Biochemometric 2D NMR-Based Heterocovariance Analysis: A Targeted Approach for Identifying Bioactive Compounds in Complex Mixtures

TL;DR

This paper introduces a new method using 2D NMR to identify bioactive compounds in complex mixtures, tested on plant extracts.

Contribution

A novel 2D NMR-based heterocovariance analysis workflow for targeted identification of bioactive compounds in complex mixtures.

Findings

The workflow successfully identified bioactive compounds in artificial mixtures of pentacyclic triterpenes.

The method was validated using a triterpene-rich Eriobotrya japonica leaf extract.

The approach enables accurate identification of compounds modulating RORγ and TGR5 receptors.

Abstract

Biochemometric approaches,
which integrate bioactivity data with
spectroscopic or spectrometric data, offer significant potential to
streamline the discovery of bioactive compounds in targeted isolation
strategies. However, the complexity of natural extracts and the presence
of structurally similar analogs make this process time-consuming and
resource intensive. This study introduces a 2D nuclear magnetic resonance
(NMR)-based heterocovariance analysis (HetCA) workflow to identify
chemical features that correlate positively or negatively with bioactivity
in complex mixtures. As a proof-of-concept, the workflow was established
using artificially mixed samples of pentacyclic triterpenes which
were screened for modulatory activities of the retinoic acid receptor-related
orphan receptor gamma (RORγ) and the G protein-coupled bile
acid receptor (TGR5). The validated concept was then exemplified using
a triterpene-rich Eriobotrya japonica leaf extract. The applied workflow enabled the targeted and accurate
identification of bioactive constituents from E. japonica that modulate RORγ and/or TGR5 using this newly developed
biochemometric 2D NMR HetCA approach.

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