Leveraging Metabolic Similarity in a ¹H NMR Database of Medicinal Plants: A Macroscopic Approach to Advancing Pharmacognostic Insights

The transition from targeted analyses to a holistic systems biology approach has required the integration of various OMICS technologies, including genomics, proteomics, and metabolomics, to comprehensively profile biological systems. Since its emergence in the late 1990s, metabolomics has become a widely applied discipline across many areas of life sciences, particularly in the study of natural products and their bioactive constituents. Natural products have long served as a valuable source for drug discovery due to their structural complexity and potent biological activity. While early efforts focused on isolating single bioactive compounds, increasing evidence supports the notion that therapeutic effects often stem from the synergistic action of multiple constituents. This evolving perspective has driven interest in the comprehensive chemical profiling of medicinal plants, viewing them as holistic bioactive entities. Among the tools for metabolomic profiling, Nuclear Magnetic Resonance (NMR) spectroscopy - alongside mass spectrometry - has played a central role. However, the full potential of NMR remains underexploited, despite its unique advantages in natural product profiling. One such advantage lies in enabling robust metabolic comparisons across plant species, aligning with the emerging concept of metabolic barcoding of natural products. In this study, we propose a macroscopic approach using an NMR database of medicinal plants to demonstrate the broad applicability of the method in systematic plant profiling. Specifically, we present NMR profiling data from 656 traditional medicinal herbs in an effort to address key challenges in medicinal plant research. These include quality control of plant materials collected across different locations and time periods, identification of alternative species based on metabolic similarity, and compositional analysis of multi-herb formulations, which may also enable bioactivity prediction based on shared metabolic profiles. Our findings demonstrate the utility of NMR-based metabolic barcoding as a scalable strategy for standardization, authentication, and holistic characterization of medicinal plants, advancing the field beyond reductionist paradigms.