kratom (Mitragyna speciosa), mitragynine (1), 7-hydroxymitragynine (2) and speciofoline (3).

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% confidence intervals). The underlying cause for these apparent differences in the data was further explored with loadings plot and volcano plot data (Fig. 3).

Figure 3

Plots of significant 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 significant 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 significant the feature is. The speciofoline-rich group (red circles) yielded 120 significant features, while 19 features were significantly distinct in the non-speciofoline-rich grouping of commercial samples (purple circles). Speciofoline (3) was found to be a metabolite that differed significantly across sample groups, while mitragynine (1) and 7-hydroxymitragynine (2) were not significantly different 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. The 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.

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. E_max and EC₅₀ values for cAMP accumulation and β-arrestin2 recruitment are listed in the table.

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.