# Mixtures Biotransformation: Multilayer Molecular Networking of Kratom Liver Metabolites

## TL;DR

This study uses molecular networking to analyze kratom's complex metabolism, revealing how liver enzymes transform its compounds into diverse metabolites.

## Contribution

The study introduces multilayer molecular networking to characterize biotransformation of natural product mixtures in a semitargeted way.

## Key findings

- Phase I and II metabolites of kratom compounds were identified using liver S9 and mass spectrometry.
- Metabolic profiles of individual kratom components differ significantly in the context of total extracts.
- Molecular networking enhances metabolite identification and understanding of kratom's pharmacological effects.

## Abstract

Metabolites generated from therapeutic drugs can exhibit
diverse
pharmacological effects, making knowledge of metabolites important
to understand the overall mechanisms of therapeutic action. Methods
to study the metabolism of single or simple mixtures of bioactive
agents are often insufficient to address the chemical diversity of
natural product mixtures. Molecular network analysis has emerged as
a powerful approach to gain an understanding of complex chemical mixtures.
In the present study, we used in vitro biotransformation
and molecular network analysis of single compounds and extracts of
the medicinal plant, kratom (Mitragyna speciosa Korth., Rubiaceae), to test the utility for characterizing natural
product mixtures. We analyzed biotransformation products from single
compounds and multiple chemotypes of kratom leaf extracts using human
liver S9 and liquid chromatography–high-resolution mass spectrometry.
Multilayer molecular networking of the polymetabolism of the entire
natural product mixture provided predicted metabolites from precursors
in a semitargeted manner. Both phase I and phase II metabolites of
precursors were detected, with the metabolic profiles of individual
components being substantially different in the context of total extracts.
Application of molecular networking to mixture metabolism will enhance
metabolite identification and the understanding of the therapeutic
and toxicological mode(s) of action of pharmacologically active plants.