Miraruira is a medicinal plant-based product (MPBP) that is widely used in the state of Amazonas for the treatment of diabetes, though its botanical identity remains unclear, which raises concerns about authenticity and therapeutic consistency. One solution to this problem is the use of mass spectrometry-based approaches, which have emerged as powerful tools for verifying botanical origin based on chemical composition. Thus, to confirm the botanical authenticity of miraruira, direct-injection mass spectrometry (DI-MS) and chemometric analyses (PCA and HCA) were conducted on methanol fractions of Salacia impressifolia and Connarus ruber, both suspected sources of miraruira, as well as commercial samples obtained in street markets in Manaus, Brazil. Additionally, the hexane extracts of C. ruber and the commercial samples were screened for benzoquinones using DI-MS, as these compounds are recurrent in the genus Connarus. The DI-MS and PCA analyses revealed distinct chemical profiles for each species, and identified mangiferin and epicatechin as chemical markers for S. impressifolia and C. ruber, respectively. Furthermore, PCA demonstrated that all the commercial samples exhibited chemical profiles closely aligned with C. ruber. However, the HCA indicated variability among these samples, suggesting C. ruber or related Connarus species are the primary sources of miraruira. Moreover, embelin, rapanone, and suberonone were identified as the main compounds in the hexane extracts of C. ruber and the commercial products. This study successfully confirmed the botanical authenticity of miraruira, identified key bioactive compounds related to its traditional use in the treatment of diabetes symptoms, and demonstrated the effectiveness of DI-MS as a valuable tool for addressing authenticity issues in MPBPs.

Glycosides are widely distributed plant metabolites with remarkable structural diversity and broad biological activities. However, comprehensive strategies for their systematic recognition, extraction, and annotation from complex plant matrices remain scarce, especially for chemically underexplored Amazonian species such as Strychnos jobertiana. In this study, we present an integrated analytical strategy combining leaf spray chemical profiling and feature-based molecular networking (FBMN) analysis to guide extract preparation and enable glycoside annotation from S. jobertiana leaves. Rapid chemical profiling by leaf spray mass spectrometry (LS-MS) enabled the early recognition of glycoside-related ions, including alkaloid and flavonoid derivatives, guiding the preparation of an aqueous extract processed by solid-phase extraction (SPE) before liquid chromatography-mass spectrometry (LC-MS) analysis. The resulting data were explored using FBMN supported by spectral search analysis and manual interpretation of tandem mass spectra. In parallel, the isolation of desoxycordifoline (1), harman-3-carboxylic acid (2), kaempferol 3-O-(2”,6”-di-O-rhamnopyranosyl) glucopyranoside (3), and kaempferol-3-O-neohesperidoside (4) provided structural support for the annotation of molecular clusters. Two major glycoside clusters were characterized, one dominated by flavonoid glycosides, and another composed primarily of monoterpene-derived glycosides. Overall, 21 compounds were annotated, including derivatives related to compounds 1-4, such as secoxyloganin (8), kaempferol-3‑O-glucoside (5), kaempferol3-O-rutinoside (6), and kaempferol-3-O-rungioside (7), and diagnostic fragment ions associated with glycoside compounds were highlighted. This integrated workflow demonstrates the value of LS-MS profiling as a decision-making tool for extract preparation and highlights feature-based molecular networking (FBMN) as a powerful approach for glycoside annotation, contributing to the chemical knowledge of Amazonian plant species.