Integrative LC-HR-QTOF-MS and Computational Metabolomics Approaches for Compound Annotation, Chemometric Profiling and In Silico Antibacterial Evaluation of Ugandan Propolis.

Background/Objectives: Propolis is a complex bee product with a composition that varies according to local vegetation, environmental conditions, and bee foraging behaviours. Recently, gas chromatography-mass spectrometry (GC-MS) has been employed in Uganda to analyse its volatile components. This study examined Ugandan propolis non-volatile metabolites to determine chemotypes and identify antibacterial compounds. Methods: Ethanolic extracts were analysed using liquid chromatography-high-resolution quadrupole time-of-flight mass spectrometry (LC-HR-QTOF-MS) in an untargeted MS/MS mode. Data processing was carried out using MZmine, then annotated with Global Natural Products Social Molecular Networking (GNPS) and SIRIUS. Chemometric methods assisted in identifying regional chemical signatures. Metabolites highlighted by the heatmap were evaluated for antibacterial activity using molecular docking against bacterial targets, followed by ADMET (absorption, distribution, metabolism, excretion, and toxicity) assessments. Results: Out of 3252 features, 234 and 52 putative compounds were annotated in GNPS and SIRIUS, respectively, as indicated by molecular networking, suggesting high chemical complexity. The chemical space mainly comprises flavonoids (including glycosides, aglycones, methylated, and prenylated derivatives), phenolic acids, amides, hydroxycinnamate derivatives, lignans, megastigmanes, and various diterpenoid skeletons. Multivariate analyses clearly distinguish geographical chemotypes, separating flavonoid-rich regions from diterpenoid-rich regions. Docking studies revealed flavonoids, diterpenoids, and lignans with strong predicted antibacterial activities and favourable ADMET profiles. Conclusions: This study provides the first LC-MS characterisation of the non-volatile metabolome of Ugandan propolis, thereby expanding its chemical diversity. Metabolomics and computational approaches lay a foundation for future ecological, chemotaxonomic, and pharmacological research.