PLANTA Protocol for the Direct Detection and Identification of Bioactive Compounds in Complex Mixtures via Combined NMR-HPTLC-Based Heterocovariance.

Abstract

The assignment of bioactivity to compounds within complex natural product (NPs) mixtures remains a significant challenge in NPs research. The present research introduces a comprehensive protocol, named "PLANTA (PhytochemicaL Analysis for NaTural bioActives)" protocol, for the detection and identification of bioactive compounds in complex natural extracts prior to isolation combining the NMR-HeteroCovariance Approach (NMR-HetCA), high-performance thin-layer chromatography (HPTLC), and chemometric techniques. This study emphasizes two novel components: STOCSY-guided targeted spectral depletion, adapted to resolve overlapping NMR signals in complex matrices, improve minor component detection, and facilitate identification through NMR databases, as well as a new SHY variant termed SH-SCY (Statistical Heterocovariance - SpectroChromatographY), a new cross-correlation method linking orthogonal datasets by identifying the corresponding HPTLC spot from a single NMR peak and reconstructing of the 1H NMR spectrum from a specific HPTLC spot, enhancing dereplication confidence. In this proof-of-concept study, an artificial extract (ArtExtr) composed of 59 standard compounds was evaluated for the detection of compounds active against the free radical 2,2-diphenyl-1-picrylhydrazyl (DPPH). Statistical approaches were applied to the spectral, chromatographic, and bioactivity data to identify the highly correlated bioactive compounds. The PLANTA protocol achieved an 89.5% detection rate of active metabolites and 73.7% correct identification of them. The integration of NMR and HPTLC with HetCA provides a robust and sensitive strategy for preisolation identification of bioactive constituents. This methodology addresses core challenges in metabolite profiling of complex mixtures and offers a streamlined, reproducible workflow for natural product dereplication and discovery.