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The discovery of bioactive natural products is often challenged by the complexity of isolating and characterizing active compounds within diverse mixtures. Previously, we introduced a 1H NMR-based weighted gene correlation network analysis (WGCNA) approach to identify spectral features linked to growth inhibitory activity of Piper (Piperaceae) leaf extracts against model plant, fungal, and bacterial organisms. This method enabled us to prioritize specific spectral features linked to bioactivity, offering a targeted approach to natural product discovery. In this study, we validate the predictive capacity of the WGCNA by isolating the compounds responsible for the bioactivity-associated resonances and confirming their antifungal efficacy. Using growth inhibition assays, we verified that the isolated compounds, including three novel antifungal agents, exhibited significant bioactivity. Notably, one of these compounds contains a rare imidazolium heterocyclic motif, marking a new structural class in Piper. These findings substantiate the 1H NMR-based WGCNA as a reliable tool for identifying structural types associated with biological activity, streamlining the process of discovering bioactive natural products in complex extracts.