Leveraging metabolic similarity in a 1H NMR database of medicinal plants to advance pharmacognostic insights

Natural products remain a central resource for drug discovery, and increasing evidence suggests that therapeutic effects often arise from the combined action of multiple constituents rather than single compounds. In this context, metabolomic profiling is essential for comparing complex plant chemical phenotypes, and 1 H NMR provides robust whole-profile fingerprints that support cross-species metabolic barcoding and systematic comparison. In this study, we establish and apply a standardized large-scale 1 H NMR database to enable macroscopic metabolomic similarity profiling of medicinal plants. Specifically, using 1 H NMR profiles from 656 traditional medicinal herbs, we demonstrate how this standardized large-scale metabolomic framework can be applied to key challenges in medicinal plant research, including quality control across different locations and time periods, identification of metabolically similar alternative species, and compositional analysis of multi-herb formulations. Our findings demonstrate the utility of this NMR-based strategy as a scalable approach for standardization, authentication, and holistic characterization of medicinal plants, advancing the field beyond reductionist paradigms. This study establishes a standardized large-scale 1 H NMR database of medicinal plants and introduces a macroscopic framework for large-scale metabolomic similarity profiling that enables chemotaxonomic contextualization, quality surveillance, and identification of metabolically similar candidate substitutes.